Austin Statistics is an open access, peer reviewed, scholarly journal dedicated to publish articles in all areas of statistics.
The aim of the journal is to provide a forum for scientists, academicians and researchers to find most recent advances in the field statistics.
Austin Statistics accepts original research articles, review articles, case reports and rapid communication on all the aspects of statistics.
Dispensing processes and the tools used have a profound influence on estimates of compound activity. Researchers have shown that leachates from plastic labware can profoundly affect biological assays. Data derived using disposable tip-based serial dilution and dispensing have shown a reduction in inhibition compared to acoustic dispensing with some compounds appearing hundreds of times more active with the acoustic process. Furthermore, there was no correlation of compound activity between the two processes. Studies of high-throughput screening (HTS) present confounding results that may influence scientific judgment and promote faulty decisions. Some researchers showed that differences in biological activity could vary by three or more orders of magnitude. What we address is how these errors may affect computational models and data manifested in external databases. We show that dispensing processes impact computational and statistical results.
Experimental design and statistical power in swine experimentation: A reviewKareem Damilola
A review on experimental design and statistical power in swine experimentation. This review helps in gaining more insights into animal experimentation(s).
Austin Statistics is an open access, peer reviewed, scholarly journal dedicated to publish articles in all areas of statistics.
The aim of the journal is to provide a forum for scientists, academicians and researchers to find most recent advances in the field statistics.
Austin Statistics accepts original research articles, review articles, case reports and rapid communication on all the aspects of statistics.
Dispensing processes and the tools used have a profound influence on estimates of compound activity. Researchers have shown that leachates from plastic labware can profoundly affect biological assays. Data derived using disposable tip-based serial dilution and dispensing have shown a reduction in inhibition compared to acoustic dispensing with some compounds appearing hundreds of times more active with the acoustic process. Furthermore, there was no correlation of compound activity between the two processes. Studies of high-throughput screening (HTS) present confounding results that may influence scientific judgment and promote faulty decisions. Some researchers showed that differences in biological activity could vary by three or more orders of magnitude. What we address is how these errors may affect computational models and data manifested in external databases. We show that dispensing processes impact computational and statistical results.
Experimental design and statistical power in swine experimentation: A reviewKareem Damilola
A review on experimental design and statistical power in swine experimentation. This review helps in gaining more insights into animal experimentation(s).
COMPARISON OF THE RATIO ESTIMATE TO THE LOCAL LINEAR POLYNOMIAL ESTIMATE OF F...IJESM JOURNAL
In this paper, attempt to study effects of extreme observations on two estimators of finite
population total theoretically and by simulation is made. We compare the ratio estimate with the
local linear polynomial estimate of finite population total given different finite populations. Both
classical and the non parametric estimator based on the local linear polynomial produce good
results when the auxiliary and the study variables are highly correlated. It is however noted that
in the presence of outlying observations the local linear polynomial performs better with respect
to design mean square error (MSE) in all the artificial populations generated.
Effect of 3D parameters on Antifungal Activities of Some Heterocyclic CompoundsIOSR Journals
Quantitative Structure Activity Relationships (QSAR) of some heterocyclic compounds was studied using some 3D parameters. The QSAR models indicated that Dipole Y, Dipole mag., Y length and some indicator parameters are very effective in describing the antifungal activities of these compounds against Candida albicans in the training and external test set. The multiple regression analysis have produced well predictive statistically significant and cross validated QSAR models which help to explore some expectedly potent compounds.
Classification accuracy analyses using Shannon’s EntropyIJERA Editor
There are many methods for determining the Classification Accuracy. In this paper significance of Entropy of
training signatures in Classification has been shown. Entropy of training signatures of the raw digital image
represents the heterogeneity of the brightness values of the pixels in different bands. This implies that an image
comprising a homogeneous lu/lc category will be associated with nearly the same reflectance values that would
result in the occurrence of a very low entropy value. On the other hand an image characterized by the
occurrence of diverse lu/lc categories will consist of largely differing reflectance values due to which the
entropy of such image would be relatively high. This concept leads to analyses of classification accuracy.
Although Entropy has been used many times in RS and GIS but its use in determination of classification
accuracy is new approach.
