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Full-Text Articles in Physical Sciences and Mathematics
When Should Random Effects Be Included In Estimable Functions And When They Should Not?, David C. Blouin
When Should Random Effects Be Included In Estimable Functions And When They Should Not?, David C. Blouin
Conference on Applied Statistics in Agriculture
In the mixed model, the behavior of linear functions of the fixed and random effects is examined. It is found that inclusion of certain functions of random effects can lead to estimators which are equivalent to those under a fixed effects model and are inconsistent with the inherent structure of the mixed model. Three examples are presented which illustrate the behavior of linear functions of the fixed and random effects. These functions represent the broad, narrow and intermediate inference spaces as introduced by McLean, Sanders and Stroup (1991). Which random effects should be included in the model is discussed. Random …
Analyzing Split-Plot Andrepeated-Measures Designsusing Mixed Models, Russ Wolfinger, Nancy Miles-Mcdermott, Jenny Kendall
Analyzing Split-Plot Andrepeated-Measures Designsusing Mixed Models, Russ Wolfinger, Nancy Miles-Mcdermott, Jenny Kendall
Conference on Applied Statistics in Agriculture
We first introduce the general linear mixed model and provide a justification for using REML to fit it. Then, for an irrigation example, we present several mixed models of increasing complexity. The initial model corresponds to a typical split-plot analysis. Next, we present covariance structures that directly describe the variability of repeated measures within whole plots. Finally, we combine the above types into more complicated mixed models, and compare them using likelihood-based criteria.