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CHANGES IN broom.mixed VERSION 0.2.9.6

  • CRAN maintenance release
  • stanreg tidiers should work for models without random effects

CHANGES IN broom.mixed VERSION 0.2.9.5

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 broom.mixed VERSION 0.2.9.4 (2022-03-28)

  • minor changes only; test tweaks for CRAN compatibility

CHANGES IN broom.mixed VERSION 0.2.9.3 (2021-07-07)

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 broom.mixed 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 broom.mixed VERSION 0.2.6 (2020-05-17)

  • No improvements; compatibility with dplyr 1.0.0; skip examples

CHANGES IN broom.mixed 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 broom.mixed VERSION 0.2.4

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 broom.mixed VERSION 0.2.3

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 broom.mixed VERSION 0.2.2

  • modify examples, for CRAN compliance

CHANGES IN broom.mixed VERSION 0.2.1

  • reduced size of stored fits for examples, for CRAN compliance

CHANGES IN broom.mixed 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 broom.mixed 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 tidymodels/broom#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