Logit and Probit Models Compared for WTP Analysis

Outline Of A Literature Review
Literature Review 15 pages
Pb lead!!!
Pb in urban soil
In soil, Pb is relatively immobile and remains in the surface horizon for many years (t½ ~ 700yrs;
Semiali et al 2004). Characteristically, Pb concentrations are highest in roadside soil and in
proportion to historical traffic flows, although over the year soil re–suspension is believed to have
widened its distribution to give a city–wide distribution.
Soil Pb in many cities with a history Pb–gasoline use, show similar distributions with the heavily
trafficked inner areas having the highest concentrations and decreasing concentrations towards the
outer parts of a city (Laidlaw and Fillippelli 2008).
Across England, urban areas typically have higher soil background concentrations of Pb than the
surrounding countryside; Ander et al 2013 suggested an overall mean of 820 mg kg–1 for urban
areas as against 180 mg kg–1 for the countryside. A recent high–density geochemical soil survey of
the Greater London Area (GLA; BGS 2011) showed that the inner central region of the oldest and
most intensely urbanized and industrial areas, about 25% of the GLA area, typically have
concentrations > 346 mg kg–1; this value is greater than the proposed new contaminated land
category four screening levels for residential land and allotment land–use (CL4SL 2014).
Soil re–suspension
Roadside soils are subjected to turbulence as vehicles pass by, and roadside dust emissions are
related to vehicle speed (exponentially), traffic volumes and
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Eq02 Life Monitor
Cold climates have proven to be associated with a range of health risks including frostbite and
hypothermia. According to a study by Gasparrini et al (2015) published in The Lancet, cold
temperature is responsible for advancing approximately 7.29% of deaths between 1985 and 2009 for
13 countries including Canada. Elderly people are at a particularly high risk for cold–related
mortality due to mental, cardiovascular, and respiratory illnesses. Elderly people are more
vulnerable to hypothermia as the body's ability to regulate temperature and sense cold lessens with
age. Additionally, many elderly people are not able to communicate when they are cold or are not
mobile enough to get to warmth. A global meta–analysis by Yu et al (2011) involving almost 13
million elderly deaths concluded that for each 1 ºC decrease in temperature there was a 1–2%
increase in ... Show more content on Helpwriting.net ...
This device differs from previously discussed models in terms of the method of temperature
measurement. The LifeMonitor relies on a core temperature capsule, VitalSense, that is ingested and
transmits readings to the sensor electronics module (SEM) in real–time (Figure 3). This device has
recently been replacing the current tympanic thermometer used by firefighters to reduce the risks
such as cardiac arrest. In a study by McKenzie & Osgood (2004) the accuracy of the VitalSense
system was measured against that of a rectal thermometer as comparison. The observed level of
agreement between the two devices (0.04 ºC) suggests that the VitalSense is a viable alternative to
consider for measurement of core temperature. However, the core temperature was not recorded on
several occasions due to an inactive capsule. The transit time of the capsule varied from 0.52 to 5.6
days therefore requiring many capsules for use throughout cold winter months which would be very

What Is The Methods Of Objective Control Of UGV?
Another important problem faced in autonomous control of UGV due to size is safely maneuvering
around obstacle while avoiding it. Many obstacle avoidance algorithms are developed for fast and
smooth motion of UGV among unexpected obstacles [16]. These algorithms generate actions to
avoid obstacles in a response to feedback from sensors. Some of the methods for controlling UGVs
are artificial potential field method [17], [18], the vector field histogram method [19], [17–21], the
dynamic window approach [22], [23], above discussed PID controller and MPC. Taking size of the
UGV into account, improvements in algorithms originally developed for small UGVs are made and
algorithms for large UGVs are proposed for avoiding discrete static obstacles ... Show more content
on Helpwriting.net ...
For the higher reliability, study is conducted using two different vehicle dynamic model for single
four–wheel truck, one with 2 degrees of freedom and another with 14 degrees of freedom. Report of
the study shows accurate maneuver of obstacle avoidance and trajectory tracking but there are still
some assumptions are made such as velocity of the UGV during the task is constant and the terrain
is flat.
Many studies have been done to localize and create model of environment using simultaneous
localization and mapping (SLAM). The aim of SLAM is to construct a map of the environment and
the trajectory on which robot is being driven. One of the most popular of these studies was an
approach provided by Smith and Cheeseman in a seminar paper in 1986 and it was developed and
implemented in [31]. In this approach, Extended Kalman Filter (EKF) is used to estimate subsequent
robot pose and map. The EKF estimates the SLAM posterior in a form of high–dimensional
Gaussian overall features in the map and the robot pose. The single hypothesis data association and
quadratic complexity because of the high dimensional Gaussian estimation of robot's state and
landmark locations, makes the off–diagonal elements very large in covariance matrices. That is why,
if the environment has many landmarks, the EKF–SLAM algorithm requires high time to update
which increases cost of the computation.

Error Performance Improvement Of A Multiplexed Mimo...
Error Performance improvement in Spatially Multiplexed MIMO Systems over Weibull–Gamma
Fading Channel
Keerti Tiwari and Davinder S. Saini
Department of Electronics and Communication Engineering
Jaypee University of Information Technology
Waknaghat, Solan, (H.P.) – 173234, India
E–mail– keerti.tiwari@mail.juit.ac.in, davinder.saini@juit.ac.in
Abstract– In multiple–input multiple–output (MIMO) systems, spatial demultiplexing at the receiver
is a motivational task. Thus, several detection techniques are investigated in existing literature.
There is a tradeoff between computational complexity and optimal performance in many detection
techniques. The ordered successive interference cancellation (OSIC) with minimum mean square
error (MMSE) is used to improve the error performance. However, maximum likelihood (ML)
detection gives optimal performance at the higher complexity level whereas MMSE–OSIC detection
is less complex. Therefore, MMSE–OSIC2 detection is suggested as a solution. In this paper, spatial
multiplexed (SM) MIMO systems are considered to evaluate error performance with different
detection techniques such as MMSE–OSIC, ML and MMSE–OSIC2 in a composite fading i.e.
Weibull–gamma (WG) fading environment. In WG distribution, Weibull and gamma distribution
represent multipath and shadowing effects respectively. It is shown by simulation results that the
MMSE–OSIC2 detection technique gives the improved symbol error performance (SER) which is
closely likely ML performance

Comparing Logit And Probit Models Essay
In Logit and Probit models, a dependent variable takes only two values that represent the occurrence
of an event (yes or no) or a choice between two alternatives. In the current case, to model choice
status of each individual WTP for improved solid waste management respondents differed in age,
educational attainment, income, sex and other observable characteristics. These are denoted by S. In
the dichotomous choice method, individuals are assumed to have utility function, U, income (I), and
a set of conditioning factors (S): U(I; S)
Each respondent was confronted with a specified bid value, BID, which she or he may contribute
towards the management initiative. It is assumed that the individual would accept a suggested BID
to maximize his or her utility under the following condition and reject it otherwise (Hanemann,
1984):
U(1, I –BID; S)+ ε1 ≥U(0, I; S) + ε0
In the current case, ε1 and ε0 are considered as independently distributed random variables with
zero means. Therefore, the probability that a household would decide to pay for the proposed
improved solid waste management for Delhi is the probability that the conditional indirect utility
function for proposed intervention is greater than the conditional indirect utility function for the
status quo. The dependent variable is dichotomous and equals 1, if the ith household is willing to
pay a bid and 0, otherwise. The general form of the estimation can be written as:
〖

