• The process of assigning numbers or labels to units of analysis in order
to represent conceptual properties.
• The measurement process begins with formulation of research problem
• Every research problem contains terms – concepts or variables.
• The ultimate goal of measurement is to specify
clearly observable referents of the terms contained
in one’s hypothesis.
• Thus, the entire measurement process consists of
moving from the abstract (concepts) to the
concrete (measures of the concept.
• Initial step is to clarify the concepts
embedded in one’s hypothesis with words
• Process of formulating and clarifying
concepts is called conceptualization. It is
linked to theory testing and construction.
• The conceptualization is an ongoing process
that may occur prior to any particular
empirical investigation and is usually
continues through research as theories and
their constituent concepts are refined and
• The conceptualization of complex concepts such as social capital
often requires careful distinctions among similar ideas and breaking
down the concept into various components or dimensions.
• Measurement assumes the possibility of assigning different values or
categories to unit of analysis; hence, we measure concepts tat vary,
which we refer to as variables.
• However, many social science concepts like social capital, or wealth
etc are not directly measurable. These are rather manifestation of
several directly measurable variables. After conceptualization , the
next step is to identify such manifestations of one’s concepts.
• Once the meaning of the concept is clarified and
the concept is constructed as variable, the process
of operationalization of the measurement process
• First step of the operationalization is to set up an
operational definition as a counterpart of
conceptual definition that corresponds reasonably
good to the concept in question.
• An operational definition describes the research
operation that will specify the value and category
of the variable on each case.
• While creating operational definitions, a researcher may
consider many different empirical representations or
• An indicator consists of a single observable measure, such as a
single questionnaire item in the survey.
• No two indicators measure a given concept or variable in the
same way, and no one indicator is likely to correspond
perfectly to its underlying concept.
• Indicators provide imperfect representations of the
concepts for two reasons:
- Indicators often contain errors of classification
- Indicators rarely capture all the meaning of a
• Because of the imperfect correspondence between
indicators and concepts, researchers often choose
to rely on more than one indicator when
operationalizing a concept.
Operationalizing the concept of religiosity
• My religious beliefs are what really lie behind my
whole approach to life. (1) this is definitely not so
(2) Probably not so (3) Probably so (4) definitely
• Self reports provide simple and generally accurate
measures of background variables such as age,
gender, marital status and education.
• Composite measures: in self report attitude
measurement, responses to several questions
frequently are combines to create and index or
• There are numerous composite measures of
prejudice, combining from two to twenty
questions or more-
• Do you think there should be laws against marriages
between blacks and whites? Yes/no
• White people have the right to keep blacks out of their
neighborhoods if they want to, and black should
respect that right. Do you agree strongly, agree slightly,
disagree slightly, or disagree strongly with this
• Observation: observation provides direct and
generally unequivocal evidence of overt behavior,
but it also is used to measure subjective
experience such as feelings and attitudes.
• Archival records: which refers to existing recorded
information, provide another invaluable source of
Level of measurement
• System in which cases are classified into two or more
categories on some variable, such as gender, race, religious
• In nominal measurement numbers (more accurately
numerals) are assigned to the categories simply as labels
or codes for the researcher’s convenience in collecting and
analyzing the data.
• Categories of the variable should possess two
characteristics: they must be exhaustive and mutually
• In ordinal measurement, number indicate only the rank order of cases on some
• Ordinal measurement allows the researchers to make an accurate judgment
about one thing compared to another, even when they can not make an accurate
absolute judgment. Ex.:
Individual’s ranking of certain leisure activities in terms of the pleasure derived from them. The three
activities are ranked as:
3. Reading sociology
, where one, two and three represent individuals’ ranking of the leisure activities
• In the realm of social measurement one can
probably say with some certitude whether security
or chance for advancement is the more important
job characteristic, without being able to say how
important either characteristic is.
• The ability of human observers to make such
comparative judgments permits a wide range of
reasonably accurate social measurements at the
ordinal level. For example, measures of
socioeconomic status, intelligence etc.
• Interval measurement has the quality of the nominal
and ordinal levels, plus the requirement that equal
distances or intervals between numbers represents
equal distances in the variable being measured.
• For Ex. Fahrenheit temperature scale: the difference
between 20ºF and 30ºF is the same as the difference
between 90ºF and 100ºF- 10ºF. We can infer not only
that 100ºF is hotter than 90ºF but also how much it
• Though interval measurement system does not have
absolute zero that is it is not a fixed but an arbitrary
• Therefore, we can not say that 100ºF is twice as hot
as 50ºF as it will require a fixed zero point which
interval measurement system does not have.
• Includes the feature of other levels plus an
absolute zero point.
• The presence of an absolute zero makes it possible
to multiply or divide scale numbers meaningfully
and thereby form ratios.
• Ex. Rs. 10000 and Rs. 20000, one can divide the
Information provided by the four
levels of measurement
Nominal Ordinal Interval Ratio
Classification X X X X
Rank Order X X X
Equal Intervals X X
Reliability and validity
• Reliability is concerned with questions of stability
• An ex. of a highly reliable measuring instrument is
a steel tape measure. A cloth tape measure would
be somewhat less reliable.
• SRS data is reliable.
• Unreliable things cannot be valid.
• Measurement validity refers to the extent of
matching, congruence, or goodness of fit between
an operational definition and the concept it is
purported to measure.
• Ex. Amniocentesis, it is a valid measure of
biological sex which can determine with virtually
Sources of error
Observed value= true value + systematic error+
The first source of variation is true differences in
the concept the operation is intended to measure.
Ex. IQ test ought to reflect only true differences in
intelligence and nothing else.
• Systematic measurement error results from the
factors that systematically influence either the
process of measurement or the concept being
• When the respondent’s sensitivity or
responsiveness to a measure is affected by the
process of observation or measurement, we refer
to this a s a reactive measurement effect.
• Random measurement error is unrelated to
true differences in the concept being
measured. It is the result of temporary,
• Ex. A tired and bored respondent may give
erroneous responses by not attending
carefully to the questions asked.
• Similarly an ambiguously worded question
will produce random errors by eliciting
responses that vary according to
respondent’s interpretation of the question’s
• Such a error is random because its presence,
extent and direction are unpredictable.
• Reliability indicates consistency, or the extent to
which a measure does not contain random error.
• Test retest reliability: the procedure involves
testing the same persons or units on two separate
Low reliability High reliability High reliability
Low validity Low validity High validity
High random error Low random error Low random error
Low systematic error High systematic error Low systematic error
Split half and internal consistency
• The second set of procedures for assessing
reliability estimates the agreement or equivalence
among the constituent parts or items of a multi-
• Ex. Age of women and age at marriage.
• Reliability assessment is relatively simple, validity
assessment by contrast is more problematic.
• Systematic errors which affect validity but not
reliability, are more difficult to detect than
• The issue of measurement validity generally
cannot be divorced from larger theoretical
• Face validity: refers simply to a personal judgment
that an operational definition appears, on the face
of it, to measure the concept it is intended to
• Content validity: concerns the extent to which a
measure adequately represents all facets of a