{"title":"混合分类和生存反应的潜在变量模型,应用于孟加拉国的生育偏好和计划生育","authors":"I. Moustaki, F. Steele","doi":"10.1191/1471082X05st100oa","DOIUrl":null,"url":null,"abstract":"In this article, we discuss a latent variable model with continuous latent variables for manifest variables that are a mixture of categorical and survival outcomes. Models for censored and uncensored survival data are discussed. The model allows for covariate effects both on the manifest variables (direct effects) and on the latent variable(s) (indirect effects). The methodological developments are motivated by a demographic application: an exploration of women’s fertility preferences and family planning behaviour in Bangladesh.","PeriodicalId":354759,"journal":{"name":"Statistical Modeling","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Latent variable models for mixed categorical and survival responses, with an application to fertility preferences and family planning in Bangladesh\",\"authors\":\"I. Moustaki, F. Steele\",\"doi\":\"10.1191/1471082X05st100oa\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, we discuss a latent variable model with continuous latent variables for manifest variables that are a mixture of categorical and survival outcomes. Models for censored and uncensored survival data are discussed. The model allows for covariate effects both on the manifest variables (direct effects) and on the latent variable(s) (indirect effects). The methodological developments are motivated by a demographic application: an exploration of women’s fertility preferences and family planning behaviour in Bangladesh.\",\"PeriodicalId\":354759,\"journal\":{\"name\":\"Statistical Modeling\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistical Modeling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1191/1471082X05st100oa\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1191/1471082X05st100oa","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Latent variable models for mixed categorical and survival responses, with an application to fertility preferences and family planning in Bangladesh
In this article, we discuss a latent variable model with continuous latent variables for manifest variables that are a mixture of categorical and survival outcomes. Models for censored and uncensored survival data are discussed. The model allows for covariate effects both on the manifest variables (direct effects) and on the latent variable(s) (indirect effects). The methodological developments are motivated by a demographic application: an exploration of women’s fertility preferences and family planning behaviour in Bangladesh.