Changes in version 0.2.9.7 (2026-02-17) - lme4 tidying with profile CIs now respects scale = "vcov" (GH #161, @richmaparker) - added glance method for TMB objects - changes for compatibility with lme4 >= 2.0.0 Changes in version 0.2.9.6 (2024-10-15) - CRAN maintenance release - stanreg tidiers should work for models without random effects Changes in version 0.2.9.5 (2024-04-01) NEW FEATURES - stanreg tidier gains exponentiate argument (wish of GH #122) - tidy.brmsfit gains optional rhat and ess columns (Alexey Stukalov) - experimental support for lqmm models (David Luke Thiessen) BUG FIXES - bug fixed for 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) USER-VISIBLE CHANGES - as.data.frame.ranef.lme now processes the optional argument (see ?as.data.frame), so that data.frame(ranef_object) works - stanreg tidier now checks for spurious values in ... Changes in version 0.2.9.4 (2022-04-17) - minor changes only; test tweaks for CRAN compatibility Changes in version 0.2.9.3 (2022-03-28) BUG FIXES - improved profile robustness in TMB tidiers NEW FEATURES - 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 USER-VISIBLE CHANGES - improved lme tidying for random effects values - brms tidiers no longer use deprecated posterior_samples - glance.lme4 now returns nobs (Cory Brunson) - some tidiers are less permissive about unused arguments passed via ... Changes in version 0.2.7 (2021-07-07) NEW FEATURES - experimental TMB tidiers (the TMB package does not return an object of class TMB, so users should run class(fit) <- "TMB" before tidying) USER-VISIBLE CHANGES - 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) BUG FIXES - Wald confidence intervals for lmerTest models now respect ddf.method - tidy.glmmTMB(.,effects="ran_vals") fixed for stringsAsFactors changes in glmmTMB (GH #103) - tidy.gamlss now works in a wider range of cases (GH #74) - tidy.brmsfit works for models without group effects (GH #100) Changes in version 0.2.6 (2020-05-17) - No improvements; compatibility with dplyr 1.0.0; skip examples Changes in version 0.2.5 (2020-04-19) NEW FEATURES - lmer tidier gets ddf.method (applies only to lmerTest fits) - glmmTMB gets exponentiate options - experimental GLMMadaptive tidiers OTHER CHANGES - fixes for updates in tibble package Changes in version 0.2.4 (2019-02-21) NEW FEATURES - gls tidier gets confint (GH #49) USER-VISIBLE CHANGES - redundant estimate.method in MCMC tidiers goes away; use robust to compute point estimates/uncertainty via median and MAD rather than mean and SE BUG FIXES - misc fixes: lme4 tidiers (confint for ran_vals, profile conf intervals fixed), R2jags, gamlss ... - ran_vals works for glmmTMB Changes in version 0.2.3 (2018-10-21) BUG FIXES - 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) NEW FEATURES - brmsfit and rstanarm methods allow conf.method="HPDinterval" USER-VISIBLE CHANGES - 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 Changes in version 0.2.2 (2018-09-20) - modify examples, for CRAN compliance Changes in version 0.2.1 - reduced size of stored fits for examples, for CRAN compliance Changes in version 0.2.0 NEW FEATURES - more consistent term names in brmsfit, rstanreg tidiers - improved tidy.MCMCglmm USER-VISIBLE CHANGES - 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) Changes in version 0.0.1 BUG FIXES - Sorted out some of the confusion over random effect naming: "ran_vals" extracts conditional modes/BLUPs/varying parameters (deviations from population-level estimates), while "ran_coefs" extracts group-level estimates NEW FEATURES - improved 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" USER-VISIBLE CHANGES - The default behaviour of most mixed-model tidiers has changed/will gradually be changed to the following (description modified from TJ Mahr at https://github.com/tidymodels/broom/issues/96): - Random effect variances and covariances can now be extracted. effects = "ran_pars" returns the standard deviations/correlations of random effects (if scales="sdcor" [default]) or their variances and covariances (if scales = "varcov") - Random effects estimates are now extracted with 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. - term names for random-effect parameters no longer contain a (redundant) group specifier (at least for lme4 models); use something like tidyr::unite(term,term,group,sep=".") to collapse the two columns