36  Supported Models

marginaleffects effects supports 102 model types directly, and dozens more via the tidymodels and mlr3 frameworks. This table shows the list of directly supported model types. There are three main alternative software packages to compute such slopes (1) Stata’s margins command, (2) R’s margins::margins() function, and (3) R’s emmeans::emtrends() function. The test suite hosted on Github compares the numerical equivalence of results produced by marginaleffects::slopes() to those produced by all 3 alternative software packages:

• ✓: a green check means that the results of at least one model are equal to a reasonable tolerance.
• ✖: a red cross means that the results are not identical; extra caution is warranted.
• U: a grey U means that computing slopes for a model type is unsupported by alternative packages, but supported by marginaleffects.
• An empty cell means means that no comparison has been made yet.

I am eager to add support for new models. Feel free to file a request or submit code on Github.

		Numerical equivalence
Supported by marginaleffects		Stata		margins		emtrends
Package	Function	dY/dX	SE	dY/dX	SE	dY/dX	SE
AER	ivreg	✓	✓	✓	✓	U	U
	tobit	✓	✓	U	U	✓	✓
DCchoice	oohbchoice
MASS	glm.nb	✓	✓	✓	✓	✓	✓
	glmmPQL			U	U	✓	✓
	polr	✓	✓	✖	✖	✓	✓
	rlm			✓	✓	✓	✓
MCMCglmm	MCMCglmm	U	U	U	U	U	U
REndo	copulaCorrection
	hetErrorsIV
	higherMomentsIV
	latentIV
	multilevelIV
Rchoice	hetprob
	ivpml
afex	afex_aov			U	U	✓	✓
aod	betabin			U	U	U	U
betareg	betareg	✓	✓	✓	✓	✓	✓
bife	bife			U	U	U	U
biglm	bigglm			U	U	U	U
	biglm			U	U	U	U
blme	bglmer
	blmer
brglm2	bracl			U	U	U	U
	brglmFit			✓	✓	✓	✓
	brmultinom			U	U	U	U
	brnb			✓	✓	U	U
brms	brm			U	U	✓	✓
crch	crch			U	U	U	U
	hxlr			U	U	U	U
estimatr	iv_robust	✓	✓	U	U	U	U
	lm_lin
	lm_robust	✓	✓	✓	U	✓	✓
fixest	feglm			U	U	U	U
	fenegbin			U	U	U	U
	feols	✓	✓	U	U	U	U
	fepois	✓	✓	U	U	U	U
flexsurv	flexsurvreg
	flexsurvspline
gam	gam			U	U	✓	✓
gamlss	gamlss			U	U	✓	✓
geepack	geeglm			U	U	✓	✓
glmmTMB	glmmTMB			U	U	✓	✓
glmtoolbox	glmgee
glmx	glmx			✓	U	U	U
ivreg	ivreg	✓	✓	✓	✓	U	U
lme4	glmer	✓	✓	✓	✓	✓	✓
	glmer.nb			✓	✓	✓	✓
	lmer	✓	✓	✓	✓	✓	✓
lmerTest	lmer			✓	✓	✓	✓
logistf	flac
	flic
	logistf
mclogit	mblogit			U	U	U	U
	mclogit			U	U	U	U
mgcv	bam			U	U	✓	✖
	gam			U	U	✓	✓
mhurdle	mhurdle			✓	✓	U	U
mlogit	mlogit			U	U	U	U
mlr3	Learner
mvgam	mvgam
nlme	gls			U	U	✓	✓
	lme
nnet	multinom	✓	✓	U	U	U	U
ordbetareg	ordbetareg			U	U
ordinal	clm	✓	✓	U	U	U	U
phylolm	phyloglm
	phylolm
plm	plm	✓	✓	✓	✓	U	U
pscl	hurdle			✓	U	✓	✖
	hurdle			✓	U	✓	✖
	zeroinfl	✓	✓	✓	U	✓	✓
quantreg	rq	✓	✓	U	U	✓	✓
rms	Gls
	lrm
	ols
	orm
robust	lmRob			U	U	U	U
robustbase	glmrob			✓	✓	U	U
	lmrob			✓	✓	U	U
robustlmm	rlmer			U	U
rstanarm	stan_glm			✖	U	✓	✓
rstpm2	aft
	gsm
	pstpm2
	stpm2
sampleSelection	heckit			U	U	U	U
	selection			U	U	U	U
scam	scam			U	U	U	U
speedglm	speedglm	✓	✓	✓	✓	U	U
	speedlm	✓	✓	✓	✓	U	U
stats	glm	✓	✓	✓	✓	✓	✓
	lm	✓	✓	✓	✓	✓	✓
	loess			✓		U	U
	nls
survey	svyglm			✓	✓	✓	✓
	svyolr
survival	clogit
	coxph	✓	✓	U	U	✓	✓
	survreg
tobit1	tobit1			✓	✓	U	U
truncreg	truncreg	✓	✓	✓	✓	U	U