EFFECTS OF MISSPECIFICATION IN LONGITUDINAL MODELS

说明(申请人摘要)：本提案的目的是 统计分析方法的发展、评价和应用 的纵向数据，重点是观察跟踪研究 流行病学和其他与健康相关的研究。具体的重点是 现实地模拟各种偏离常用假设的情况 模型，评估效果，考虑稳健的新估计技术 可能的错误规范并开发方法来检测 说明有误。要考虑的错误规范是省略的混杂因素， 测量误差和信息性缺失数据。我们会特别注意 对这些之间的关系，将会有一个统一的框架出台 只要有可能。 拟开展的工作包括： -适合潜在随机效应的模型，以捕捉可能的 规格错误 -开发用于拟合信息性缺失数据的模型的简单方法 -适用于测量误差问题的半参数随机效应模型 -对混杂的影响进行全面调查 广义线性模型，以及 -开发伪分数测试，以检测GEE的错误说明 这些方法将被应用于大型纵向结构的分析。 关于睡眠障碍、糖尿病、老年人跌倒、新生儿肺的数据 老龄化人口中的疾病和眼疾。

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.