Table 3.
Comparisons of Hypothesis Testing Aspects
| Software Procedure (Version) | Alternative Methods for Computing Approximate DF | Bayesian Inference Methods | Appropriate Hypothesis Tests for Variance Components |
|---|---|---|---|
| HLM (7) | √ | ||
| MIXREG (1.2) | |||
| MLwiN (2.22) | √ | √ | |
| Mplus (6.1) | √ | ||
| R (2.12.2): lme() | 1 | 2 | |
| R (2.12.2): lmer() | 1 | 2 | |
| R (2.12.2): hglm() | |||
| SAS (9.2): PROC MIXED | √ | √ | |
| SAS (9.2): PROC GLIMMIX | √ | 3 | |
| SAS (9.2): PROC HPMIXED | |||
| SPSS (20): MIXED / GENLINMIXED | √ | ||
| Stata (12): gllamm | |||
| Stata (12): xtmixed | 4 | ||
| Statistica (10) | |||
| SYSTAT (13) | |||
| WinBUGS (1.4.3) | √ |
1
With mcmcsamp() in the lme4 package, or pvals.func() in the languageR package.
2
With exactLRT() in the RLRsim package.
3
A mixture of central Chi-square distributions is used to compute the p-values for the likelihood ratio test for several recognized special cases.
4
For tests of single variance components.