The document discusses different types of variables and research designs. It defines a variable as something that can be measured and varies, taking on different values. Variables can be classified based on their relationship in a study, the study design, and unit of measurement. Research designs discussed include experimental, observational, longitudinal, case study, and mixed methods. Various factors are examined such as manipulation of variables, use of control groups, measurement over time, and combining qualitative and quantitative methods.

1. RESEARCH DESIGNS AND VARIABLES
VARIABLES
A variable is a concept that can be measured and takes different
values (it varies).
Is a symbol to which numerals or values are attached. i.e. age,
height weight, income etc.
Variables can be classified in the following ways:-
The causal relationship
The study design
The unit of measurement.
For studies that investigate association or causal relationship.
They use the following variables :

2. Change (Independent) variables : They bring about or cause change
in a situation
Outcome (dependent) variables : They are the effects of a change
variable
Affect or influence (extraneous) variables : They link the cause and
the effect variables. May increase or decrease relationship between
dependent and independent variable.
Connecting or linking (Intervening) variables : They complete the
relationship between cause and effect variables. Used when the
relationship between dependent and independent variable cannot be
established without the intervention of a variable

3. For studies that examine association
They may be used in a controlled experiment study.
The independent variable is manipulated by researcher.
Are of 2 sets
Active variable : Are variables that can be changed or manipulated
Attribute variables: Are variables that cannot be manipulated 3w2
age, gender, education.
For the unit of measurement
Variables can be either categorical or qualitative (nominal or ordinal
scale) or continuous or quantitative ( Interval or ratio scales).

4. Categorical variables : Are measured on nominal or ordinal
measurement scale
Continuous variable : Are made on either an interval or ratio scale
Categorical variables are of 3 types:
Constant variable: Has one value or category eg water,taxi
Dichotomous variable: Has only two categories eg yes/no,
male/female, rich/poor.
Polytomous variable: Has more than two categories eg religion –
Christian, hindu, muslim; Attitudes – favourable, uncertain,
unfavourable

5. Measurement scales for variables
Are classified into four categories
1. Nominal or classificatory scale
It enables classification of individuals, objects or responses based on
shared characteristics.
A variable may have subgroups depending on the extent of variation.
2. Ordinal or ranking scale
Has properties of the nominal scale and also ranks subgroups in a
certain order. Ie ascending or descending order. It reflects the
magnitude of variation in a variable
It can measure attitude or socioeconomic status using average, above
average and below average

6. 3. Interval scale :
Is similar to ordinal scale but uses a unit of measurement that allows
individuals or responses to be placed at equally spaced intervals in
relation to the spread of the variable. eg the Celsius and Fahrenheit
system.
It has a unit of measurement with an arbitrary starting and
termination point
4. Ratio scale :
Is an absolute scale with properties of nominal, ordinal and interval
scale with a starting point fixed at zero. Eg age, height, weight and
income are measurement of this scale.

7. RESEARCH DESIGNS
Action study:
Is a collaborative and adaptive research used in work or community
situations that focuses on solution driven outcomes and is regarded as a
learning cycle.
It has direct relevance to improving practise and advocating for change
Case study design:
Is an in-depth study of a particular research problem that narrows down
broad research to a few easily researchable study.
It provides descriptions of specific and rare cases bringing understanding
of complex issues through context analysis of limited events

8. Causal design:
It measures the impact a change has on existing norms and
assumptions.
It results to empirical association – A conclusion based on finding
an association between independent and dependent variable
Cohort design:
A study conducted over a period of time involving members of the
same population making note of statistical occurrence.
It is used to measure risk factors, causes before outcome and effect
over time. Can use original or secondary data.

9. Cross sectional design:
It has no time frame, it relies ox existing differences and groups are
selected based on existing differences.
It provides a picture of outcome at a time, studies and draws
inferences from existing people or subject differences, estimates
prevalence of an outcome and is not expensive.
Descriptive design:
It provides information on current state and describes what exists
with respect to variables. Answers the questions on who, what,
when, where and how.
It collects large data for detailed analysis used for recommendation
in practise.

10. Experimental design:
It allows control over factors affecting results in an experiment.
It uses time priority and consistency in a causal relationship to
identify correlation. It has a control group and an experimental
group measured on the same dependent variable.
True experiments have control, randomization and manipulation.
Exploratory design:
Is done where there are few or no earlier studies to rely upon to
predict an outcome.
Are used to establish an understanding of how to study an issue and
the effective methodology to gather information.

11. Historical design:
It collects, verifies and synthesizes evidence from the past to
establish facts that defend or refute a hypothesis.
It uses secondary sources and primary documents ie archives.
Longitudinal design:
It follows the same people over time and makes repeated
observations. It measures change in variables over time.
It facilitates prediction of future outcomes based upon earlier
factors.

12. Meta-analysis design:
Meta analysis is an analytical methodology that evaluates and
summarizes results from studies increasing sample size and ability
to study effects of interest.
Are used to develop new understanding of research problem using
synoptic reasoning. It analyses different study results and increases
precision by which effect are estimated.
Mixed method design:
This research uses more approaches to examine a research problem.
It focuses on research problems that require examination under
different circumstances ie culture uses different research methods ie
qualitative and quantitative.

13. Observational design:
It draws conclusion by comparing subjects against a control group.
The researcher has no control over the experiment.
It involves direct observations- where people know you are
watching over them and indirect observation when people do not
know they are being observed.
Philosophical design:
It analyses arguments about fundamental issues to discuss the root of
a research problem. Are framed in 3 ways
Ontology- study that describes nature of reality
Epistemology- study that explores the nature of knowledge
Axiology- The study of values

14. Sequential design:
Is a deliberate staged study that takes place in a sequence. One after
another.
The researcher obtains unlimited number of subjects before making
the decision as to whether to accept the null or alternative hypothesis
It uses sampling techniques to gather data and applies statistical
methods to analyse data.
It uses samples of individuals and interviews to gather information.

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