HLR

Dimitrios Zacharatos

2025-02-12

This shows the output of HLR function from workingfunctions.
Installation instructions of workingfunctions can be found here https://github.com/sedzinfo/workingfunctions

Report HLR

result<-report_hlr(df=infert,corlist=8,factorlist=1,predictor="case",random_effect="case")
result
##               dv                      model                 fixed       random                                                                                                call Model df      AIC      BIC    logLik   Test      L.Ratio   p.value
## 1 pooled.stratum                       base    pooled.stratum ~ 1         <NA>                                   nlme::gls(model = formula(fbaseline), data = temp, method = "ML")     1  2 2119.941 2126.968 -1057.971                  NA        NA
## 2 pooled.stratum           random_intercept    pooled.stratum ~ 1    ~1 | case lme.formula(fixed = formula(fbaseline), data = temp, random = frandom_intercept,     method = "ML")     2  3 2121.941 2132.482 -1057.971 1 vs 2 3.060691e-07 0.9995586
## 3 pooled.stratum random_intercept_predictor pooled.stratum ~ case    ~1 | case         lme.formula(fixed = fpredictor, data = temp, random = frandom_intercept,     method = "ML")     3  4 2123.936 2137.989 -1057.968 2 vs 3 5.861154e-03 0.9389750
## 4 pooled.stratum     random_intercept_slope pooled.stratum ~ case ~case | case             lme.formula(fixed = fpredictor, data = temp, random = frandom_slope,     method = "ML")     4  6 2127.936 2149.016 -1057.968 3 vs 4 4.047206e-08 1.0000000