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Measurement of Constructs - Coggle Diagram

- - - - Operationalization refers to the process of developing indicators or items for measuring these constructs.
      - Indicators operate at the empirical level, in contrast to constructs, which are conceptualized at the theoretical level. The combination of indicators at the empirical level representing a given construct is called a variable, variables may be independent, dependent, mediating, or moderating, depending on how they are employed in a research study
        
        Values of attributes may be quantitative (numeric) or qualitative (non- numeric). Quantitative data can be analyzed using quantitative data analysis techniques, such as regression or structural equation modeling, while qualitative data require qualitative data analysis techniques, such as coding.
        
        Indicators may be reflective or formative. A reflective indicator is a measure that reflects an underlying construct
        
        A formative indicator is a measure that forms or contributes an underlying construct. Such indicators may represent different dimensions of the construct of interest.
- - - - 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 non- availability of the underlying construct). Most measurement in the natural sciences and engineering, such as mass, incline of a plane, and electric charge, employ ratio scales, as are some social science variables such as age, tenure in an organization, and firm size (measured as employee count or gross revenues)
        
        Based on the four generic types of scales discussed above, we can create specific rating scales for social science research. Common rating scales include binary, Likert, semantic differential, or Guttman scales. Other less common scales are not discussed here.
        
        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.
        
        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
        
        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 as adjectives framed as polar opposites.
        
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