Quantitative Study On Quantitative Research Study
Quantitative Study
The article is a quantitative research study. There were three types of data collected in this study.
Data was collected through structured interviews, inter–rater and validity data, statistical analysis,
and descriptive data. Interviews took place at the Department of Forensic Psychiatry in Stockholm.
A trained research assistant carried out the interview after receiving preparatory training that
consisted of 12 test interviews, under the guidance of the first author. These interviews were
instructed to clarify the exposure information if the interviewee was inconsistent in their response by
using other sources such as (police reports, medical files). The structured interview covered offender
and offence–specific information, exposure to alcohol, and illegal and prescribed psychotropic
drugs. The inter–rater reliability test was conducted using two raters score information
independently from 16 sit–in interviews. Data was calculated using Cohen's k for categorical,
nominal data and for continuous data intra–class correlation coefficients (ICCs). The two–way
ANOVA, random model type, was used to permit generalization of ICCs to others individual raters.
The descriptive data was generated using the participants age ranging from 17 to 76 years old;
including principal clinical diagnoses assigned according to the Diagnostic and Statistical Manual
(DSM–IV). However, the Standard Mentel–Haenszel methods, sparse data in each stratum, were
used for statistical

In Addition To Saving And Bequest Channels, The Proposed
In addition to saving and bequest channels, the proposed model in this paper identifies two
additional channel of child labor. These are heterogeneity in child 's ability, which causes
heterogeneity in the cost of education, and differential future expectation of parents depending on
their socio–economic background. I attempt to capture these four channels using a number of
variables. For saving, I use income of household head and for bequest, I use whether the household
owns any house. Here income of household head may be under–reported or may have some types of
measurement errors, so, we use several other variables to instrument it. Ownership of a house is
used to capture bequest as housing price is very high almost across the country ... Show more
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Secondly, the socio–economic group in which the household head belongs to is also crucial in
forming household head 's expectation. Thus, I use household head 's gender ($Head_female$),
Household head 's sector of employment ($Sector$), religion of household head ($Religion$), and
the location of household ($Urban$). Using these variables I estimate the following models: Where
$y$ is child 's working hours per day, $ extbf{X}={Urban, Sector, Female, Head_literacy, Religion,
House,$ $ Head_income, Head_female, Dropout_ability, Dropout_cost, Dropout_income}$, $
extbf{Z}={Urban, Head _sector,$ $ Female, Head _literacy, House, Land, Num _hhchld, Head
_literacy, Head_age, Dropout_ability,$ $Dropout_cost, Religion, Dropout_income, TV,
Head_female}$, $Q_{N}(eta) = g_{N}(eta) 'W_{N}g_{N}(eta)$, $g_{N}(eta)=frac{1}
{N} sum_{i=1}^{N}Z 'epsilon$, and $W$ is a $N imes N$ positive semi–definite matrix. In
addition, I also estimate logit and probit model of child labor, where I attempt to estimate the
probabilities of being a child labor with respect to the variables mentioned above. Results of these
models are shown in the following table:
In the above table second column reports the OLS estimates. Dummy $Urban$ has positive
coefficient, which indicates that child labor on an average work 0.4 hour more in

Crime Scenes: Agarose Gel Electrophoresis Essay
As seen on many crime shows and in real–life crime scenes, it is necessary to be able to identify
DNA. Most of the time, this is done using a technique known as gel electrophoresis. Gel
electrophoresis is a method used to separate the macromolecules that make up nucleic acids, such as
DNA and RNA, along with proteins. Gel electrophoresis is significant because it has given scientists
insight on what cells cause certain diseases and has led to advancements in DNA and fingerprint
identification. My experiment will use gel electrophoresis to compare the separation of food dye in
different agarose concentrations. The background for this experiment includes the following
subjects: inventors, real–world uses, necessary components, separation, ... Show more content on
Helpwriting.net ...
This theory was formulated in 1970 and is one of the most recent on the topic of gel electrophoresis.
The National Academy of Science states, The behavior of macromolecules in gel filtration and gel
electrophoresis may be predicted from Ogston's model for random mesh work of fibers. This model
has been generalized to apply to non–spherical molecules and to several gel types. The theory
defines conditions for optimal separation and optimal resolution in gel electrophoresis and gel
filtration (Unified Theory for Gel Electrophoresis and Gel Filtration). There are a few components
that compose a gel electrophoresis chamber. First of all, there is a chamber used to contain the gel.
The gel used in my experiment will be made from agarose. In order to create an electric field, there
are positive and negative electrodes attached to a power source. My experiment will use alligator
clips as the electrodes and nine–volt batteries as the power source. A buffer solution, in this case a
1% solution of baking soda, submerges the gel to allow the ions to carry through and maintain the
stability of the Ph levels. A comb is used to generate wells inside of the gel to hold the samples. The
comb will be made of styrofoam (Forensic Science: Building Your Own Tool For Identifying DNA).
Proteins, or nucleic acids, are isolated and separated within a gel. The gel is cast in a thin, welled
slab. In this particular experiment, the gel will be

Ordered Successive Interference Cancellation ( Osic ) Is...
Abstract– In this paper, ordered successive interference cancellation (OSIC) is adopted with
minimum mean square error (MMSE) detection to enhance the multiple–input multiple–output
(MIMO) system performance. The optimum detection technique increases the system complexity
with improved error rate performance. Therefore, MMSE–OSIC detection is used which gives
reduced error rate compared to traditional MMSE with a considerable level of complexity. The
system performance is analyzed in a composite fading environment which deals with multipath and
shadowing, known as Weibull–gamma (WG) fading environment. Along with the composite fading,
a composite noise i.e. additive white generalized Gaussian noise (AWGGN) model is taken into
account to form various noise scenarios such as impulsive, Gamma, Laplacian, Gaussian and
uniform noise. Consequently, generalized Q– function is used to develop such noise scenario. The
average symbol error probability (ASEP) of MIMO system is computed for 16–quadrature
amplitude modulation (16–QAM) using MMSE–OSIC detection in WG fading with AWGGN.
Analytical expressions are evaluated in terms of Fox–H function (FHF). These expressions
demonstrate the best fit to simulation results.
Keywords– MIMO, MMSE–OSIC, WG fading, AWGGN, M–QAM, ASEP.
1. Introduction
In MIMO systems, spatial multiplexing is used for high data rate transmission and spatial diversity
is used to achieve reliable communication. However, there is a tradeoff between diversity and

