Social Research Methods: Qualitative and Quantitative Approaches

QUALITATIVE AND QUANTITATIVE MEASUREMENT

Principles of Good Measurement.Three features
of good measurement whether we are considering
using a single-indicator or a scale or index (discussed
next) to measure a variable are that (1) the attributes
or categories of a variable should be mutually
exclusive, (2) they should also be exhaustive, and
(3) the measurement should be unidimensional.

1. Mutually exclusive attributesmeans that
   an individual or a case will go into one and only one
   variable category. For example, we wish to measure
   the variable type of religion using the four attributes
   Christian, non-Christian, Jewish, and Muslim. Our
   measure is not mutually exclusive. Both Islam and
   Judaism are non-Christian religious faiths. A Jew-
   ish person and a Muslim fit into two categories:
   (1) the non-Christian and (2) Jewish or Muslim. An-
   other example without mutually exclusive attributes
   is to measure the type of city using the three cate-
   gories of river port city, state capital, and access to
   an international airport. A city could be all three (a
   river port state capital with an international airport),
   any combination of the three, or none of the three.
   To have mutually exclusive attitudes, we must cre-
   ate categories so that cases cannot be placed into
   more than one category.


2. Exhaustive attributemeans that every case
   has a place to go or fits into at least one of a vari-
   able’s categories. Returning to the example of the
   variable religion, with the four categorical attributes
   of Christian, non-Christian, Jewish, and Muslim,
   say we drop the non-Christian category to make the
   attributes mutually exclusive: Christian, Jewish, or
   Muslim. These are not exclusive attributes. The
   Buddhist, Hindu, atheist, and agnostic do not fit
   anywhere. We must create attributes to cover every
   possible situation. For example, Christian, Jewish,
   Muslim, or Other attributes for religion would be
   exclusive and mutually exclusive.


3. Unidimensionalitymeans that a measure
   fits together or measures one single, coherent con-
   struct. Unidimensionality was hinted at in the pre-
   vious discussions of construct and content validity.
   Unidimensionality states that if we combine several
   specific pieces of information into a single score
   or measure, all of the pieces should measure the

same thing. We sometimes use a more advanced

technique—factor analysis —to test for the unidi-

mensionality of data.

We may see an apparent contradiction between

the idea of using multiple indicators or a scale or

index (see next section) to capture diverse parts of

a complex construct and the criteria of unidimen-

sionality. The contraction is apparent only because

constructs vary theoretically by level of abstraction.

We may define a complex, abstract construct using

multiple subdimensions, each being a part of the

complex construct’s overall content. In contrast,

simple, low-level constructs that are concrete typi-

cally have just one dimension. For example, “fem-

inist ideology” is a highly abstract and complex

construct. It includes specific beliefs and attitudes

toward social, economic, political, family, and sex-

ual relations. The ideology’s belief areas are parts of

the single, more abstract and general construct. The

parts fit together as a whole. They are mutually re-

inforcing and collectively form one set of beliefs

about the dignity, strength, and power of women.

To create a unidimensional measure of feminist ide-

ology requires us to conceptualize it as a unified be-

lief system that might vary from very antifeminist

to very profeminist. We can test the convergence va-

lidity of our measure with multiple indicators that

tap the construct’s subparts. If one belief area (e.g.,

sexual relations) is consistently distinct from all

other areas in empirical tests, then we question its

unidimensionality.

It is easy to become confused about unidimen-

sionality because an indicator we use for a simple

Unidimensionality The principle that when using

multiple indicators to measure a construct, all indica-

tors should consistently fit together and indicate a

single construct.

Mutually exclusive attribute The principle that vari-

able attributes or categories in a measure are organized

so that responses fit into only one category and there

is no overlap.

Exhaustive attributes The principle that attributes

or categories in a measure should provide a category

for all possible responses.