EFFECTS OF MISSPECIFICATION IN LONGITUDINAL MODELS

描述（申请人摘要）：本提案的目的是 统计分析方法的开发、评价和应用 纵向数据，重点是观察性随访研究， 流行病学和其他健康相关研究。具体重点是 现实地模拟各种偏离的假设， 模型，评估效果，考虑新的估计技术，是强大的 可能的错误说明，并制定检测方法 错误说明需要考虑的错误规范是省略的混杂因素， 测量误差和信息缺失数据。将特别注意 这些之间的关系，并将介绍一个统一的框架 只要有可能 拟议的工作包括： - 具有潜在随机效应的拟合模型， 错误规格 - 开发简单的方法来拟合信息丰富的缺失数据的模型 - 测量误差问题的半参数随机效应模型 - 对混杂因素的影响进行全面调查， 广义线性模型，以及 - 基于GEE的伪得分检验方法的建立 该方法可应用于大量的纵断面分析 关于睡眠障碍、糖尿病、老年人福尔斯跌倒、新生儿肺 老年人中的疾病和眼病。

DESCRIPTION (Applicant's abstract): The aims of this proposal are the development, evaluation and application of methods for the statistical analysis of longitudinal data, with emphasis on observational follow-up studies in epidemiologic and other health related research. The specific focus is to realistically model various departures from the assumptions of commonly applied models, evaluate the effect, consider new estimation techniques that are robust to the possible misspecification and develop methods for detecting the misspecification. Misspecifications to be considered are omitted confounders, measurement error and informative missing data. Special attention will be paid to the relationships between these, and a unified framework will be introduced whenever possible. The proposed work includes: - Fitting models with latent random effects geared to capture possible misspecifications - Developing simple methods for fitting models for informative missing data - Adapting semiparametric random effects models for measurement error problems - Undertaking a comprehensive investigation of the effect of confounding in generalized linear models, and - Developing of a pseudo score test to detect misspecification with GEE The methods will be applied in the analysis of large amounts of longitudinal data on sleep disorders, diabetes, falls among the elderly, neonatal lung disease and eye disease in an aging population.