Current State Of The Art Mdss
This section describes literature review conducted in the field of MDSS in order to understand
current state–of–the–art MDSS in the field of HIS. Throughout the process of literature review, it
was observed there exists already huge amount of literature on how MDSS was built in the field of
HIS. After carefully studying the entire literature, it was found that the existing MDSS were broadly
classified into 3 systems. Forecasting binary outcomes Forecasting classification outcomes and
Forecasting outbreaks. In the next paragraphs, this thesis paper discussed various factors of 3
mentioned MDSS like main motivation for the implementation of new MDSS, different data mining
(DM) algorithms used, techniques used to improve the ... Show more content on Helpwriting.net ...
(Adeyemi, Demir, Chaussalet, 2013); (Demir, 2014) argued that readmission rates should not be
accounted for 30 days after surgery, moreover depending upon the disease type it varied from 30–90
days or other minor diseases had a short time frame of 14 days to longer time frame up to 1 year or
up to 45–days from diagnosis. To overcome this serious readmission rate problem, Center for
Medicare and Medicaid services (CMS) imposed huge penalties on the hospitals, which had serious
readmission rates (Amarasingham et al., 2010). Furthermore, most of the developed country
governments devoted high importance to identify the patients who are at high risk of readmitting so
that hospitals can plan the patient pathways. According to (Demir, 2014) they are: a. Prevention and
wellness promotion for relatively low risk patients b. Supporting self–care interventions for
moderate risk patients c. Early intervention care management for patients with emergent risk and d.
Intensive case management for very high risk patients Most of the researchers created many
predictive models that predict the patient's readmission with a simple yes or no. Few studies
described in table 2, outline who conducted the study, data setting, data mining algorithm used and
their accuracies. Source Population setting Data Mining Algorithm ROC statistic Anderson and
Steinberg,1985 Medicare patients in the USA from 1974–1977 Logistic

Multivariate Statistical Analysis : Natural And Physical...
Multivariate Statistical Analysis
Statistical methodology designed to obtain information from data sets that include simultaneous
measurements on many variables is called multivariate statistical analysis (1). Multivariate statistics
helps to study how the variables are related to one another, and also how they work in combination
to differentiate between the cases on which the observations are made. Several research disciplines
such as biology, medicine, environmental Science, Psychology, Sociology, Economics, Education,
Archaeology, Anthropology have broad applications of Multivariate statistical analysis (2).
Numerous interesting research questions about natural and physical processes are so complex that
they require multivariate ... Show more content on Helpwriting.net ...
The usual regression method does not work when we are given a binary response variable. In these
situations we should think about using the logistic regression (4).
Considering the following model estimated regression equation (equation 1) It is called as simple
Logistic regression, because there is only one predictor and also the exponential function is never
0 or negative.
There are some other models available for dichotomous and non–dichotomous categorical
outcomes. Probit regression: A model used for binary outcomes, but instead of the logit
specification, the probit uses the cumulative distribution function for a standard normal distribution.
Multinomial Logistic Regression: A model used for outcomes that are nominal, e.g., blood type (A,
B, AB, O). Ordinal Logistic Regression: A model used for outcomes that are ordinal, e.g., Likert
scale questionnaire (excellent, very good, good, fair, poor).
Simple logistic regression application involves one dichotomous variable and one independent
variable. Multiple logistic regression application involves when there is a single dichotomous
outcome and more than one independent variables (4) (5).
Applications in Bio–Medical Research:
Logistic regression is one of the widely used tool in fields such as bio–medical research, medical,
epidemiology, social sciences, engineering, ecology, psychology and marketing. For instance
logistic regression can be used to

An Outage Occurrence? Based On The Expected Effect Of...
Modeling Overview The models developed for this research focused on addressing the following
question: What is the likelihood of an outage occurrence? Based on the expected effect of weather,
demographics, and socioeconomic features on outages, some hypotheses to be tested are as follows:
Hypothesis #1 – Weather has an influence on power outages. Snow, rain, wind and temperature have
an impactful effect on underground cables, overhead lines, or complete electrical infrastructure that
can cause electrical grids to fail. Weather also effects consumer demand, which drives changes on
the electrical grid. Hypothesis #2 – Income changes will increase/decrease energy consumption and
power outages. Changes in income have an effect on the commercial and residential developments
in the area. The changes affect the max load capabilities of the electrical grid. Income changes have
a hierarchy of purchases. For example, if a group has a change of income that now allows air
conditioner purchases, the electrical load will change quickly. Hypothesis #3 – Ethnicity of a
population has an influence on power outages. Certain ethnicities have generalized electrical usage.
Some groups do not use air conditioners, but others leave the windows open into the winter. That
type of demographic features may be impactful explanatory variables to help predict outages. The
objective of this Capstone is to utilize data mining procedures and the business analytica framework
learned throughout

Factors That Affect The Body Mass Of Adult Female Yellow...
Over the past few decades, the expression of a variety of life history, behavioural, and physiological
traits have been correlated with systematic environmental changes in temperature, growing season
length, and precipitation1,2. The assumed causal pathway in most if not all studies is that
environmental changes drive changes in traits, and these changes lead to changes in fitness3. This
causal model has rarely been explicitly tested and the quantitative genetic consequences of such
changes in fitness are mostly unknown. Here, we close that gap by combining both a path analysis
and a quantitative genetic approach on 37 years of data on a wild population of adult female yellow–
bellied marmots. We demonstrate that changes in body mass were driven by the changes in spring
temperature, but contrary to any expectations the increase in fitness was not caused by changes in
temperature or body mass. Changes in body mass are thus not directly responsible for the observed
change in population dynamic. In addition, we found a constant positive selection at the phenotypic
level on body mass, a constant heritability of fitness, and a varying (but not trending) heritability of
body mass. Our results clearly indicate that the changes in body mass are not due to an evolutionary
response, and that evolutionary dynamics have not been modified because the fitness–body mass
relation has remained constant. Global climate changes have the potential to impact dramatically
multiple traits, as well

Notes On The And Flow Data
2 DATAAND OPERATIONALIZATION
Tostudy the impactofpoliticalaffinity onFDI,I employ the datafrom UNCTAD,whichrecord bilateral
FDI stock and flow data for more than 200 countries from 2001 to 2012. Since FDI flow data can be
a poor conceptual choice for answering political questions (Kerner, 2014;
Sorens and Ruger, 2015; Benacek et al., 2014), I choose to use only the stock data.
One possible drawback for UNCTAD data is its compilation by reports from different countries,
which have varied reporting rules and rigorousness. As a result, it may have serious measurement
errors or substantial missing values. However, this weakness appears to plague the other two major
FDI data resources (IMF and OECD) as well. 1 In addition, since biased or ... Show more content on
Helpwriting.net ...
This choice is mainly out of convenience. It is also workable to use the outstock data instead. The
interpretation will be similar.
2.1 POLITICAL AFFINITY
Admittedly there is no perfect measure for two countries' political closeness. To somehow proxy this
measurement, I use the ideal points compiled by Erik Voeten and colleagues from the UN general
assembly roll–call voting data. 3 This dataset has ideal point estimates for countries from 1946 to
2014. To measure political affinity for a given country pair, I take the absolute value of the
difference between their ideal points and code them as idealPoint. In this regard, the smaller value
the idealPoint variable is, they closer is the country pair's relationship.
2.2 CONTROLS
As mentioned before, to somehow mitigate the reporting country's biasness, I need to apply controls
over the country's general FDI volume. More importantly, the volume of FDI stock in a certain
country is substantially affected by the attractiveness of the destination and the financial caliber of
the donor country. In this regard, I tally the total volume of both the instock FDI for the recipient
country and the outstock FDI for the donor country. The former is used as a proxy for the
destination's investment attractiveness and the latter for the donor's financial caliber. This way I can
sidestep the use of other economic controls and focus on studying how political affinity affect FDI.
3This dataset can be downloaded from Harvard.

