Work

Utilizing Latent Class Analysis (LCA) to Analyze Response Patterns in Categorical Data

Year: 2023

Type: book-chapter

Abstract: Models 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.

Source: Contemporary trends and issues in science education

DOI: 10.1007/978-3-031-28776-3_6

Authors: Martina Brandenburger, Martin Schwichow

Institution: University of Education Freiburg

Language: English

Topic: Psychometric Methodologies and Testing

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

OpenAlex ID: W4385434530