Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Latent Class Analysis of Respondent Scalability

Latent Class Analysis of Respondent Scalability The psychometric literature contains many indices to detect aberrant respondents. A different, promising approach is using ordered latent class analysis with the goal to distinguish latent classes of respondents that are scalable, from latent classes of respondents that are not scalable (i.e., aberrant) according to the scaling model adopted. This article examines seven Latent Class models for a cumulative scale. A simulation study was performed to study the efficacy of different models for data that follow the scale model perfectly. A second simulation study was performed to study how well these models detect aberrant respondents. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Latent Class Analysis of Respondent Scalability

Quality & Quantity , Volume 34 (2) – Oct 16, 2004

Loading next page...
 
/lp/springer_journal/latent-class-analysis-of-respondent-scalability-1oy4PKfaJt

References (39)

Publisher
Springer Journals
Copyright
Copyright © 2000 by Kluwer Academic Publishers
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
DOI
10.1023/A:1004775921860
Publisher site
See Article on Publisher Site

Abstract

The psychometric literature contains many indices to detect aberrant respondents. A different, promising approach is using ordered latent class analysis with the goal to distinguish latent classes of respondents that are scalable, from latent classes of respondents that are not scalable (i.e., aberrant) according to the scaling model adopted. This article examines seven Latent Class models for a cumulative scale. A simulation study was performed to study the efficacy of different models for data that follow the scale model perfectly. A second simulation study was performed to study how well these models detect aberrant respondents.

Journal

Quality & QuantitySpringer Journals

Published: Oct 16, 2004

There are no references for this article.