A Digital Representation Of Underwater Bathymetry
Bathymetry derived terrain variables are indicative of seabed morphology and can be used as
predictors of suitable benthic habitats. A digital elevation model (DEM) is a digital representation of
the elevation of locations on the land surface, and in the case of this report can be used as a digital
representation of underwater bathymetry. The DEM can be used to derive various benthic terrain
variables of underwater systems (Pescus 2012). Some terrain variables include depth, slope,
rugosity, aspect and terrain variability. Depth is a major environmental gradient which controls
species distribution, as various under water organisms rely on photosynthesis to survive and grow.
As depth increases, less sunlight penetrates the water, resulting in a limited source of energy for
photosynthesizing organisms (Pescus 2012). Additionally bigger/older individuals often prefer
deeper waters (Lauria et al. 2015). Slope (expressed in degrees with values from 0° to 90°) describes
the rate of change in elevation over distance. Low values of slope correspond to flat ocean bottom
(or areas of sediment deposition) while higher values indicate potential rocky ledges. (Lauria et al.
2015) The slope of many marine systems has a strong influence on the distribution of benthic
components, such as coral in coral reef systems. Slope can first be a derivative of a DEM and then
calculated using spatial analyst tools in ArcGIS. The slope represents the rate of change of elevation
for each DEM cell

A New Approach to Portfolio Matrix Analysis for Strategic...
A NEW APPROACH TO PORTFOLIO MATRIX ANALYSIS
FOR STRATEGIC MARKETING PLANNING
1
2
Vladimir Dobrić , Boris Delibašić
Faculty of organizational science, vdobric@fon.rs
2
Faculty of organizational science, delibasic.boris@fon.rs
1
Abstract: Portfolio matrix is probably the most important tool for strategic marketing planning,
especially in the strategy selection stage. Position of the organization in the portfolio matrix and it's
corresponding marketing strategy depends on the aggregation of values of relevant strategic factors.
Traditional approach to portfolio matrix analysis uses averaging function as an aggregation operator.
This approach is very limited in realistic business environment characterized by complex ... Show
more content on Helpwriting.net ...
It is clear that the use of weighted arithmetic mean as an aggregation operator can't express all the
possible interactions between strategic factors that exist in a realistic business environment. This
explains why the traditional approach to portfolio matrix analysis is highly limited, with the
inherited weaknesses that can't be overcome without substantial modification. Therefore, under
previous conditions, it is obvious that a new approach to portfolio matrix analysis is needed. This
new approach must take in consideration all the possible forms of interactions between strategic
factors that can occur in a realistic business environment.
These interactions can be expressed with a logical aggregation operator, so a new approach to
portfolio matrix analysis can be based on this operator. W eighted arithmetic mean and other known
aggregation operators are just, as we will see in the following sections, special cases of logical
aggregation operator.
2. THE MCDONALD'S DIRECTIONAL POLICY MATRIX (DPM)
Although the DPM, like other models of portfolio matrices, attempts to define an organization's
strategic position and strategy alternatives, this objective can't be met without considering what is
meant by the term
„organization. The accepted level at which an organization can be analysed using the DPM is that

of the
„strategic business unit. The most common

What Is GEKF Algorithm For Tracking Moving Targets In A...
In this paper, we present a new method called NGEKF algorithm for tracking moving targets in a
wireless sensor network (WSN). Until now, several methods have been presented for target tracking.
These approaches face limitations that affect the efficient operation of WSN such as high energy
consumption, high implementation cost and low speed or accuracy (e.g. Extended Kalman Filter and
combination of Maximum Likelihood Estimation and Kalman Filter (KF+MLE)). Hence, other
literatures have proposed methods which consider the sensor scheduling problem as finding the
optimal sequence of the sensors to estimate the target position. These algorithms reduce the energy
consumption and increase the network lifetime (e.g. Mutual Information (MI) and ... Show more
Therefore, some approaches have been designed to estimate the position of the nodes [1, 2].
In most tracking methods, Kalman Filter (KF) and its extensions such as Extended Kalman Filter
(EKF), Unscented Kalman Filter (UKF) and the particle filter are used. These algorithms assume
that the motion of a moving target can be described by a dynamic model. There are many data
collection methods that the position of nodes can be estimated using them. Some of these methods,
use the distance between nodes in the measurement model. Signals between the transmitter and
receiver are always contaminated with noises. In the most cases, it is assumed that the measurement
noise is an additive and Gaussian noise. This assumption is not always true. Measurement signals
corrupted by multiplicative noise are presented in some systems such as discrete–time linear
systems [3], control systems [4], communication systems [5] and tracking systems [6]. A crucial
point is that the measurement error increases as a function of distance between sensor and the target.
As the result, applying the additive noise model leads to smaller tracking accuracy. Thereupon,
multiplicative noise model must be used instead of the additive model.
In some literature, the multiplicative noise has been used. Spinello and Stilwell [7] have presented a
recursive algorithm using the Maximum Likelihood Estimation method coupled with Gauss–
Newton algorithm in which a statedependent

Compare Poisson And Negative Binomial Regression
The ultimate goal of this study was to compare Poisson and Negative binomial regression models
using road accident (count) data to assess which of them significantly fit count data. The data for
this study were obtained from the Building and Road Research Institute of the Council for Scientific
and Industrial Research (CSIR) on the number of people killed by road accidents in Ghana,
including days that those accidents occurred within the period from 2001–2010.The maximum
likelihood estimation was employed to determine the parameter estimates for each model with R
statistical package. The results showed that the negative binomial regression model best fits road
accidents' data significantly as compared with the poison regression model. The results also revealed
that the day an accident occurred within the week significantly affected the expected number of
people killed in that accident. It was identified that Saturday significantly had the highest number of
people killed in road accidents in Ghana.
Keywords: maximum likelihood estimation, negative binomial regression, parameter estimate,
Poisson regression.
1.0 Introduction
Poisson and Negative Binomial regression analysis are techniques used to model dependent ... Show
Afukaar et al. (2007) and Ackaah and Salifu (2011) applied Poisson, Negative Binomial and Log–
Linear regression models to road accident data in Ghana. Oppong and Asiedu–Addo (2014) used
Poisson regression to model the contribution of vehicular type to the death of road accidents
casualties in Ghana and observed overdispersion in the data. Negative Binomial regression model
was then used as an approximation to the Poisson regression model which catered for the extra
Poisson parameter (Oppong Asiedu–Addo,

A Paradigm For Multiple Input Multiple Output ( Mimo )...
Abstract– A paradigm for multiple–input multiple–output (MIMO) channel modeling demands
diversity technique to compensate the effects of fading and shadowing. In this paper, error
performance of MIMO system is analyzed with orthogonal space time block code (OSTBC) and
maximal ratio combining (MRC) techniques over Weibull–gamma (WG) fading channel. WG
distribution forms a composite channel model which is used to determine the effects of multipath as
well as shadowing. Closed form expressions for symbol error rate (SER) are computed for MIMO
systems using OSTBC and MRC in this scenario. Consequently, the effects of fading severity by
varying shape parameters are also shown by simulation and analytical results. Keywords– Multiple–
input multiple–output (MIMO), orthogonal space time block code (OSTBC), maximal ratio
combining (MRC), Weibull–gamma (WG) fading, symbol error rate (SER). Introduction In the
present wireless systems, the demand of proliferation of bandwidth for high data rate and reliable
communication requirement is increasing. Multiple–input multiple–output (MIMO) systems are
investigated to achieve these requirements. Also, diversity techniques are recommended to increase
the reliability of system. Orthogonal space time block codes (OSTBCs) are employed in MIMO
systems to achieve the full transmit diversity while allowing a simple maximum likelihood decoding
algorithm. This algorithm is based on linear processing of received signals [1–2]. MIMO system
uses