Hellinger Optimal Criterion and 퓗푷푨- Optimum Designs for Model Discrimination...inventionjournals
Kullback-Leibler (KL) optimality criterion has been considered in the literature for model discrimination. However, Hellinger distance has many advantages rather than KL-distance. For that reason, in this paper a new criterion based on the Hellinger distance named by Hellinger (ℋ) -optimality criterion is proposed to discriminate between two rival models. An equivalence theorem is proved for this criterion. Furthermore, a new compound criterion is constructed that possess both discrimination and a high probability of desired outcome properties. Discrimination between binary and Logistic GLM are suggested based on the new criteria
DA entrance exam is one of the highly anticipated and aspired examinations in India which offers the aspirants a large number of government job opportunities.
Competiton gurukul Coaching for NDA recruitment . Competition gurukul institute is the best coaching center for NDA in delhi India. NDA carry out selection and enrolment of Army , Navy, Air Force Officers . The National Defence Academy (NDA) admits students to the Army, Navy and Air Force wings through an entrance examination held twice a year, generally in the months of April and September. This examination is conducted by the Union Public Service Commission
Competition gurukul is a fine and promising institute for NDA coaching and our selection 75%. It provides all necessary resources of coaching for cracking NDA exam with marvelous ranking. The quality of coaching that competition gurukul provides is unique in various ways:
The syllabus is covered in specified duration with larger focus on concept development, knowledge building, through trick fusion frequent practice of formulas, facts and figures.
Wisely revised and highly graded study material.
Interactive, practical and sound approach conducted in classroom by highly qualified knowledge and dynamic professional teachers and experts.
Regular test and assessment as well as marks record keeping and maintenance system.
Time to time notification of various declared exams and guidance to farm filling.
Development of a Spatial Path-Analysis Method for Spatial Data AnalysisIJECEIAES
Path analysis is a method for identifying and analyzing direct and indirect relationship be- tween independent and dependent variables. This method was developed by Sewal Wright and initially only used correlation analysis results in identifying the variables’ relationship. So far, path analysis has been mostly used to deal with variables of non-spatial data type. When analyzing variables that have elements of spatial dependency, path analysis could result in a less precise model. Therefore, it is necessary to build a path analysis model that is able to identify and take into account the effects of spatial dependencies. Spatial autocorrelation and spatial regression methods can be used to enhance path analysis to identify the effects of spatial dependencies. This paper proposes a method derived from path analysis that can process data with spatial elements and furthermore can be used to identify and analyze the spatial effects on the data; we call this method spatial path analysis.
Statistical modelling is of prime importance in each and every sphere of data analysis. This paper reviews the justification of fitting linear model to the collected data. Inappropriateness of the fitted model may be due two reasons 1.wrong choice of the analytical form, 2. Suffers from the adverse effects of outliers and/or influential observations. The aim is to identify outliers using the deletion technique. In I extend the result of deletion diagnostics to the ex- changeable model and reviews some results of model analytical form checking and the technique illustrated through an example.
2017 - Plausible Bioindicators of Biological Nitrogen Removal Process in WWTPsWALEBUBLÉ
Reference:
Zornoza, A., Alonso, J.L. and Serrano, S. (2017) Plausible Bioindicators of Biological Nitrogen Removal Process in WWTPs. In: Abstracts of the 7th congress of European microbiologists FEMS 2017, Valencia, Spain, 9-13 July 2017.
COMPARISON OF THE RATIO ESTIMATE TO THE LOCAL LINEAR POLYNOMIAL ESTIMATE OF F...IJESM JOURNAL
In this paper, attempt to study effects of extreme observations on two estimators of finite
population total theoretically and by simulation is made. We compare the ratio estimate with the
local linear polynomial estimate of finite population total given different finite populations. Both
classical and the non parametric estimator based on the local linear polynomial produce good
results when the auxiliary and the study variables are highly correlated. It is however noted that
in the presence of outlying observations the local linear polynomial performs better with respect
to design mean square error (MSE) in all the artificial populations generated.
