Author:
Brandenburger Martina,Schwichow Martin
Abstract
AbstractModels based on Rasch’s (1960) measurement theory build quantitative, continuous latent variables based on persons’ categorical responses. In contrast, within latent class analysis (LCA), persons are represented by qualitative, categorical latent variables. LCA can be used to identify patterns within categorical responses. In this chapter, we present the general idea of the LCA, including conventions for interpreting results, compare the LCA with Rasch analysis and combine the LCA’s results with a unidimensional Rasch model. Our presentation is based on a concrete empirical example that investigates experimental design errors and includes the used data set and R scripts as supplemental materials.
Publisher
Springer International Publishing
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