# Exam5.3: Example 5.3 from Generalized Linear Mixed Models: Modern... In StroupGLMM: R Codes and Datasets for Generalized Linear Mixed Models: Modern Concepts, Methods and Applications by Walter W. Stroup

## Description

Exam5.3 Inference using empirical standard error with different Bias connection

## References

1. Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. CRC Press.

`DataSet4.1`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55``` ```data(DataSet4.1) DataSet4.1\$trt <- factor(x = DataSet4.1\$trt) DataSet4.1\$block <- factor( x = DataSet4.1\$block) ##---REML estimates on page 172 library(lme4) # library(lmerTest) Exam5.3REML <- lmer( formula = y ~ trt + (1|block) , data = DataSet4.1 , REML = TRUE # , control = lmerControl() , start = NULL # , verbose = 0L # , subset # , weights # , na.action # , offset , contrasts = NULL , devFunOnly = FALSE # , ... ) ##---Standard Error Type "Model Based" with no Bias Connection AnovaExam5.3REML <- anova( object = Exam5.3REML ) AnovaExam5.3REML ##---Standard Error Type "Model Based" with "Kenward-Roger approximation" Bias Connection # library(pbkrtest) anova( object = Exam5.3REML, ddf = "Kenward-Roger") ##---ML estimates on page 172 Exam5.3ML <- lmer( formula = y ~ trt + ( 1|block ) , data = DataSet4.1 , REML = FALSE # , control = lmerControl() , start = NULL # , verbose = 0L # , subset # , weights # , na.action # , offset , contrasts = NULL , devFunOnly = FALSE # , ... ) ##---Standard Error Type "Model Based" with no Bias Connection AnovaExam5.3ML <- anova( object = Exam5.3ML ) AnovaExam5.3ML ##---Standard Error Type "Model Based" with "Kenward-Roger approximation" Bias Connection anova( object = Exam5.3ML, ddf = "Kenward-Roger") ```