Effect of 3D parameters on Antifungal Activities of Some Heterocyclic CompoundsIOSR Journals
Quantitative Structure Activity Relationships (QSAR) of some heterocyclic compounds was studied using some 3D parameters. The QSAR models indicated that Dipole Y, Dipole mag., Y length and some indicator parameters are very effective in describing the antifungal activities of these compounds against Candida albicans in the training and external test set. The multiple regression analysis have produced well predictive statistically significant and cross validated QSAR models which help to explore some expectedly potent compounds.
Classification accuracy analyses using Shannon’s EntropyIJERA Editor
There are many methods for determining the Classification Accuracy. In this paper significance of Entropy of
training signatures in Classification has been shown. Entropy of training signatures of the raw digital image
represents the heterogeneity of the brightness values of the pixels in different bands. This implies that an image
comprising a homogeneous lu/lc category will be associated with nearly the same reflectance values that would
result in the occurrence of a very low entropy value. On the other hand an image characterized by the
occurrence of diverse lu/lc categories will consist of largely differing reflectance values due to which the
entropy of such image would be relatively high. This concept leads to analyses of classification accuracy.
Although Entropy has been used many times in RS and GIS but its use in determination of classification
accuracy is new approach.
Hellinger Optimal Criterion and 퓗푷푨- Optimum Designs for Model Discrimination...inventionjournals
Kullback-Leibler (KL) optimality criterion has been considered in the literature for model discrimination. However, Hellinger distance has many advantages rather than KL-distance. For that reason, in this paper a new criterion based on the Hellinger distance named by Hellinger (ℋ) -optimality criterion is proposed to discriminate between two rival models. An equivalence theorem is proved for this criterion. Furthermore, a new compound criterion is constructed that possess both discrimination and a high probability of desired outcome properties. Discrimination between binary and Logistic GLM are suggested based on the new criteria
DA entrance exam is one of the highly anticipated and aspired examinations in India which offers the aspirants a large number of government job opportunities.
Competiton gurukul Coaching for NDA recruitment . Competition gurukul institute is the best coaching center for NDA in delhi India. NDA carry out selection and enrolment of Army , Navy, Air Force Officers . The National Defence Academy (NDA) admits students to the Army, Navy and Air Force wings through an entrance examination held twice a year, generally in the months of April and September. This examination is conducted by the Union Public Service Commission
Competition gurukul is a fine and promising institute for NDA coaching and our selection 75%. It provides all necessary resources of coaching for cracking NDA exam with marvelous ranking. The quality of coaching that competition gurukul provides is unique in various ways:
The syllabus is covered in specified duration with larger focus on concept development, knowledge building, through trick fusion frequent practice of formulas, facts and figures.
Wisely revised and highly graded study material.
Interactive, practical and sound approach conducted in classroom by highly qualified knowledge and dynamic professional teachers and experts.
Regular test and assessment as well as marks record keeping and maintenance system.
Time to time notification of various declared exams and guidance to farm filling.
Development of a Spatial Path-Analysis Method for Spatial Data AnalysisIJECEIAES
Path analysis is a method for identifying and analyzing direct and indirect relationship be- tween independent and dependent variables. This method was developed by Sewal Wright and initially only used correlation analysis results in identifying the variables’ relationship. So far, path analysis has been mostly used to deal with variables of non-spatial data type. When analyzing variables that have elements of spatial dependency, path analysis could result in a less precise model. Therefore, it is necessary to build a path analysis model that is able to identify and take into account the effects of spatial dependencies. Spatial autocorrelation and spatial regression methods can be used to enhance path analysis to identify the effects of spatial dependencies. This paper proposes a method derived from path analysis that can process data with spatial elements and furthermore can be used to identify and analyze the spatial effects on the data; we call this method spatial path analysis.
Statistical modelling is of prime importance in each and every sphere of data analysis. This paper reviews the justification of fitting linear model to the collected data. Inappropriateness of the fitted model may be due two reasons 1.wrong choice of the analytical form, 2. Suffers from the adverse effects of outliers and/or influential observations. The aim is to identify outliers using the deletion technique. In I extend the result of deletion diagnostics to the ex- changeable model and reviews some results of model analytical form checking and the technique illustrated through an example.
