Variables and Constructs in Research

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Variables & Constructs
M S Ahluwalia

Psychology Super-Notes
Research Methods in Psychology

Copyright © 2020, by M S Ahluwalia
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Variables & Constructs >> Contents
Contents
1. What is a Variable?
2. What are the Types of Variables?
3. What is a Construct?
4. What are the Types of Constructs?
10

Variables & Constructs >> What is a Variable
1. What is a Variable (1/2)
It is important that the values of a variable are observable. Therefore, if what is being studied is a
variable, it has more than one value and each value can be observed. For example, the outcome of
throwing a dice. There are six possible values, and each of them can be observed.
Variable
• A variable is something that varies.
• A variable is “a thing that is changeable” or “a quantity that may have a number
of different values.” (Webster)
Definitions by Behavioural Scientists
• Variable is ‘a property that can take different values’ (Kerlinger, 1986)
• Variables are those attributes of objects, events, things and beings, which can be
measured (D’Amato, 1970)
• Variable is a characteristic or attribute that can take on a number of values, for
example, number of items that an individual solves on a particular test, the speed
with which we respond to a signal, IQ, sex, level of anxiety, and different degrees of
illumination are variables commonly employed in psychological research.
(Postman and Egan, 1949)

Variables & Constructs >> What is a Variable
1. What is a Variable (2/2)
Relation between Variables of Study and Theoretical Concepts
• Variables exist in reality – they are tangible: duration, frequency, rate, or intensity of bar presses;
items checked on a questionnaire; murders committed; books written.
• Whereas theory is an idea - theoretical concepts like hunger, motivation, anxiety are intangible
• Therefore, a researcher makes certain assumptions to relate theory to the real world. This is done
by means of operational definitions used to measure the concepts.
• Example: A theory reveals that increasing anxiety will increase the affiliation motive.
− To test this, the researcher takes the theoretical concepts of anxiety and affiliation motive and
relates them to variables by means of operational definitions.
− The theory is an abstract statement.
− Example, anxiety can be measured by the Anxiety Scale and affiliation by how close people sit
to each other in the experiment. These two measures constitute the variables of the study.
− The scores on the variables of anxiety and distance apart are related to one another as test of
the hypothesis.
− The relationship between the variables is taken as providing support for or against the particular
theory that generated the experiment.

Contents
13

Variables & Constructs >> What are the Types of Variables
2. What are the Types of Variables
Several distinctions are made amongst variables, which leads to categorisation into the following type-
sets:
Categori-
sation of
Variables
1
Stimulus,
Organism
and
Response
Variables
2
Independent
and
Dependent
Variables
3
Extraneous
and
Confounding
Variables
4
Active and
Attribute
Variables
5
Quantitative
and
Categorical
Variables

2.1. Stimulus, Organism and Response Variables
• Psychologists study behaviour or the causes of behaviour as variables.
• Many psychologists use a theoretical viewpoint called the S-O-R model to explain all behaviour.
• Application of S-O-R model (example)
− An experiment is conducted in which a rat is placed on a metal grid floor, the grid is electrified,
and the length of time it takes for the rat to jump from the grid to a platform is measured.
− Using S-O-R model:
• Stimulus variable: Electrical Shock
• Value of variable: Intensity of shock
• Organism variable: Skin resistance of the rat at the time the shock was introduced.
• Response variable: the latency - time elapsed between the onset of shock and the rat jumping
Stimulus Variables (S)
• Refers to some form of
stimulus to which the
organism is sensitive
• Example: Light
Organism Variables (O)
• Refers to the changeable
physiological and
psychological
characteristics being
observed
• Example: anxiety level, age,
heart rate etc.
Response Variables (R)
• Refer to some behaviour or
action of the organism as a
response to the stimulus
• Example: pressing a lever

2.2. Independent and Dependent Variables
Types of
Variables
Independent
Variable
Type E Variable
Type S Variable
Dependent
Variable
Factor that is manipulated
by the experimenter to
ascertain relationship with
an observed phenomenon.
Factor that appears,
disappears, or varies as the
independent variable is
introduced, removed or
varied
One which is manipulated only through
the selection process
One which is directly or experimentally
manipulated by the experimenter

2.2.1. Independent Variables (IV)
Independent variables can be of two types depending upon the mode of manipulation:
• Example: an experimenter wants to study the effect of noise upon task performance in an industry.
− Noise is the IV and task performance is the Dependent Variable.
− Noise is manipulated by dividing into three categories – continuous, intermittent and no noise.
− Noise is being directly manipulated hence, it is a Type-E independent variable.
• Example: an experimenter wants to study the impact of age on the rate of production of workers.
− Age is the IV
− Experimenter selects groups of workers based on age to gets an appropriate representation of
different age groups. Hence this constitutes the examples of S-independent variables.
− Subsequently, the rate of production obtained by each age group will be analysed for testing H.
(Also Stimulus Variable)
Independent
Variables
Refers to the factor that is manipulated by the experimenter to ascertain
relationship with an observed phenomenon.
1.
Type E
Type E independent variable is one which is directly or experimentally manipulated
by the experimenter
2.
Type S
Type S independent variable is one which is manipulated through the process of
selection only

