Chapter 6: Measurement of Constructs (Conceptualization:…
Chapter 6: Measurement of Constructs
Conceptualization: Conceptualization is the mental process by which fuzzy and imprecise constructs (concepts) and their constituent components are defined in concrete and precise terms.
Multidimensional constructs consist of two or more underlying dimensions.
Unidimensional constructs are those that are expected to have a single underlying dimension.
Operationalization: Operationalization refers to the process of developing indicators or items for measuring these constructs. This process allows us to examine the closeness amongst these indicators as an assessment of their accuracy (reliability).
Indicators operate at the empirical level, in contrast to constructs, which are conceptualized at the theoretical level.
Value: Values of attributes may be quantitative (numeric) or qualitative
Quantitative data can be analyzed using quantitative data analysis techniques, such as regression or structural equation modeling
qualitative data require qualitative data analysis techniques, such as coding.
Formative: qualitative data require qualitative data analysis techniques, such as coding.
A reflective indicator is a measure that “reflects” an underlying construct.
Levels of Measurement: Levels of measurement, also called rating scales, refer to the values that an indicator can take (but says nothing about the indicator itself)
Statistical properties of rating scales
Nominal scales, also called categorical scales, measure categorical data. These scales are used for variables or indicators that have mutually exclusive attributes
Ordinal scales are those that measure rank-ordered data, such as the ranking of students in a class as first, second, third, and so forth, based on their grade point average or test scores.
Interval scales are those where the values measured are not only rank-ordered, but are also equidistant from adjacent attributes.
Ratio scales are those that have all the qualities of nominal, ordinal, and interval scales, and in addition, also have a “true zero” point (where the value zero implies lack or nonavailability of the underlying construct).
Binary scales. Binary scales are nominal scales consisting of binary items that assume one of two possible values, such as yes or no, true or false, and so on.
FOUNDERS & VARIOUS SCALE DESIGNS
Semantic differential scale. This is a composite (multi-item) scale where respondents are asked to indicate their opinions or feelings toward a single statement using different pairs of adjectives framed as polar opposites.
Guttman scale. Designed by Louis Guttman, this composite scale uses a series of items arranged in increasing order of intensity of the construct of interest, from least intense to most intense.
Likert scale. Designed by Rensis Likert, this is a very popular rating scale for measuring ordinal data in social science research. This scale includes Likert items that are simply-worded statements to which respondents can indicate their extent of agreement or disagreement on a five or seven-point scale ranging from “strongly disagree” to “strongly agree”.
This Chapter Examines the process and outcomes of scale development
An index is a composite score derived from aggregating measures of multiple constructs (called components) using a set of rules and formulas. It is different from scales in that scales also aggregate measures, but these measures measure different dimensions or the same dimension of a single construct.
Scales and indexes generate ordinal measures of unidimensional constructs. However, researchers sometimes wish to summarize measures of two or more constructs to create a set of categories or types called a typology. Unlike scales or indexes, typologies are multidimensional but include only nominal variables.