The document discusses various types of research design including descriptive, correlational, semi-experimental, experimental, and meta-analytic designs. It describes key elements of research design such as the degree to which the research question is crystalized, the method of data collection, the researcher's ability to influence variables, the purpose and time dimension of the study, and whether it occurs in a laboratory or field setting. The document also discusses exploratory and causal research designs, and summarizes descriptive and experimental research designs. It covers topics such as variables, measurement, scales, sources of error, and ensuring validity and reliability.

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UNIT II Research Design And Measurement
Research Design – Definition:Research design expresses both the structure of the
research problem—the frame-work, organization, or configuration of the
relationships among variables of a study—and the plan of investigation used to
obtain empirical evidence on those relationships.Essentials of Research
Design:An activity- and time-based plan; plan always based on the research
question; A guide for selecting sources and types of information; A framework for
specifying the relationships among the study’s variables; A procedural outline for
every research activity.
Types of Research Design:1) Descriptive – Detailed descriptions of specific
situations using interviews, observations, document overview, numerical
descriptions;e.g., case-study, naturalistic observation, survey; 2) Correlational –
Quantitative analyses of the strength of relationships between two or more
variables e.g., case-control study, observational study; 3) Semi-experimental –
Comparing a group that gets a particular intervention with another group that is
similar in characteristic but did not receive the intervention. e.g., field
experiment, quasi-experiment; 4) Experimental – Assigning an intervention to
selected groups by random assignmente.g., experiment with random assignment;
5) Meta-analytic e.g., meta-analysis.
Descriptors of research design:1) The degree to which the research question has
been crystalized – Exploratory Study, Formal Study. 2) The method of data
collection – Monitoring, Communication study. 3) The power of researcher to
produce effects in the variables under study – Experimental, Ex post facto. 4) The
purpose of the study – Reporting, Descriptive, Casual – Explanatory, Predictive. 5)
The time dimension – Cross-sectional, Longitudinal. The topic scope – breadth
and depth – of the study – Case & Statistical Study. 6) The research environment -
Field setting, Laboratory research, Simulation. 7) The participants’ perceptions of
research activity - Actual routine, Modified routine.
Definitions:Exploratory studies:tend toward loose structures with the objective
of discovering future research tasks. The immediate purpose of exploration is
usually to develop hypotheses or questions for further research. Formal Study: it
begins with a hypothesis or research question and involves precise procedures
and data source specifications. The goal of a formal research design is to test the
hypotheses or answer the research questions posed. Monitoring:includes studies
in which the researcher inspects the activities of a subject or the nature of some
material without attempting to elicit responses from anyone. Communication
study: the researcher questions the subjects and collects their responses by
personal or impersonal means. Experiment: the researcher attempts to control
and/or manipulate the variables in the study. Ex post facto design: investigators
have no control over the variables in the sense of being able to manipulate them.
They can only report what has happened or what is happening. Reporting study
provides a summation of data, often recasting data to achieve a deeper
understanding or to generate statistics for comparison. Causal-Explanatory: a
study is concerned with learning why—that is, how one variable produces
changes in another.Causal-Predictive:attempts to predict an effect on one
variable by manipulating another variable while holding all other variables
constant.Cross-sectional studies:are carried out once and represent a snapshot
of one point in time. Longitudinal studies:are repeated over an extended period.
Statistical studies:are designed for breadth rather than depth. They attempt to
capture a population’s characteristics by making inferences from a sample’s
characteristics. Hypotheses are tested quantitatively. Generalizations about
findings are presented based on the representativeness of the sample and the
validity of the design. Case studies: place more emphasis on a full contextual
analysis of fewer events or conditions and their interrelations. Although
hypotheses are often used, the reliance on qualitative data makes support or
rejection more difficult. An emphasis on detail provides valuable insight for
problem solving, evaluation, and strategy. This detail is secured from multiple
sources of information. It allows evidence to be verified and avoids missing data.
Designs also differ as to whether they occur under actual environmental
conditions (Field conditions) or under staged or manipulated conditions
(Laboratory conditions). Simulation: To replicate the essence of a system or
process.Participant’s perceptual awareness:when people in a disguised study
perceive that research is being conducted. Participants’ perceptual awareness
influences the outcomes of the research in subtle ways or more dramatically.
Exploratory and Casual Research Design:Exploratory research design relies
heavily on Qualitative techniques and these are the four exploratory
techniques:a) Secondary data analysis: Doing study on the studies made by
others for their own purposes;b) Experience surveys:seek Interviewee ideas
about important issues or aspects of the subject and discover what is important
across the subject’s range of knowledge;c) Focus groups:Group of people and a
Moderator meet and Moderator use group dynamics principles to focus or guide
the group in exchange of ideas, feelings and experience on a specific topic; d)
Two-stage designs:(i) clearly defining the research question and (ii) developing
the research design.
Casual Research Design:The essential element of causation is that A “produces” B
or A “forces” B to occur. The ideal standard of causation requires that one
variable always causes another and no other variable has the same causal effect.
