Development in methodology on longitudinal data is fast. Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on cor
longitudinal studiesMcNemar's testpaired Student's t-testPoisson distributionFirst page of articledoi:10.1111/1467-9884.t01-21-00356Rigby, Alan S.University of SheffieldJohn Wiley & Sons, Ltd.Journal of the Royal Statistical Society: Series D (The Statistician)...
Introduces a series of articles dealing with statistical analysis of longitudinal data. Nonstandard method for estimating a linear growth model in LISREL; Analysis of categorical longitudinal data; Measurement of change.doi:10.1080/016502598384216
The versatility of multi-state models for the analysis of longitudinal data with unobservable features Multi-state models provide a convenient statistical framework for a wide variety of medical applications characterized by multiple events and longitudinal ... VT Farewell,BDM Tom - 《Lifetime Data A...
over time should be done with great caution: a comparison between methods. Journal of clinical ...
Multivariate Applications Series(共27册),这套丛书还有 《Longitudinal Analysis》《Structural Equation Modeling with Mplus》《Structural Equation Modeling With Lisrel, Prelis, and Simplis》《Handbook of Ethics in Quantitative Methodology》《》等。 我来说两句 短评 ··· 热门 还没人写过短评呢 我要...
面板数据处理方法lecture 1 statistical methods for the analysis of longitudinal data.ppt,Lecture 1 (Chapter 1) Introduction This course describes statistical methods for the analysis of longitudinal data, with a strong emphasis on applications in the biol
Longitudinal Data Analysis involves using analytic techniques to study data collected from the same units over multiple time points, aiming to understand patterns and relationships of change within individuals over time. AI generated definition based on: International Encyclopedia of the Social & Behavioral...
(covariates) that are associated with an outcome value. General linear mixed effect models are the standard workhorse for statistical analysis of longitudinal data. However, analysis of longitudinal data can be complicated for reasons such as difficulties in modelling correlated outcome values, functional...
We consider the penalized generalized estimating equations for analyzing longitudinal data with high-dimensional covariates which often arise in microarray experiments and large-scale health studies. Existing high-dimensional regression procedures often assume independent data and rely on the likelihood function...