Goodness-of-fit Test for Latent Class Rgression Model

• Main Authors: Hui-Yi Kao, 高徽宜
• Other Authors: Guan-Hua Huang
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/86786850641580404603

碩士 === 國立交通大學 === 統計學研究所 === 93 === Biomedical and psychosocial researchers increasingly utilize latent class regression (LCR) models to analyze relationships between measured multiple categorical outcomes and covariates of interest. In LCR, the multiple outcomes are summarized and their associations with risk factors are determined in a single modeling step. These models are parsimonious and can incorporate theory underlying the multiple response choices. However, these advantages come at the price of strong modeling assumptions which may critically influence analytic findings. Careful evaluation of model appropriateness is necessary. In this thesis, we first introduced Hosmer-Lemeshow statistic for multiple logistic regression model and then extended the method to LCR model to assess overall fit of the LCR model. An analysis of how measured health impairments affect older persons' functioning is used for illustration. KEY WORDS: categorical data; goodness-of-fit test; latent class regression; chi-square distribution.