2017 - Plausible Bioindicators of Biological Nitrogen Removal Process in WWTPsWALEBUBLÉ
Reference:
Zornoza, A., Alonso, J.L. and Serrano, S. (2017) Plausible Bioindicators of Biological Nitrogen Removal Process in WWTPs. In: Abstracts of the 7th congress of European microbiologists FEMS 2017, Valencia, Spain, 9-13 July 2017.
For Domestic Wastewater Treatment, Finding Optimum Conditions by Particle Swa...Agriculture Journal IJOEAR
Abstract— Performing jar test method is used for finding out optimum conditions (coagulant type, coagulant dose, pH etc.)for treatment of domestic wastewater before physicochemical process, or coagulation process. In this study, Response Surface Method (RSM) is applied to determine optimum combinations of coagulant dose and pH value in jar test. Alum, FeCl3 and FeSO4 are used as coagulant and compared with highest removal efficiency of their two responses which turbidity and chemical oxygen demand (COD).Finding equations from RSM are also evaluated with Particle Swarm Optimization (PSO) method by using Matlab Program. Alum and Ferric Chloridedose500 mg/lat pH7 found as optimum conditions for domestic wastewater treatment. COD removal for Alum and Ferric Chloride are 90% and 70%,respectively.In addition, Because of becoming low COD removal (maximum 50%) and ineffectively color removal, Ferric Sulfate coagulant found as inconvenient for treating domestic wastewater.
Application of Semiparametric Non-Linear Model on Panel Data with Very Small ...IOSRJM
-This research work investigated the behaviour of a new semiparametric non-linear (SPNL) model on
a set of panel data with very small time point (T = 1). The SPNL model incorporates the relationship between
individual independent variable and unobserved heterogeneity variable. Five different estimation techniques
namely; Least Square (LS), Generalized Method of Moments (GMM), Continuously Updating (CU), Empirical
Likelihood (EL) and Exponential Tilting (ET) Estimators were employed for the estimation; for the purpose of
modelling the metrical response variable non-linearly on a set of independent variables. The performances of
these estimators on the SPNL model were examined for different parameters in the model using the Least
Square Error (LSE), Mean Absolute Error (MAE) and Median Absolute Error (MedAE) criteria at the lowest
time point (T = 1). The results showed that the ET estimator which provided the least errors of estimation is
relatively more efficient for the proposed model than any of the other estimators considered. It is therefore
recommended that the ET estimator should be employed to estimate the SPNL model for panel data with very
small time point.
Episode 12 : Research Methodology ( Part 2 )
Approach to de-synthesizing data, informational, and/or factual elements to answer research questions
Method of putting together facts and figures
to solve research problem
Systematic process of utilizing data to address research questions
Breaking down research issues through utilizing controlled data and factual information
SAJJAD KHUDHUR ABBAS
Chemical Engineering , Al-Muthanna University, Iraq
Oil & Gas Safety and Health Professional – OSHACADEMY
Trainer of Trainers (TOT) - Canadian Center of Human
Development
Episode 18 : Research Methodology ( Part 8 )
Approach to de-synthesizing data, informational, and/or factual elements to answer research questions
Method of putting together facts and figures
to solve research problem
Systematic process of utilizing data to address research questions
Breaking down research issues through utilizing controlled data and factual information
SAJJAD KHUDHUR ABBAS
Chemical Engineering , Al-Muthanna University, Iraq
Oil & Gas Safety and Health Professional – OSHACADEMY
Trainer of Trainers (TOT) - Canadian Center of Human
Development
Computer model simulations are widely used in the investigation of complex hydrological systems. In particular, hydrological models are tools that help both to better understand hydrological processes and to predict extreme events such as floods and droughts. Usually, model parameters need to be estimated through calibration, in order to constrain model outputs to observed variables.
Relevant model parameters used for calibration are usually selected based on expert knowledge of the modeller or by using a local one-at-a-time (OAT) sensitivity analysis (SA). However, in case of complex models those approaches may not result in proper identification of the most sensitive parameters for model calibration. In particular local OAT SA methods are only effective for assessing the relative importance of input factors when the model is linear, monotonic, and additive, which is rarely the case for complex environmental models. In contrast Global Sensitivity Analysis (GSA)
is a formal method for statistical evaluation of relevant parameters that contribute significantly to model performance. GSA techniques explore the entire feasible space of each model parameter, and they do not require any assumptions on the model nature (such as linearity or additivity).