The Structural Analysis Of Extreme Learning Machine ( ELM )
Extreme Learning Machine (ELM)
Extreme Learning Machine is a feedforward neural network for the regression, sparse
approximation, feature learning, compression, clustering and for classification with a single or multi
layers of hidden nodes in which the parameters are randomly generated and they are need not be
changed. The hidden nodes are assigned randomly and are never updated. But they can be inherited
from their ancestors. In many cases the output weights of hidden nodes are generally learned in a
single layer which is essential for learning a linear model.
First, the ELM was proposed for the single hidden layer feedforward neural network (SLFN), which
was then changed to single hidden layer feedforward network, since the hidden nodes ... Show more
An important step in ELM is to ﬁnd the output weights . It is solved by reducing the training error
and also the rule of the output weights. If the norms of weights and training error are smaller, then
the generalization performance of SLFNs tends to get better.
The main function can be termed as .
To solve the above problem, smallest norm least square method is used. where, is the Moore–
Penrose generalized inverse of matrix Q.
Several methods are there to calculate such as orthogonalization method, orthogonal projection
method, Singular Value Decomposition (SVD) method and the iterative method.
The orthogonal projection approach can be utilized efficiently in two cases. One is when is
nonsingular and the other is when is nonsingular. On the basis of Ridge Regression Theory, the
generalization function and the stability of SLFN can be enhanced by adding a positive value to the
diagonal of or .Using this method can be computed as follows, when is nonsingular, when is
nonsingular,
Galactic Swarm Optimization Algorithm
The original PSO algorithm was developed by Kennedy and Eberhart. It was encouraged by
swarming like schooling behavior in fish and flocking behavior in birds. Both the swarms do not
process any global optimization but they provide a technique for confusing predators and predator

Measurement, Definition, And Effect Decomposition For...
Methods Notation, definition, and effect decomposition for dichotomous outcome Let A denote the
exposure, Y a dichotomous outcome, M1 the first mediator, M2 the second mediator, and C a set of
baseline covariates. For example, A may denote body mass index (BMI), Y event of chronic heart
failure (CHF) at by the end of follow up, M1 cholesterol level, and M2 systolic blood pressure
(SBP). We compare two hypothetical levels of exposure: BMI = 25 and BMI = 21, which are
denoted as A =1 and A = 0, respectively. The causal relation among A, Y, M1, M2, and C is
illustrated graphically in Figure 1. There may be moreTheoretically, it allows more than two
mediators as well as time–varying mediator–outcome confounders which are affected by exposure,
such as the case shown in Figure 2. However, for simplicity, we assume that no time–varying
confounder exists and only two orderingordered mediators are of interest. The question of interest in
this paper may beis the extent of to which the effect of BMI (A) on event of CHF (Y) is mediated by
cholesterol level change (M1) and SBP (M2). The standard approach is to decompose the overall
effect of A on Y into four paths: the path not via M1 or M2, the path via M1 only, the path via M2
only, and path via M1 and followed by M2. Counterfactual outcome models are used to define four
paths based on causal theory 2–6, 16, 25. This model denotes the hypothetical outcome (in this
article it is also called counterfactual level of a certain

Correlation Between The Data, And The Fitted Values Essay
Abstract We use diagnostic method to find residual and influence in nonlinear regression for
repeated measurement data. The purpose of that to detect disparity between the data, and the fitted
values as well as disparity among a few data sets. Most of these Techniques based on graphical
representation of residuals, hat matrix and case deletion measures. After fitting a regression model,
it is important to regulate whether the entire requisite models supposition are reasonable before
performing inference. If there are any breaches, subsequent inferential procedures may be invalid
resulting in faulty conclusions. Therefore, it is crucial to perform appropriate model diagnostic.
The one–step approximation the estimates, generalized cook distance and likelihood distance are
considered. Cook and likelihood distance are two statistical diagnostics method. Models diagnostics
procedures imply both graphical and formal statistical tests. These procedures recognize us to
inspect whether the supposition of the regression model are justifiable and decide whether we can
belief subsequent inference outcome. We use these methods to explore the performance of residual
and influence in nonlinear regression model. These residuals can produce confusing results when
used in diagnostic method corresponding to those for linear regression. Simulation provide to

Relative Asbestos Effect Essay
In addition to the multiplicativity index, the Relative Asbestos Effect (RAE) was used to evaluate
the multiplicative interaction between smoking and asbestos. The RAE is the effect of smoking on
the asbestos effect expressed as the ratio of the risk ratio due to asbestos exposure in non–smokers
(RR01) to that in smokers (RR11). This measure is used to examine the heterogeneity of asbestos
effect across categories of smoking status, to determine if there is effect–measure modification. If
the asbestos effect is the same for non–smokers as for smokers, then the RAE is equal to one,
whereas a value greater than one indicates that the effect of asbestos is greater in non–smokers than
in smokers (negative multiplicative interaction), and vice versa (27). The equation of RAE is:
RAE=RR01/RR11 ... Show more content on Helpwriting.net ...
For the interaction term, an odds ratio (95% CI) which is significantly greater (or less) than one,
indicates a multiplicative interaction (29). The multiplicative interaction may also be evaluated with
the likelihood ratio test comparing logistic regression models (or cox regression) with or without the
interaction term (7,30). In epidemiologic studies, researchers examine the additive interaction or
multiplicative interaction only for empirical reasons; and usually use the one that shows a better fit
to the observations. In fact, statistical interactions are mostly evaluated as departure from
multiplicativity, due to the statistical models used in the analyses (e.g. logistic regression), and that
the models generate the multiplicative interactions results immediately. Usually, if authors are
interested in the evaluation of the statistical interaction, they should report results as departure from
additivity and

The Amazon Rainforest : The Lungs Of The Amazon
Flowing over the northern tip of South America is the world's second–biggest river, the Amazon,
whose waterway basin accounts for the majority part of the Amazon Rainforest, the world's biggest
tropical rainforest. The Amazon Rainforest, whose local name is Amazonas, and which is sometimes
referred to as the Lungs of the Planet since it creates more than 20 percent of the world's oxygen.
A fact backed by the United Nations environment program (UNEP). It is also the source of 20
percent of the planet's free–flowing fresh water
Sixty percent of the Amazon Rainforest is found in Brazil, and around 13 percent is found in Peru,
yet the rest is spread out in more than seven other South American nations, namely Suriname,
Colombia, Venezuela, French Guiana, Guyana, Ecuador, and Bolivia. The source of life for the
Amazon Rainforest, the Amazon River, traces its origin in the Andes Mountains of Peru and flows
eastbound over the South American mainland until the point that it enters the Atlantic Ocean in
Belem, Brazil.
To refer to the Amazon Rainforest as huge would be an understatement. The Amazon comprises 1.4
billion acres of land that make 54 percent out of all the remaining tropical rainforests on earth. In
fact, in a parallel world, if the Amazon were a nation, it would be the ninth biggest nation on earth.
As of June 2011, the Amazon's size and assorted diversity made it a contender for one of the New
Seven Wonders of the World by the Seven Wonders of the World Foundation.
In