Method of Agreement: (John Stuart Mill) “When two or more cases of a given
phenomenon have one and only one condition in common, then that condition
may be regarded as the cause (or effect) of the phenomenon.” Method of
Difference: (John Stuart Mill)“If there are two or more cases, and in one of them
observation can be made, and if variable C occurs when observation Z is made,
and does not occur when observation Z is not made; then it can be asserted that
there is a causal relationship between C and Z. Causal Hypothesis
Testing:1.Covariation between A and B, 2. Time order of events moving the
hypothesized direction, 3. No other possible causes of B. Random Assignment:All
factors (except DV) must be held constant and not go against another variable &
each factor must have equal chance. Relationship between two variables: 1)
Symmetrical: is one in which two variables fluctuate together; 2) Reciprocal:
when two variables mutually influence or reinforce each other; 3) Asymmetrical:
Changes in one variable (IV) responsible for changes in another variable (DV);
Types of Asymmetrical: Stimulus-Response; Property-Disposition(nature);
Disposition-Behavior; Property-Behavior.
Descriptive and Experimental Design:Descriptive is a more formalized study and
its objectives are 1. Descriptions of phenomena or characteristics associated with
a subject population (the who, what, when, where, and how of a topic). 2.
Estimates of the proportions of a population that have these characteristics. 3.
Discovery of associations among different variables.
Experimental Design:Experiments are studies involving intervention by the
researcher beyond that required for measurement. The usual intervention is to
manipulate some variable in a setting and observe how it affects the subjects
being studied (e.g., people or physical entities). The researcher manipulates the
independent or explanatory variable and then observes whether the
hypothesized dependent variable is affected by the intervention. Advantages: 1)
the researcher’s ability to manipulate the independent variable; 2) contamination
from extraneous variables can be controlled; 3) the convenience and cost of
experimentation are superior to other methods; 4) replication—repeating an
experiment with different subject groups and conditions. Disadvantages: 1) The
artificiality of the laboratory; 2) generalization from nonprobability samples; 3)
Sometimes Outrun the budget; 4) It is only effectively targeted at problems of
the present or immediate future; 5) Sometimes the study is not so ethical. Steps
for conducting an experiment:1. Select relevant variables.2. Specify the
treatment levels. 3. Control the experimental environment. 4. Choose the
experimental design.5. Select and assign the subjects.6. Pilot test, revise, and
test.7. Analyze the data.
Different types of experimental design: 1) Repeated measures design (or within-
subjects design) requires one group of samples or participants. This same group is
exposed to all of the levels of the independent variable of interest. 2)
Independent samples design (or between-subjects design), the samples or
participants are assigned into equally sized groups and each group receives a
different treatment. 3) Matched pairs design the samples or participants are
matched into pairs with most similarity to each other and each member of the
pair is randomly assigned to a different experimental condition. 4)Factorial
design is used where there are several independent variables and the researcher
is interested in their combined effect on the dependent variable.
The many experimental designs vary widely in their power to control
contamination of the relationship between independent and dependent
variables. The most widely accepted designs are based on this characteristic of
control: (1) preexperiments: After-only study, One-goup pretest-posttest design,
Static group comparison; (2) true experiments: Pretest-posttest control group
design, Posttest-only control group design;(3) field experiments (quasi- or semi-
): nonequivalent control group design, Separate sample pretest-posttest design,
Group time series design.
Validity of findings:Mechanism to check whether results are true and whether a
measureaccomplishes its claims. Internal Validity: Checking whether he
conclusions we draw about a demonstrated experimental relationship truly imply
cause.Threats to Internal Validity:•History •Maturation •Testing •
Instrumentation • Selection • Statistical regression • Experimental mortality
External validity:Does an observed causal relationship generalize across persons,
settings, and times. Threats to External Validity:• Reactivity of testing on X •
Interaction of selection and X • Other reactive factors.
Variables in Research:Refer cheatsheet of Unit I.
Measurement and scaling:Measurement in research consists of assigning
numbers to empirical events, objects or properties, or activities in compliance
with a set of rules. 3-Step Process of Measurement:1.
Selectingobservableempiricalevents. 2. Developing a set of mapping rules: a
scheme for assigning numbers or symbols to represent aspects of the event being
measured. 3. Applying the mapping rule(s) to each observation of that
event.Variables being studied in research may be classified as objects or as
properties. Objects include the concepts of ordinary experience, such as tangible
items like furniture. Properties are the characteristics of the object.Mapping rule
assumptions for Measurement Scales:1. Numbers are used to classify, group, or
sort responses. 2. Numbers are ordered. 3. Differences between numbers are
ordered. 4. The number series has a unique origin indicated by the number
zero.Different Scales:1) Nominal: Just a classification but no order, distance, or
natural origin (e.g., Gender) 2) Ordinal: Classification and order but no distance
or natural origin (e.g., Rice Variety) 3) Interval:Classification, order, and distance,
but no natural origin (e.g., Temperature) 4) Ratio:Classification, order, distance,
and natural origin (e.g., Age in Years). Construction of Measurement: is based on
the following questions: 1) Is distribution expected to be normal?; 2) What is my

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expected sample size?; 3) How many groups will be compared?; 4) Are groups
related or independent?
Sources of Error in Measurement: 1) The respondent; 2) Situational factors; 3)
The measurer; 4) The instrument. Characteristics of good measurement: Validity;
Reliability; Practicality. Validity & Reliability of Instrument:Validity: Content;
Criterion-Related; Concurrent; Predictive; Construct. Reliability: Stability;
Equivalence; Internal Consistency.