2.2.2. Dependent Variables (DV)
• It is a measure of the behaviour of the person or animal reflecting the IV’s effects
• This response is generally measured using at least one of several different dimensions (Alberto &
Troutman 2006):
Relationship with Independent Variables
• The relationship is that of dependence - one variable depends upon the other.
• Example: Suppose you find a relationship between meaningfulness of learning material and speed
of learning. Speed of learning then depends upon meaningfulness; the greater the meaningfulness,
the faster the learning. Speed of learning is the DV and meaningfulness the IV. Similarly, sudden
noise is IV; change in breathing is DV.
• An experiment confirms the relationship between an independent and a dependent variable.
Dependent
Variables
Refers to the factor that appears, disappears, or varies as the experimenter
introduces, removes or varies the independent variable. (Townsend,1953)
Frequency
• Number of times a
particular
behaviour occurs
Duration
• Amount of time
that a behaviour
lasts
Latency
• Amount of time
between stimulus
and performance
of behaviour
Force
• Intensity or
strength of a
behaviour

2.3. Extraneous and Confounding Variables
Types of
Variables
Extraneous
Variables
Organismic
Variables
Situational
Variables
Sequential
Variables
Confounding
Variables
Variables that may ‘mask’ the
relationship between
independent variable and
dependent variable
Factor that appears,
disappears, or varies as the
independent variable is
introduced, removed or varied
Environment or
experiment related
variables
Subject related
variables
Variables such as
adaptation, fatigue or
practice effects

2.3.1. Extraneous Variables
• They may directly affect the dependent variable, or combine with the independent variable to do it
• They must be controlled so that experimenter can determine whether the dependent variable
changes in relation to variation in the independent variable.
• They are relevant in nature, and in experimental studies.
Types of Extraneous Variables
• Organismic Variables
− Subject related variables including age, sex, intelligence, personality etc.
• Situational Variables
− Environmental variables related to the experimental setting (e.g. noise, temperature, humidity)
− Experimental task related variables
• Sequential Variables
− When participants need to be tested in several conditions, this exposure may result in sequence
effects - adaptation, fatigue or practice effects which, if allowed to operate, affect the result.
Extraneous
Variables
Variables that may ‘mask’ the relationship between independent variable and
dependent variable. These factors, not intended to be measured in the study, may
increase or decrease the magnitude or strength of the relationship between the
independent and dependent variables.

2.3.1. Extraneous Variables
Causal Relationship between Independent, Dependent and Extraneous Variables
• Example: A study on the relationship between smoking and coronary heart disease.
• Various variables may be involved such as number of cigarettes or amount of tobacco smoked
every day; the duration of smoking; the age of the smoker; dietary habits; and the amount of
exercise undertaken by the individuals.
• These factors affect the extent to which smoking might cause coronary heart disease. They may
increase or decrease the magnitude of the relationship.
• In this case, the different sets of variables are as follows:
Extent of Smoking
Coronary Heart
Disease
Independent Variable
Assumed Cause
Dependent Variable
Assumed Effect
Age of the person,
Duration of smoking,
Extent of exercise etc.
Extraneous Variables
Affect the Relationship

2.3.2. Confounding Variables
• Example: in a study of the effect of television viewing on perception of violence, the experimental
group contained only adolescents, whereas the control group only adults. Age of participants
would be confounded with the independent variable under study.
• Confounding makes the conclusions of the study doubtful.
• It is necessary to unconfound the variables.
Confounding
Variables
If researcher is not careful while doing a study, then some variable may get
combined with the independent variable, in a way that the effect of one cannot be
separated from the effect of other. This is known as confounding. And the variable
causing it is called confounding variable.

2.4. Active and Attribute Variables
Types of
Variables
Active
Variables
Attribute
Variables
• Any variable that is manipulated.
• Example: reward, punishment, methods of
teaching, creating anxiety through
instructions etc.
• Any variable which is not manipulated but
measured by the experimenter
• Example: human characteristics like
intelligence, aptitudes, sex, socio-economic
status, education, field dependence and need
for achievement.
• Organisations, institutions, groups, population
and geographical areas also have attributes.
Organisations are variably productive;
groups differ in cohesiveness; geographical
areas vary widely in resources.

2.5. Quantitative and Categorical Variables
Types of
Variables
Quantitative
Variables
Continuous
Variables
Discrete
Variables
Categorical
Variables
Constant-value
Variables
Dichotomous
Variables
Polytomous
Variables
• Any variable that varies
in amount
• Example: intelligence etc.
Any variable that varies in kind
Example: gender, race, religion
Variable can have only two
categories as in yes/no,
good/bad and rich/poor
Variable can have only one
value or category
Example: taxi, tree, water
Variables can have more
than two categories, for
Example: religions (Ch.., Is.., ..
Variables which contain a
clear gap. Example: the no.
of books in a library, etc.
Can be measured in any
degree of exactness
Example: age, height, etc.

