R Under development (unstable) (2025-07-27 r88459 ucrt) -- "Unsuffered Consequences"
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> regression.tests <- FALSE
> 
> if (regression.tests && require("carData") && require("effects")){
+ 
+   load("regression-tests.RData")
+   
+   regressionTest <- function(old, new){
+     test.name <- deparse(substitute(new))
+     if (!isTRUE(all.equal(old, as.data.frame(new), tolerance=1e-5))) {
+       stop("failed regression test ", test.name)
+     } else {
+       cat("\n", test.name, ": OK", sep="")
+     }
+   }
+   
+   m.lm <- lm(prestige~(income + education)*type, data=Duncan)
+   eff.lm <- Effect(c("income", "type"), m.lm)
+   regressionTest(df.lm, eff.lm)
+   
+   m.glm <- glm(volunteer ~ sex + neuroticism*extraversion, data=Cowles, family=binomial)
+   eff.glm <- Effect(c("neuroticism", "extraversion"), m.glm)
+   regressionTest(df.glm, eff.glm)
+   
+   m.mlm <- lm(cbind(post.test.1, post.test.2, post.test.3) ~ 
+                 group*(pretest.1 + pretest.2), data = Baumann)
+   eff.mlm <- Effect(c("group", "pretest.1"), m.mlm)
+   regressionTest(df.mlm, eff.mlm)
+   
+   if (require(nnet)){
+     m.multinom <- multinom(vote ~ age + gender + economic.cond.national +
+                            economic.cond.household + Blair + Hague + Kennedy +
+                            Europe*political.knowledge, data=BEPS)
+     
+     eff.multinom <- Effect(c("Europe", "political.knowledge"), m.multinom,
+                 xlevels=list(political.knowledge=0:3))
+     regressionTest(df.multinom, eff.multinom)
+   }
+   
+   if (require(MASS)){
+     m.polr <- polr(poverty ~ gender + religion + degree + country*poly(age,3),
+                     data=WVS)
+     
+     eff.polr <- Effect(c("country", "age"), m.polr)
+     regressionTest(df.polr, eff.polr)
+   }
+   
+   if (require(nlme)){
+     m.lme <- lme(distance ~ age*Sex, data = Orthodont, random = ~ 1)
+     eff.lme <- Effect(c("age", "Sex"), m.lme)
+     m.gls <- gls(Employed ~ GNP*Population,
+         correlation=corAR1(form= ~ Year), data=longley)
+     eff.gls <- Effect(c("GNP", "Population"), m.gls)
+     regressionTest(df.gls, eff.gls)
+   }
+   
+   if (require(lme4) && require(nlme)){
+      data("Orthodont", package="nlme")
+      m.lmer <- lmer(distance ~ age*Sex + (1 |Subject), data = Orthodont)
+      eff.lmer <- Effect(c("age", "Sex"), m.lmer)
+      regressionTest(df.lmer, eff.lmer)
+   }
+   
+   if (require(lme4)){
+     m.glmer <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
+                 data = cbpp, family = binomial)
+     eff.glmer <- Effect("period", m.glmer)
+     regressionTest(df.glmer, eff.glmer)
+   }
+   
+   if (require(lme4) && require(robustlmm)){
+       m.rlmer <- rlmer(distance ~ age*Sex + (1 |Subject), data = Orthodont)
+       eff.rlmer <- Effect(c("age", "Sex"), m.rlmer)
+       regressionTest(df.rlmer, eff.rlmer)
+   }
+   
+   if (require(betareg) && require(lme4)){
+      data("GasolineYield", package = "betareg")
+      m.betareg <- betareg(yield ~ batch*temp, data = GasolineYield)
+      eff.betareg <- Effect(c("batch", "temp"), m.betareg)
+      regressionTest(df.betareg, eff.betareg)
+   }
+   
+   if (require(ordinal) && require(MASS)){
+     m.clm <- clm(poverty ~ gender + religion + degree + country*poly(age,3),
+         data=WVS)
+     eff.clm <- Effect(c("country", "age"), m.clm)
+     regressionTest(df.clm, eff.clm)
+     
+     m.clm2 <- clm2(poverty ~ gender + religion + degree + country*poly(age,3),
+                  data=WVS)
+     eff.clm2 <- Effect(c("country", "age"), m.clm2)
+     regressionTest(df.clm2, eff.clm2)
+     
+     m.clmm <- clmm(SURENESS ~ PROD + (1|RESP) + (1|RESP:PROD), 
+                 data = soup, link = "logit", threshold = "flexible")
+     eff.clmm <- Effect("PROD", m.clmm)
+     regressionTest(df.clmm, eff.clmm)
+   }
+   
+   if (require(poLCA)){
+     set.seed(123)
+     data(election, package="poLCA")
+     f <- cbind(MORALG,CARESG,KNOWG,LEADG,DISHONG,INTELG,
+                MORALB,CARESB,KNOWB,LEADB,DISHONB,INTELB)~PARTY
+     m.poLCA <- poLCA(f, election, nclass=3, nrep=5)
+     eff.poLCA <- Effect("PARTY", m.poLCA)
+     regressionTest(df.poLCA, eff.poLCA)
+   }
+   
+   if (require(survey)){
+     data(api, package="survey")
+     dstrat <-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)
+     m.svyglm <- svyglm(api00~ell*meals+mobility, design=dstrat)
+     eff.svyglm <- Effect(c("ell", "meals"), m.svyglm)
+     regressionTest(df.svyglm, eff.svyglm)
+   }
+   
+   if(require(nlme) && require(MASS)){
+     m.glmmPQL <- glmmPQL(y ~ trt*I(week > 2), random = ~ 1 | ID,
+                     family = binomial, data = bacteria)
+     eff.glmmPQL <- Effect(c("trt", "week"), m.glmmPQL)
+     regressionTest(df.glmmPQL, eff.glmmPQL)
+   }
+ 
+ }
> 
> # the following commented-out code creates the comparison objects:
> #
> # df.betareg <- as.data.frame(eff.betareg )
> # df.clm <- as.data.frame(eff.clm) 
> # df.clm2 <- as.data.frame(eff.clm2)
> # df.clmm <- as.data.frame(eff.clmm) 
> # df.glm <- as.data.frame(eff.glm) 
> # df.glmer <- as.data.frame(eff.glmer) 
> # df.gls <- as.data.frame(eff.gls) 
> # df.lm <- as.data.frame(eff.lm) 
> # df.lme <- as.data.frame(eff.lme) 
> # df.lmer <- as.data.frame(eff.lmer) 
> # df.mlm <- as.data.frame(eff.mlm) 
> # df.multinom <- as.data.frame(eff.multinom) 
> # df.poLCA <- as.data.frame(eff.poLCA) 
> # df.polr <- as.data.frame(eff.polr) 
> # df.rlmer <- as.data.frame(eff.rlmer) 
> # df.svyglm <- as.data.frame(eff.svyglm)
> # df.glmmPQL <- as.data.frame(eff.glmmPQL)
> # 
> # 
> # save(df.betareg, df.clm, df.clm2, df.clmm, df.glm,
> #      df.glmer, df.gls, df.lm, df.lme, df.lmer, df.mlm,
> #      df.multinom, df.poLCA, df.polr, df.rlmer, df.svyglm,
> #      df.glmmPQL,
> #      file="regression-tests.RData")
> 
> # To add to regression tests first
> # load("regression-tests.RData")
> 
> proc.time()
   user  system elapsed 
   0.10    0.07    0.15