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Analysis of Categorical Data with the R Package confreq

by 1,*,† and 2,†
1
Center for International Student Assessment (ZIB), Technical University Munich, 80335 München, Germany
2
Department of Psychology, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, 91052 Erlangen, Germany
*
Author to whom correspondence should be addressed.
Both authors contributed equally to this work.
Academic Editor: Peida Zhan
Psych 2021, 3(3), 522-541; https://doi.org/10.3390/psych3030034
Received: 3 August 2021 / Revised: 30 August 2021 / Accepted: 31 August 2021 / Published: 7 September 2021
The person-centered approach in categorical data analysis is introduced as a complementary approach to the variable-centered approach. The former uses persons, animals, or objects on the basis of their combination of characteristics which can be displayed in multiway contingency tables. Configural Frequency Analysis (CFA) and log-linear modeling (LLM) are the two most prominent (and related) statistical methods. Both compare observed frequencies (foik) with expected frequencies (feik). While LLM uses primarily a model-fitting approach, CFA analyzes residuals of non-fitting models. Residuals with significantly more observed than expected frequencies (foik>feik) are called types, while residuals with significantly less observed than expected frequencies (foik<feik) are called antitypes. The R package confreq is presented and its use is demonstrated with several data examples. Results of contingency table analyses can be displayed in tables but also in graphics representing the size and type of residual. The expected frequencies represent the null hypothesis and different null hypotheses result in different expected frequencies. Different kinds of CFAs are presented: the first-order CFA based on the null hypothesis of independence, CFA with covariates, and the two-sample CFA. The calculation of the expected frequencies can be controlled through the design matrix which can be easily handled in confreq. View Full-Text
Keywords: categorical data; log linear modeling; Configural Frequency Analysis (CFA); multivariate analysis; nonparametric methods categorical data; log linear modeling; Configural Frequency Analysis (CFA); multivariate analysis; nonparametric methods
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MDPI and ACS Style

Heine, J.-H.; Stemmler, M. Analysis of Categorical Data with the R Package confreq. Psych 2021, 3, 522-541. https://doi.org/10.3390/psych3030034

AMA Style

Heine J-H, Stemmler M. Analysis of Categorical Data with the R Package confreq. Psych. 2021; 3(3):522-541. https://doi.org/10.3390/psych3030034

Chicago/Turabian Style

Heine, Jörg-Henrik, and Mark Stemmler. 2021. "Analysis of Categorical Data with the R Package confreq" Psych 3, no. 3: 522-541. https://doi.org/10.3390/psych3030034

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