System Performance Improvement For Ofdm System Over...
SER Performance Improvement in OFDM System over Generalized K–Fading Channel
Keerti Tiwari, Bindu Bharti and Davinder S. Saini
Department of Electronics and Communication Engineering
Jaypee University of Information Technology
Waknaghat, Solan (H.P.)–173234, India krt.tiwari@gmail.com, bindu.bharti457@gmail.com,
davinder.saini@juit.ac.in
Abstract– In this paper, performance metric of orthogonal frequency division multiplexing (OFDM)
system is analyzed over a composite fading channel i.e. generalized K– fading channel. Here,
OFDM system is considered which include repetition code to enhance the wireless link performance
with simplicity. Symbol error rate (SER) performance is evaluated using binary phase shift keying
(BPSK) and 16–qardature amplitude modulation (16–QAM) over generalized–K fading channel.
This channel model considers Nakagami–m distribution to define multipath and gamma distribution
to represent shadowing. Simulation results demonstrate that improved system performance can be
achieved using repetition code in severely faded environment. A comparative study of coded and
uncoded system is also given in this paper. Consequently, SER performance is improved with the
increase in shape parameters.
Keywords– Orthogonal frequency division multiplexing (OFDM), Generalized K–fading, binary
phase shift keying (BPSK), 16–qardature amplitude modulation (16–QAM), symbol error rate
(SER). Introduction
Next generation wireless technologies have demanded efficient and

A Report On A Cox Model Essay
A Cox model is a well–recognized statistical technique for exploring the relationship between the
survival of a patient and several explanatory variables. A Cox model provides an estimate of the
treatment effect on survival after adjustment for other explanatory variables. It allows us to estimate
the hazard (or risk) of death, or other event of interest, for individuals, given their prognostic
variables. Interpreting a Cox model involves examining the coefficients for each explanatory
variable. A positive regression coefficient for an explanatory variable means that the hazard for
patient having a high positive value on that particular variable is high. Conversely, a negative
regression coefficient implies a better prognosis for patients with higher values of that variable.
Cox's method does not assume any particular distribution for the survival times, but it rather
assumes that the effects of the different variables on survival are constant over time and are additive
in a particular scale [17]. The hazard function is the probability that an individual will experience an
event (for example, death) within a small time interval, given that the individual has survived up to
the beginning of the interval. In this model the unique effect of a per–unit increase in a variable or
covariate is assumed to be multiplicative with respect to the hazard rate [18]. For example, taking a
drug may halve one 's hazard rate for a stroke occurring, or, changing the material from which a

Safe Patient Handling
Student's Name
Professor's Name
Course
Date
Safe Patient Handling Program
Summary
Effects of a National Safe Patient Handling Program on Nursing Injury Incidence Rates by Gail
Powell–Cope, Peter Toyinbo, Nitin Patel, Deborah Rugs, Christine Elnitsky, Bridget Hahm, Bryce
Sutton, Robert Campbell, Karen Besterman–Dahan, Mary Matz, Michael Hodgson and published in
2014 discusses the musculoskeletal injury( MSI) among the primary healthcare providers in the
veteran health administration facilities. The research shows that the rate of the MSI is quite high and
this overall impacts the efficiency of the nurses. The article suggests that failure to educate the peer
leaders on the appropriate safety patience handling programs, inadequate equipment, and staffing
contributes to MSI (Powell–Cope et al.).
The researchers had a three–year study between 2008 and 2011 where they gathered data from
coordinators in from the previous years on the rate and the incidence of the injuries in the hospital to
evaluate whether there was any difference before and after the program implementation (Powell–
Cope et al.). Indeed, the study showed that the program helped to reduce injuries among the
caregivers. This paper proposed that health directors implement peer leadership training on the safe
patient handling program (SPH) and the use of specialized handling equipment (Powell–Cope et
al.). Further, there is a need to incorporate SPH training in the orientation of new workers and
assessing the healthcare providers on their ... Show more content on Helpwriting.net ...
Effects Of A National Safe Patient Handling Program On Nursing Injury Incidence Rates. JONA:
The Journal Of Nursing Administration, vol 44, no. 10, 2014, pp. 525–534. Ovid Technologies
(Wolters Kluwer Health),

Few Animal Studies Have Proved That Gabapentin Has A...
Few animal studies have proved that gabapentin has a potential to activate a serotonin receptor
(5HT3) at the spinal level and also attenuate the function of microglial cells[6]. In some parts of the
brain such as periaqueductal grey (PAG) and anterior cingulated cortex, gabapentin has been shown
to elevate the level of GABA, a major inhibitory neurotransmitter, which might serve as an
explanation of its' efficacy in partial management of seizure[14]. Although gabapentin is approved
to be used as an add–on treatment of focal epilepsies in 6 years and older patients and as
monotherapy in patients older than 12 years of age, it seems to show no efficacy when used in a
management of generalized tonic–clonic seizures, generalized absence ... Show more content on
Helpwriting.net ...
Due to an effect of gabapentin at the level of hypothalamus to regulate the temperature, it can also
be used as an effective non–hormonal therapy for hot flashes, a bothersome problem of menopause.
It is shown to be more efficacy if used in patients with hot flashes that associated with sleep
interference [17]. Study shows that a bioavailability of gabapentin is low and it is dose–dependent.
The bioavailability of 300 mg is around 60% and decreasing to less than 30% if the dosage is 1600
mg 3 times a day [4; 11]. It has low protein binding property and it is eliminated unchanged in the
urine, which means it will not change into toxic metabolite or intermediate that can be harmful to
the body. Gabapentin has a short half life of 5 to 9 hours, but with renal impairment, it will
increase[4]. A dose adjustment is required in patient who has creatinine clearance of 60 ml/min and
in the elderly because of reduced renal function that has been thought to be decreased around 1%
per year after the age of 40[4; 16]. A number needed to treat (NNT) of gabapentin is 6.3 and its
number needed to harm (NNH) is 25.6, therefore it is considered a safe drug [6]. The ceiling effect
has been reported to be 100 mg/kg in one study and 30–300 mg/kg in another study following oral
administration [13]. The pharmacokinetic of absorption of gabapentin is not linear unlike other
newer anti–seizure medications. The explanation for this event is because gabapentin absorption
depends on

The Regression Model Should Not Only The Independent...
In order to maintain the reliability and the integrity of the research, the regression model should
include not only the independent variables that were chosen based on their characteristics, but also
the possible impacts from other sources and the unexplained variation. The part that simply cannot
be explained is called stochastic error term. Serial correlation is a violation of Assumption IV, the
uncorrelated observations of the error term. When serial correlation occurs, it means the independent
variable has correlation with the error term. It occurs the most in time–series data because ...Serial
correlation occurs when the error term from one time period depends in a systematic way on the
error term from a different time period ... Show more content on Helpwriting.net ...
In this model, since there are only 9 observations and 4 independent variables, the critical values of
dl and du when N=15 was used from the appendix. The dl = 0.69 and du = 1.97. The Durbin–
Watson statistic of this model is 1.42, which places in within the interval of [0.69, 1.97]. This means
the result is inconclusive; we can neither reject the null hypothesis nor accept it. Such result could
be caused by the variables and other factors that are not explained by the chosen independent
variables. Other than the current result of the DW test, positive serial correlation is still a major
possible outcome of time series data. Positive serial correlation indicates that the positive errors for
one observation increase the probability of a positive error for another observation, and vice versa.
In order to remedy serial correlation, GLS is introduced. Generalized least squares (GLS) is a
method of ridding an equation of pure first–order serial correlation and in the process restoring the
minimum variance property to its estimation (Studenmund, 2006). In this model, GLS did not
necessarily run because of the inconclusive result of the DW test, so that the presence of serial
correlation is unsure. Classical Assumptions of OLS Following are the seven classical assumptions
of OLS that must be held in order for a regression model to be a successful unbiased estimator. 1.
The regression model is linear, is