In this work we apply the GSA to LISFLOOD, a fully-distributed hydrological model used for flood forecasting at Pan-European scale within the European Flood Awareness System (EFAS). Two case studies are considered, snowmelt- and evapotranspiration-driven catchments, to identify sensitive parameters for both types of hydrological regimes. Results of the GSA will then be used for selecting parameters that need to be estimated during model calibration. Considering the large
number of parameters of a fully-distributed model, a two-step GSA framework is applied. First, we implement the computationally efficient screening method of Morris. This method requires a limited number of simulations and produces a qualitative ranking and selection of important factors. As a second step, we apply the variance-based method of Sobol, only to the subset of factors determined as important during the previous screening. The method of Sobol provides quantitative estimates for first order and total order sensitivity indexes of input factors.
The calibration results after the GSA will be described for both case studies and compared against those obtained by using only prior expert knowledge
Stability refers to the performance with respective changing environmental factors overtime within given location.
Selection for stability is not possible until a biometrical model with suitable parameters is available to provide criteria necessary to rank varieties / breeds for stability.
Stable isotope methodology can be employed in the study and characterisation of soil carbonates on the basis of their reaction time during the acidification step.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
1. Predictive Modeling of Natural Attenuation Processes in Soil
Orlu, R.N.a
, Stewart, D.I.a
, Bottrell, S.H.b
a
Institute of Public Health and Environmental Engineering, School of Civil Engineering,
b
Earth Surface Science Institute, School of Earth and Environment,
University of Leeds, Leeds, United Kingdom, LS2 9JT.
A two –level linear model for a sampling occasion i in a sampling period j is given below (where G and X represent the value on the level-2 and
level-1 predictors respectively):
§ The main aim of this study is to investigate the mechanisms of intrinsic, iron-mediated degradation of volatile petroleum hydrocarbons in
experimental analogues of subsurface regions (laboratory-constructed mesocosms).
§ Initial stages of experimentation involved the assessment of toluene removal in the presence and absence of a) extraneous sources of Fe3+
and b) differing soil matrices
§ The preceding stages involved analysis of the incubated material from the iron-amended (HM, GE, MT, FH, LP), soil-amended (S1, S2,
S3) and un-amended (SO, ST) mesocosms.
§ Statistical analysis using the mixed effects model approach was performed to produce a linear predictive model for toluene removal in the
un-amended and amended mesocosm groups over three sampling periods designated A, B, and C.
§ The analysis was performed using SPSS® software on a .05 alpha level with the data for total dissolved iron (Fe) and pH in the mesocosms
specified as level 2 and level 1 predictors respectively.
1. Atlas, R.M. and Philip, J. 2005. Bioremediation: Applied Microbial Solutions for Real world Environmental Cleanup. Washington, DC, : American society for Microbiology (ASM) Press.
2. Bagiella, E., Sloan, R.P. and Heitjan, D.F. 2000. Mixed-effects models in psychophysiology. Psychophysiology. 37(1), pp.13-20 Myers et al., 2013
3. Song, X.K. and Song, P.X.K. 2007. Correlated Data Analysis: Modeling, Analytics, and Applications. Springer.
4. Wang, L.A. and Goonewardene, Z. 2004. The use of MIXED models in the analysis of animal experiments with repeated measures data. Canadian Journal of Animal Science. 84(1), pp.1-11.
5. West, B.T., Welch, K.B. and Galecki, A.T. 2014. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition. CRC Press.
6. Wu, L. 2009. Mixed Effects Models for Complex Data. CRC Press.
§ Repeatedly measured data from the mesocosm study showed toluene
concentrations, total dissolved iron and pH differed across the amended
and un-amended mesocosms.
§ Preliminary tests for correlation showed moderate (.30 < r < .50) to high
(.50 < r < 1.0) correlation in the time series data for mesocosm pH,
toluene, concentrations and total dissolved iron concentrations (Fe).
