NEWS.md
stanreg tidier gains exponentiate argument (wish of GH #122)tidy.brmsfit gains optional rhat and ess columns (Alexey Stukalov)lqmm models (David Luke Thiessen)glmmTMB tidying with conf.int=TRUE, random effects in multiple model components, subset of components requested in tidy output (GH #136, Daniel Sjoberg)tidy.brmsfit works better for models with no random/group-level effects (Matthieu Bruneaux)lme tidier gets functionality for information about variance models (use effects = "var_model") (Bill Denney)
support for models with fixed sigma values in lme tidier (Bill Denney)
added tidy and glance methods for allFit objects from the lme4 package
get_methods() function returns a table of all available tidy/glance/augment methods
TMB tidiers (the TMB package does not return an object of class TMB, so users should run class(fit) <- "TMB" before tidying)term names are no longer “sanitized” in gamlss tidiers (e.g. “(Intercept)” is not converted to “X.Intercept.”)
gamlss glance method returns nobs (GH #113)
dplyr 1.0.0; skip examplesgls tidier gets confint (GH #49)don’t ignore conf.level in tidy.(merMod|glmmTMB) (GH #30,31: @strengejacke)
levels correct in tidy.brmsfit (GH #36: @strengejacke)
component argument works for random effects in glmmTMB (GH #33: @strengejacke)
tidy.brmsfit gets component column (GH #35: @strengejacke), response column for multi-response models (GH #34: @strengejacke)
component tags are stripped from tidied brmsfit objects
“Intercept” terms in brms fits are re-coded as “(Intercept)” by default, for dotwhisker/cross-model compatibility; for previous behaviour, specify fix.intercept=FALSE
all methods return tibbles (tbl_df) rather than data frames
the value of the group variable for fixed-effect parameters has changed from "fixed" to NA
brmsfit and rstanarm tidiers are more consistent with other tidiers (e.g. the argument for setting confidence level is conf.level rather than prob)
"ran_vals" extracts conditional modes/BLUPs/varying parameters (deviations from population-level estimates), while "ran_coefs" extracts group-level estimatesimproved nlme tidiers
improved glmmTMB tidiers (can handle some zero-inflation parameters)
lme4 tidiers now optionally take a pre-computed profile argument when using conf.method="profile"
scales="sdcor" [default]) or their variances and covariances (if scales = "varcov")effects = "ran_coefs" for the group-level estimates (previously these effects were extracted with tidy(model, "random")) or effects = "ran_vals" for the conditional modes (deviations of the group-level parameters from the population-level estimates)effects can take a vector of values (those listed above, plus “fixed” for fixed effects). The default value is effects = c(“ran_pars”, “fixed”) which extracts random effect variances/covariances and fixed effect estimates.group specifier (at least for lme4 models); use something like tidyr::unite(term,term,group,sep=".") to collapse the two columns