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@jacob-long jacob-long released this 25 Aug 13:12
· 1 commit to master since this release

Bug fixes:

  • predict_merMod() was miscalculating predictions under a specific set of
    conditions: When the model was fit with lme4::glmer(), the link was not
    identity, standard errors were simultaneously being calculated, and the
    user included random effects. This error has been corrected
    (#144)
  • When printing summ.glm() results with knitr, the p value for the
    omnibus chi-squared test is now included in the model statistics, like it
    already is when using the function in the console. (#138
  • effect_plot() no longer fails with an error when models weights are
    specified without a variable name.
    (#156)

Enhancements:

  • summ() will now produce model fit statistics for glm.nb models
    (#142).
  • effect_plot() now includes the argument facet.by. If you want to plot
    your prediction variable at multiple values of some other variable, you can
    pass the name of that variable to facet.by. It will, by default, create a
    separate plot for each unique level of that variable using
    ggplot2::facet_wrap(). If you only want specific levels of the facet.by
    variable, you can specify them by giving a vector of values to the at argument.
    More than most kinds of plots, you may need to do some further customization
    to the results of effect_plot() since the plots may not fit the space well,
    or you may want to rearrange into different row/column configurations, etc. I
    expect this to be most useful for cases when you have a multilevel model and
    there is a random slope specified for the pred variable. A version of this
    feature was requested by Github user 5tokesy (#147).
  • plot_coefs() now handles fixest_multi objects from the fixest package
    out of the box. (#123)
  • The omit.coefs and coefs arguments to plot_coefs() can now be modified
    using the new argument, coefs.match. You may use regular expressions to more
    efficiently match coefficient names, which will be most useful when you have
    models with many coefficients with predictable naming schemes. To have your
    arguments interepreted this way, set coefs.match = "regex".
    (#122)

Other changes:

  • Removed tidy.glht() method because the broom package now implements one.
    (#139)
  • Made broom and broom.mixed hard dependencies to help avoid user confusion
    and a few errors that could occur when one was missing. (#149)
  • cli is now used to format (colorizing, italicizing, etc.) console output
    rather than crayon. Please report any issues if formatting doesn't work
    right for you; there shouldn't be any changes from past releases.