A Report On A Cox Model
A Cox model is a statistical method used for exploring the relationship between the survival of a
patient and several risk variables. A Cox model provides an estimate of the therapeutic procedure
effect on survival after adjustment for other explanatory variables. It allows to estimate the risk of
mortality, or other events of interest, for patients, given their prognostic variables. Cox model
analysis involves examining the coefficients for each variable. A positive regression coefficient for
an explanatory variable means that the hazard for patient having a high positive value on that
particular variable is high. Conversely, a negative regression coefficient implies a better prognosis
for patients with higher negative values of that variable. Cox's method does not assume a
distribution for the survival times, but it rather assumes that the effects of the different variables on
survival are constant over time and are additive at some level or scale [17]. The hazard function is
the probability that an individual will experience an event (like mortality) within some time interval,
given that the individual has survived up to the beginning of the interval. In this model the unique
effect of a per–unit increase in a variable is assumed to be multiplicative with respect to the hazard
rate [18]. For example, following a certain therapeutic procedure may reduce one 's hazard rate for
mortality by one half. Thus in order to convert this multiplicative problem to additive we tend

Generalized Anxiety Disorder ( Gad ) Essay
Literature Review
Generalized Anxiety Disorder
Generalized anxiety disorder (GAD) is a disorder in which an individual may feel persistent,
excessive, and worry about everyday things that may not even happen. Individuals with this disorder
may feel worry, excessive anxiety, and have thoughts of the worst even when there is no need for
concern. A person experiencing GAD may expect a disaster. They may worry about their finances,
money, health, family, work, or any issue that may come to mind. This disorder may be present
when a person worrying increases on more days than one for at least six months. GAD can interfere
with work, school, family, and even social activities. GAD can be diagnosed in adults when they
experience at least three of the symptoms. These symptoms include restlessness or feeling on the
edge, fatigue, difficulty focusing or mind going blank, irritability, muscle tension, pain in back or
headaches, and sleep disturbance (ADAA, n.d.).
According to the Mayo Clinic, genetics may play a role as well as other factors, but is not fully
known. Some of the risk factors for GAD is personality, genetics, and sex. With personality, a
person who is shy, have negative thoughts, or who avoids dangerous situations may be more prone
to generalized anxiety disorder than others are. GAD may run in the family, thus being a genetic
factor. Also, women are more prone to have GAD than men. The common two treatments for GAD
include medication and psychotherapy. Psychotherapy

Types Of Treatment For Anxiety Disorders
Introduction Anxiety disorders are distressing, and impairing conditions, associated with significant
social costs (Palazzo, Altamura, Stein, Baldwin, 2014). There are many different types of
treatment for anxiety disorders. Some are more effective than others. The studies within this paper
will further tell us about anxiety disorder, different types of treatments, and treatment effectiveness.
The Purpose of the Studies The purpose of the study by Palazzo, Altamura, Stein, and Baldwin
(2014) was to find published literature on health literacy about psychotropic medications. The study
also includes some difference between public beliefs and clinicians' opinions. It is said that anxiety
symptoms and disorders often lead to the development of other mental and physical disorders. It was
proved that mental literacy is effective in encouraging a help seeking attitude. Unfortunately little is
known about how to enhance knowledge about psychotropic medications. Depression and an
anxiety disorder in young patients and in clinicians' opinions showed that there are difference
between public beliefs and clinicians' opinions. Norton, Abbott, Norberg, and Hunt (2015) studied
mindfulness and acceptance based treatments for social anxiety disorders. The advancement of
mindfulness and acceptance has been associated with psychological supplementary wellbeing.
Individuals avoid or endure situations with intense anxiety, which leads to impairment in life
functioning.

Benefits Of Marjoram
Marjoram (Origanum majorana) is an aromatic herb in the mint family which originated in Egypt
and Arabia. It is also widely referred to as Oregano. Marjoram was initially used by Hippocrates as
an antiseptic agent. To the ancient Greeks, it was names as 'Amarakos', a symbol of love, honour
and happiness. Aristotle reported it as anti–poison. In the old Egypt, Marjoram was used to disinfect
and preserve food and its oil was messaged on the forehead and in the hair. Traditionally, the leaves
of marjoram are employed to cure diabetes, insomnia, catarrh, asthma and nervousness.18 Today, it
is commonly found in the Mediterranean region or grown in gardens around the world. In its varied
forms of: marjoram essential oil, fresh or dried marjoram leaves, ... Show more content on
Helpwriting.net ...
The extract exhibited a marked effects in DPPH (1, 1–diphenyl–2–picrylhydrazyl) scavenging assay.
27The ethanol extracts of both stem and root has shown in–vitro antioxidant activity, respectively
using Spectrophotometric method by DPPH, H2O2 free radical scavenging, metal chelating and
ferric ion reducing power assay. Both the extracts showed potent antioxidant activity in all models.
The IC50 values were found comparable with ascorbic acid and the reducing ability of root ethanol
extract.25 The ethyl–alcohol, n–hexane and aqueous extracts obtained from leaves and flowering
tops of two marjoram Hungary and Egypt showed antioxidant activity in vitro by
Spectrophotometric and Chemilaminometric method methods using DPPH and Rancimat methods.

The Changing Price Elasticity of Demand for Domestic...
The Changing Price Elasticity of Demand for Domestic Airline Travel
Consumers make economic decisions as to what they buy based largely on price. More specifically,
the change in the amount of a good purchased is often highly dependent on its change in price. That
measure of responsiveness is defined as the price elasticity of demand.
Mathematically, it is often expressed as: Ed
= – percent change in quantity demanded / percent change in price, or –(dQ/Q)/(dP/P). The minus
sign is often omitted because price elasticity of demand is presumed to be negative. If Ed = 0, it is
perfectly inelastic, a change in price does not affect the quantity demanded. If 0 Ed
–1, it is relatively inelastic, the quantity demanded does
not ... Show more content on Helpwriting.net ...
Multiplicative: Y= (X)a
(X1)b
(X2)c
, in which each independent variable interacts with other independent variables.
The bulk of aviation demand models have been of the multiplicative form to utilize that interaction.
Fortunately, the multiplicative form can be readily converted to a linear form by simply taking the
logarithms of all variables. One difficulty with both model types if using actual data is the effect of
the numerical value (size) of the variables themselves. Different scalar size in the variables tends to
mask the effect of which independent variable has a greater effect on the dependent variable. While
one correction to scalar effects may be to use what is known as standardized or beta coefficients,1
the models developed below will be based on the percentage change in the variables from one year
to the next, rather than the level of the variable.
In this manner the scalar differences are also eliminated. In Part D, Results and Conclusions, the
development of the model form is shown in steps, using actual data. 3
Models may also be developed with or without a constant (trend) factor. In a model without a
developed constant, the trend is subsumed in the coefficients of the remaining independent
variables, and may bias those coefficients. All equations in this paper use a constant term.
Part C. The

