期刊
PSYCHOMETRIKA
卷 68, 期 4, 页码 563-583出版社
SPRINGER
DOI: 10.1007/BF02295612
关键词
response style; ordinal regression; hierarchical regression models; probit models; Bayesian statistics
This paper proposes a general approach to accounting for individual differences in the extreme response style in statistical models for ordered response categories. This approach uses a hierarchical ordinal regression modeling framework with heterogeneous thresholds structures to account for individual differences in the response style. Markov chain Monte Carlo algorithms for Bayesian inference for models with heterogeneous thresholds structures are discussed in detail. A simulation and two examples based on ordinal probit models are given to illustrate the proposed methodology. The simulation and examples also demonstrate that failing to account lot individual differences in the extreme response style can have adverse consequences for statistical inferences.
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