§ Tests for normality also indicated the data to be normally distributed.
§ The results of parameter estimation for the period A, B and C data
suggest the specified variables may not be suitable predictors of toluene
removal.
Linear model estimation for panel data is based on the classical general linear model (West et al., 2014). Classical general linear models include regression analysis, analysis of variance or ANOVA, and analysis of covariance or
ANCOVA. Classical general linear model or GLMs are used as statistical tools for experiments with continuous variables and are naturally studied in the framework of the multivariate normal distribution. Mixed effects models
are a rapidly growing application of basic multilevel modeling of longitudinal data. A mixed effect model incorporates the fixed effects assumption (i.e. that the individual specific effects are correlated with the individual
variables) as well as the random effects assumption (i.e. that the individual specific effects are uncorrelated with the independent variables). Data obtained from experimental or observational studies in which data is collected
over several points in time are referred to as repeated measures data (Taris, 2000; Verma, 2015; Nemec and Branch, 1996). The mixed effects model is considered a more appropriate method for analysing repeatedly measured
continuous data in comparison to classical GLMs as mixed models are based on less restrictive assumptions and provide a generally more flexible approach by allowing a wide variety of correlation patterns (or variance-
covariance structures) to be explicitly modeled (Bagiella et al., 2000; Wu, 2009). Monitored natural attenuation is a passive remedial approach which harnesses natural microbial processes to reduce the amount of contaminant in
soil or groundwater. Biodegradation studies assessing the fate of petroleum hydrocarbons in the unsaturated zone through a natural attenuation process may involve the collection of data over several time points. Mixed
effects models avoid violations due to missing data and unequal spacing making the approach particularly suitable for predictive modeling of repeatedly measured data from biodegradation studies.
Table 8.4 Parameter estimates for the level-2 mixed effects model of toluene removal with
predictors*
Parameter Period Estimate Value of test
statistic
p-value
FIXED EFFECTS PARAMETERS
ϒ00 Period A
Period B
Period C
1.610
1.773
15.2
t = -3.305
t = -1.028
t = -1.696
p = .001
p =.283
p = .096
ϒ10 Period A
Period B
Period C
.261
.309
2.23
t = 4.132
t = 1.415
t = 1.854
p = .0001
p =.160
p = .069
ϒ01 Period A
Period B
Period C
.259
.332
.985
t = 2.140
t = 1.865
t = 1.691
p = .035
p =.065
p = .097
ϒ11 Period A
Period B
Period C
.041
.048
.413
t = -2.615
t = -2.141
t = -1.810
p = .010
p =.035
p = .076
VARIANCE-COVARIANCE PARAMETERS
U0j Period A
Period B
Period C
.047
.294
.853
z = 3.368
z = 2.904
z = 2.269
p = .001
p =.004
p = .023
U1j Period A
Period B
Period C
.294
.003
.002
z = 2.904
z = 2.640
z = 2.093
p = .004
p =.008
p = .036
rij Period A
Period B
Period C
.008
.012
.008
z = 7.612
z = 7.000
z = 5.049
p = .0001
p =.0001
p = .0001
*All tests were performed at the .05 alpha level
0 1 2 3 4 5
0.0
0.2
0.4
0.6
0.8
1.0
6 7 8 9 10 11
0.0
0.2
0.4
0.6
0.8
1.0
12 13 14 15 16 17
0.0
0.2
0.4
0.6
0.8
1.0
BA C
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
0 1 2 3 4 5
0.0
0.2
0.4
0.6
0.8
1.0
6 7 8 9 10 11
0.0
0.2
0.4
0.6
0.8
1.0
12 13 14 15 16 17
0.0
0.2
0.4
0.6
0.8
1.0
BA C
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
0 1 2 3 4 5
0.0
0.2
0.4
0.6
0.8
1.0
6 7 8 9 10 11
0.0
0.2
0.4
0.6
0.8
1.0
12 13 14 15 16 17
0.0
0.2
0.4
0.6
0.8
1.0
BA C
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
Toluene(mM)
Period
SO
ST
HM
GE
MT
FH
LP
S1
S2
S3
Background
Analytical approach Preliminary findings
References