Titlebook: Linear Mixed Models for Longitudinal Data; Geert Molenberghs,Geert Verbeke Book 2000 Springer-Verlag New York 2000 Fitting.Linear Mixed Mo

cardiac-arrest

Inference for the Random Effects,and the variance components in . and in all ∑.), it is often useful to calculate estimates for the random effects . as well, since they reflect how much the subject-specific profiles deviate from the overall average profile. Such estimates can then be interpreted as residuals which may be helpful fo

傲慢物

Palpate

Local Influence for the Linear Mixed Model,ensitive to peculiar observations. The data analyst should be aware of particular observations that have an unusually large influence on the results of the analysis. Such cases may be found to be completely appropriate and retained in the analysis, or they may represent inappropriate data and may be

Negligible

The Heterogeneity Model,sarily normally distributed. Their so-called heterogeneity model assumes the random effects to be sampled from a mixture of normal distributions rather than from just one single normal distribution. This not only extends the assumption about the random-effects distribution to a very broad class of d

MAIM

帶子

Exploring Incomplete Data,vel standpoint (Figures 4.1 and 4.5) as well as from the population-averaged or group-averaged perspective (Figures 4.2, 4.3, 4.4, and 10.3). These plots are designed to focus on various structural aspects, such as the mean structure, the variance function, and the association structure..An extra le

CORE

Pattern-Mixture Models,tle is often known, has been extensively documented. See also Sections 15.3, 15.4, 17.1, 17.2.2, and 17.5. This has lead to growing interest in pattern-mixture modeling, based on the factorization (15.2) (Little 1993, Glynn, Laird and Rubin 1986, Hogan and Laird 1997). After initial mention of patte

Frenetic

Sensitivity Analysis for Selection Models, specific challenges related to sensitivity to modeling assumptions. Even when the linear mixed model would beyond any doubt be the choice of preference to describe the measurement process ., then the analysis of the actually observed, incomplete version is subject still to further untestable modeli

未成熟

ANTI