2.5.1. Quantitative Variables
Types of Quantitative Variables
Continuous Variables
• A variable which is capable of being
measured in any arbitrary degree
of fineness or exactness.
• It falls along a continuum and is not
limited to a certain number of values
• Example: age, height, intelligence,
reaction time, etc.
The age of the person can be
measured in years, month and days
Discrete Variables
• Variables which are not capable of
being measured in any arbitrary
degree of fineness or exactness
because they contain a clear gap.
• It falls into separate bins with no
intermediate values possible
• Example: the number of members in
a family, no. of females in a particular
group, no of books in a library etc.
Quantitative
Variables
Any variable that varies in amount. Precise and accurate measurement is possible
because they can be easily ordered in terms of increasing and decreasing
magnitude.
Example: speed of response, intensity of sound, level of Illumination, intelligence etc.

Contents
26

Variables & Constructs >> What is a Construct
3. What is a Construct (1/2)
• Concepts are building block of thinking. They allow us to organise knowledge in systematic
ways.
• They represent properties, abstraction and relations between the features.
• Example: ‘achievement’ –
− It is an abstraction formed from the observation of certain behaviours of children.
− These behaviours are associated with the mastery or “learning” of school tasks – reading words, doing arithmetic problems,
drawing pictures, and so on.
− The various observed behaviours are put together and expressed in a word – ‘achievement’.
• ‘Intelligence’, ‘aggressiveness,’ ‘conformity’, and ‘honesty’ are some of the concepts used to express
varieties of human behaviour of interest to behavioural scientists.
Concept
Any describable regularity of real or imagined, events or objects (Bourne, Ekstrand,
& Dominowski, 1971)
A concept is a set of features connected by some rule (Hulse, Egeth, Deese 1980)

Variables & Constructs >> What is a Construct
3. What is a Construct (2/2)
Characteristics of a Construct
1. A construct is part of a theoretical framework and relates in various ways to other constructs
2. A construct is usually operationally defined so as to allow its observation and measurement.
• Example: “Intelligence” is a concept, an abstraction from intelligent and nonintelligent behaviours,
but, as a construct, scientists use “intelligence” consciously and systematically in two ways:
1. It is a part of theoretical schemes and relates in various ways to other constructs. In this sense,
school achievement may also be, in part, a function of intelligence and motivation.
2. “Intelligence” is defined and specified so that it can be observed and measured. We can record
observations of the intelligence of children by administering X intelligence test to them, or we can
ask teachers to tell us the relative degrees of intelligence of their pupils.
• Example: “reinforcement”
− At a theoretical level, reinforcement can be, and is, related to other constructs such as drive,
motivation, association, and habit strength.
− Reinforcement may be operationally defined as any stimulus or event which increases the
probability of the occurrence of a (desired) response.
Construct
Concepts which are invented, adapted or constructed by the researchers for special
scientific purposes.

Contents
29

Variables & Constructs >> What are the Types of Constructs
4. What are the Types of Constructs (1/2)
Types of
Constructs
Intervening
Variables
Hypothetical
Constructs
• A construct which is used as a summary
term for a group of other constructs
• It has no meaning apart from the context in
which it is used.
• Example: “hostility” - which is inferred from
hostile and aggressive acts.
• Example: Clark Hull utilised intervening
variables in the formation of his learning
theory. He defined Reaction Potential (RP) as
the combination of habit strength and drive
(Hilgard & Bower, 1966). RP is an intervening
variable, as it only summarizes the other
constructs – habit strength and drive, and
has meaning only in relation to them
• A theoretical term which is employed to
describe something “real”
• It is an intermediary which has tangible
characteristics
• Example: “reflex” refers to certain readily
observable characteristics such as the
patellar reflex (knee jerk.) The term “reflex”
refers to the chain of events that occurs
within the organism after the application of
the stimulus and before the response. Hence,
reflex is a hypothetical construct.
• Example: Habit strength, defined by Hull as
the number of reinforced trials, is a
hypothetical construct.

Variables & Constructs >> What are the Types of Constructs
4. What are the Types of Constructs (2/2)
A combined example
Suppose an equation is developed to tell us how much a person knows:
K = AC X IQ
Where:
• AC = amount of conditioning, defined as the number of reinforced trials a person receives
• IQ = intelligence, defined as that person’s score on a standard intelligence test
• K = knowledge, defined as being a function of AC and IQ
• AC and IQ are hypothetical constructs - they describe something real and are defined directly
by the operations that established them or by which they were measured).
• K is an intervening variables - it has no meaning of its own, but only summarizes or stands for
other constructs.
• However, if K was defined as the number of correct solutions a person achieved on a “knowledge
test,” then K would also be a hypothetical construct

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