Nature Vs Nurture : Is The Nature Or Nurture?
AoS 3: Student Directed Research Investigation Unit 1 Psychology – Megan Rodrigues
RESEARCH QUESTION How is the nature vs nurture debate related to a consideration of the
mental disorder, schizophrenia? INTRODUCTION Schizophrenia is categorized by thoughts or
experiences that seem abnormal with reality, disorganized speech or behaviour and decreased
participation in regular daily activities. Difficulty with memory and concentration are sometimes
also present. The two hit hypothesis generally refers to a genetic vulnerability, which is known as
the first hit, triggered by something in the environment, which is known as the second hit The first
hit is proposed to involve disruption of some sort of brain mechanism that is susceptible to ... Show
Aim: The aim of this experiment was to explore the synergistic effects of heritability and
environment in the cases of two brothers with schizophrenia. Procedure: The procedure was a case
study, and the researcher interviewed two brothers, which are both diagnosed with the mental
disorder, schizophrenia. While being interviewed, they spoke about their past experiences during
their childhood, and how their mother had the carrier gene, which one twin inherited. Conclusions /
Results: Conclusions suggest that the nature vs nurture dichotomy may not be as relevant as looking
at the interaction between these two forces. It was discovered that while one's genetic heritage
creates a predisposition towards schizophrenia, other factors such as the home environment, the
parental environment, dietary factors and others may determine whether the disease is manifested.
Source 2: Schizophrenia as a complex trait Sullivan, P.F, Kendler, K.S, Neale, M.C. (2003)
Schizophrenia as a complex trait. Arch Gen Psychiatry, 60, 1187–1192. Aim: To calculate meta–
analytic estimates of heritability in liability and shared an individual – specific environmental effects
from the pooled twin data. Procedure: To identify all relevant primary studies, computerized
PubMed searches for an inclusive list of descriptors were performed and searched the reference lists
of prior reviews of schizophrenia to identify any reports not retrieved in the PubMed search. 14
published

Causes And Effects Of Historical Trauma In Native American...
Understanding the causes and effects of historical trauma is imperative to truly comprehend the
current state of afflicted communities today. As historical trauma influences multiple generations,
the impact of adverse childhood experiences (ACEs) on the health of Native American populations
is an important issue to consider and can possibly be viewed as an indication of historical trauma.
ACEs are traumatic events that occur during childhood, such as abuse and neglect, and are known to
have severe implications throughout an individual's lifetime. The following review of literature
explores impacts of historical trauma, the prevalence of ACEs in indigenous communities,
interventions for healing, and future improvements in the field. Historical trauma is a concept that
refers to the wounding of generations due to traumatic experiences such as boarding schools, forced
displacement, and genocide. Responses to this distress manifest in a number of social issues. For
example, alcoholism and substance abuse could be recognized as attempts to numb unresolved grief.
Other manifestations of emotional responses to this trauma include abuse, depression, domestic
violence, and suicide. A framework for understanding the effects of historical trauma on
communities is provided by Evans–Campbell (2008) in her article, Historical Trauma in American
Indian and Native American Communities. These three levels include individual–level impacts,
family–level impacts, and community–level impacts.

Models From Simple Random And Complex Survey Designs
Models (GLM) to data from simple random and complex survey designs. This program supports a
range of sampling distributions including Gaussian, inverse Gaussian, multinomial, binomial,
negative binomial, Bernoulli, Poisson, and gamma. The last program, MAPGLIM can be used to fit
GLM models to the multilevel data. Each of these programs can function as stand–alone program.
To estimate a model with missing data, LISREL by default uses the full information maximum
likelihood (FIML) approach. However, users may also opt to impute missing values using either
expectation maximization or Markov Chain Monte Carlo algorithms. Beginning with version 9.10,
LISREL will automatically provide robust estimation of standard errors and chi–square statics if a
raw file is used as a data input. The default estimation method in LISREL is Maximum Likelihood
(ML) even if an estimated asymptotic covariance matrix is provided, but the users may override the
default when setting up the model.
Together, the LISREL 9.2 package makes possible estimations of a wide range of statistical used in
educational research, such as exploratory– and confirmatory factor analysis (EFA and CFA) with
continuous and ordinal variables, multiple–group analysis, multilevel linear and nonlinear models,
latent growth curve models, and generalized linear models (GLM) to complex survey data and
simple random sample data (Byrne 2012; Sörbom 2001).
LISREL interface
The data analysis workflow in LISREL involves three most

Domestic Violence Social Work
Problem Of Domestic Violence Is Too Weighty Social
Work Essay ukessays.com /essays/social–work/problem–of–domestic–violence–is–too–weighty–
social–workessay.php
The problem of domestic violence is too weighty, both as public health and social issues, to be
content with intervention approaches that sound good or look right based on some conceptual
model, but that have no empirical support for their efficacy (Gorney, 2007). Unfortunately, this has
been the tradition regarding interventions in this field–many earnest appeals and opinions, very little
data (Ganley, 2008).
It is important in conceptualizing interventions for partner violence to distinguish between
interventions that are inefficacious and interventions that are harmful. ... Show more content on
Helpwriting.net ...
The available data suggest that there is a severity continuum of partner violence, not necessarily
discrete categories. Those on the high end of the continuum tend to have many complicating issues,
including severe and frequent partner violence perpetration, antisocial personality characteristics,
generalized violence, and affective instability (Hassan, et al 2000). Not surprisingly, individuals
with these characteristics have higher violence recidivism after batterer counseling, when compared
to less severe cases (McLellan, 2003). Although it seems quite sensible to steer such severe cases
away from couple's interventions, there is no compelling reason to believe that they will respond
more favorably to gender–specific interventions. As yet, there is no empirical basis upon which to
recommend treatment matching for various forms of substance abuse treatment based on violence
frequency or severity.
It is a popular misconception that intervention programs for domestic violence perpetrators
exclusively handle severe cases. Even among those who are court–mandated to counseling, there is
a wide range of case severity that can impact treatment outcome (Murphy et al., 2000). Some
referrals have engaged exclusively in verbal abuse, phone harassment, or other

Distribution Of The Risk Burden Essay
1. Introduction:
Equitable distribution of the risk burden must be structured using advanced statistical methods to
divide the portfolio into homogenous classes. thus, each insured belongs to a particular class can pay
the pure premium Proportional to the risk degree of this class.
Over the last decade, generalized linear model (GLM) was a common statistical tool for a prior
classification see; e.g. Dionne and Vanasse (1989), Haberman and Renshaw (1996),
Pinquet (1999), Bermúdez et al. (2001) and Boucher and Denuit
(2006). The merits of this model are twofold. Firstly , the random deviations from the mean may
have a distribution not normal (kaas et al. 2008). Secondly, the transformed mean of dependent
variable may be a linear function of the explanatory variables which determined by the link
function.
However, this model have two drawbacks; firstly, It consider the random variables is independent
and that may be not fulfilled in case of longitudinal, repeated measurements and spatial data.
Secondly, the model is not convenient for unknown nonlinear effect of independent variables
because the GLM models consider the independent variables have linear effect . The first shortage
can be covered by GLMM models also this models used to superimpose credibility on a GLM
setting see; e.g. Klinker (2011) and Antonio (2007). The second shortage can be covered by GAM
models that permit us to overcome the linearity assumptions inherent to GLMs.
The spatial models give us

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