Scale analysis (statistics)


Scale analysis (statistics)

In statistics, scale analysis is a set of methods to analyse survey data, in which responses to questions are combined to measure a latent variable. These items can be dichotomous (e.g. yes/no, agree/disagree, correct/incorrect) or polytomous (e.g. disagree strongly/disagree/neutral/agree/agree strongly). Any measurement for such data is required to be reliable, valid, and homogeneous with comparable results over different studies.

Measurement models

Measurement is the assignment of numbers to subjects in such a way that the relations between the objects are represented by the relations between the numbers (Michell, 1990).

Traditional models

* Likert scale
* Reliability analysis, see also Classical test theory and Cronbach's alpha
* Factor analysis

Modern models based on Item response theory

* Guttman scale
* Mokken scale
* Rasch model
* (Circular) Unfolding analysis
* Circumplex model

Other models

* Latent class analysis
* Multidimensional scaling

References

* Michell, J (1990). An Introduction to the logic of Psychological Measurement. Hillsdales, NJ: Lawrences Erlbaum Associates Publ.


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