## Residuals and Outliers in Repeated Measures Random Effects Models (1995)

Venue: | Expected Total |

Citations: | 5 - 0 self |

### BibTeX

@TECHREPORT{Weiss95residualsand,

author = {Robert E. Weiss},

title = {Residuals and Outliers in Repeated Measures Random Effects Models},

institution = {Expected Total},

year = {1995}

}

### OpenURL

### Abstract

An approach for developing Bayesian outlier and goodness of fit statistics is presented for the linear model and extended to a hierarchical random effects model for repeated measures data. Diagnostics for univariate outliers, missing covariates, multivariate outliers and global goodness of fit are developed. Distribution theory for the posterior of the residuals is worked out. A local approach is used to show how omitted covariates and fixed and random effects affect residual summaries. Standard plots are interpreted in light of these understandings. Key Words: Bayesian Data Analysis, Goodness-of-Fit, Hierarchical Models, Longitudinal Data, Outlier, Philosophy of Statistics, Shrinkage. 1 Introduction. This paper develops a Bayesian approach to residual analysis and extends the approach to the random effects model (REM) used to model repeated Robert E. Weiss is Assistant Professor, Department of Biostatistics, Box 177220; UCLA School of Public Health; Los Angeles CA 90095-1772 U.S....