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Log-Linear Modeling, Latent Class Analysis, or Correspondence Analysis Which Method Should Be Used for the Analysis of Categorical Data?

B. S. Everiti, +1 more
TLDR
The analysis of such data should clearly depend on the substantive questions posed by the researcher involved, although in many cases these questions will be rather vague as mentioned in this paper, and it will often be left to the statistician to clarify what is meant by such concepts and whether they are present in the investigator's data.
Abstract
Data collected by social and behavioral scientists very often consist of large multidimensional tables of subjects cross-classified according to the values or states of several categorical variables. For example, Table 1 shows a set of data on suicide victims in which the method of committing suicide is cross-classified by sex and age group (Van der Heijden & de Leeuw, 1985) and Table 2 shows counts of subjects resulting from a survey of the political attitudes of a sample from the British electorate (Butler & Stokes, 1974). The analysis of such data should clearly depend on the substantive questions posed by the researcher involved, although in many cases these questions will be rather vague. The research worker may be interested in such notions as “pattern” and “structure” but it will often be left to the statistician to clarify what is meant by such concepts and whether they are present in the investigator’s data. Finally, the statistician has the often difficult task of explaining the results.

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Citations
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Journal ArticleDOI

Latent class analysis in medical research.

TL;DR: Different variants of latent class analysis (LCA) for dichotomous data are described in the following: the basic (unconstrained) model, models with parameters fixed to given values and with equality constraints on parameters, multigroup LCA including mixed-group vali dation, and linear logistic LCAincluding its relationship to the Rasch model and to the measurement of change in latent subgroups.
Journal ArticleDOI

Modeling Relations among Discrete Developmental Processes: A General Approach to Associative Latent Transition Analysis

TL;DR: A flexible approach to modeling relations in development among two or more discrete, multidimensional latent variables based on the general framework of loglinear modeling with latent variables called associative latent transition analysis (ALTA).
Journal ArticleDOI

Screening for common mental disorders using the SRQ-20 in Brazil: what are the alternative strategies for analysis?

TL;DR: The SRQ-20 cutoff point seems to underestimate the magnitude of CMD among women, and the alternative methods of analysis presented herein highlight the different possibilities of using this important instrument of screening for mental health.
Book ChapterDOI

Korrespondenzanalytische Standortstypisierung der alten Bundesländer

Lutz Vetter
TL;DR: In this article, the authors discuss the Entwicklung und Anwendung neuer statistischer Methoden gilt in diesem Zusammenhang als ein wichtiger Arbeitsschwerpunkt.
References
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Journal ArticleDOI

Exploratory data analysis

F. N. David, +1 more
- 01 Dec 1977 - 
Journal ArticleDOI

Exploratory Data Analysis.

Book

Discrete multivariate analysis: theory and practice

TL;DR: Discrete Multivariate Analysis is a comprehensive text and general reference on the analysis of discrete multivariate data, particularly in the form of multidimensional tables, and contains a wealth of material on important topics.
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