Merge branch 'main' into dcchoice

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-Version: 0.19.5
-Date: 2023-09-13 07:09:16 UTC
-SHA: 3ebd4e597e7a67ee0ed14bff617c5889b01767bb
+Version: 0.19.6
+Date: 2023-10-12 10:36:43 UTC
+SHA: f2fbc4f7b48031b6359e0b815389c989cbf2976f

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: insight
 Title: Easy Access to Model Information for Various Model Objects
-Version: 0.19.5.13
+Version: 0.19.6.3
 Authors@R: 
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -123,6 +123,7 @@ Suggests:
     gee,
     geepack,
     geoR,
+    ggeffects,
     GLMMadaptive,
     glmmTMB,
     gmnl,
@@ -206,3 +207,4 @@ Config/Needs/website:
     rstudio/bslib,
     r-lib/pkgdown,
     easystats/easystatstemplate
+Remotes: strengejacke/ggeffects

NAMESPACE

@@ -608,6 +608,7 @@ S3method(get_parameters,gam)
 S3method(get_parameters,gamlss)
 S3method(get_parameters,gamm)
 S3method(get_parameters,gbm)
+S3method(get_parameters,ggcomparisons)
 S3method(get_parameters,glht)
 S3method(get_parameters,glimML)
 S3method(get_parameters,glmm)
@@ -816,6 +817,7 @@ S3method(get_statistic,gamm)
 S3method(get_statistic,garch)
 S3method(get_statistic,gee)
 S3method(get_statistic,geeglm)
+S3method(get_statistic,ggcomparisons)
 S3method(get_statistic,glht)
 S3method(get_statistic,glimML)
 S3method(get_statistic,glmm)
@@ -1317,6 +1319,7 @@ S3method(model_info,gamlss)
 S3method(model_info,gamm)
 S3method(model_info,garch)
 S3method(model_info,gbm)
+S3method(model_info,ggcomparisons)
 S3method(model_info,glht)
 S3method(model_info,glimML)
 S3method(model_info,glmm)

NEWS.md

@@ -1,3 +1,14 @@
+# insight 0.19.7
+
+## General
+
+* Support for objects of class `ggcomparisons` from `ggeffects::hypothesis_test()`.
+
+## Changes to functions
+
+* `get_varcov()` for models of class `pgmm` (package *plm*) now also supported
+  robust variance-covariance matrices (i.e. argument `vcov`).
+
 # insight 0.19.6
 
 ## General

R/clean_parameters.R

@@ -27,12 +27,12 @@
 #' The `Effects` column indicate if a parameter is a *fixed* or *random* effect.
 #' The `Component` can either be *conditional* or *zero_inflated*. For models
 #' with random effects, the `Group` column indicates the grouping factor of the
-#' random effects. For multivariate response models from {brms} or
-#' {rstanarm}, an additional *Response* column is included, to indicate
+#' random effects. For multivariate response models from **brms** or
+#' **rstanarm**, an additional *Response* column is included, to indicate
 #' which parameters belong to which response formula. Furthermore,
 #' *Cleaned_Parameter* column is returned that contains "human readable"
 #' parameter names (which are mostly identical to `Parameter`, except for for
-#' models from {brms} or {rstanarm}, or for specific terms like smooth-
+#' models from **brms** or **rstanarm**, or for specific terms like smooth-
 #' or spline-terms).
 #'
 #' @examplesIf require("curl", quietly = TRUE) && curl::has_internet() && require("brms")

R/find_formula.R

@@ -21,7 +21,7 @@
 #'  - `conditional`, the "fixed effects" part from the model (in the
 #'    context of fixed-effects or instrumental variable regression, also
 #'    called *regressors*) . One exception are `DirichletRegModel` models
-#'    from {DirichletReg}, which has two or three components,
+#'    from **DirichletReg**, which has two or three components,
 #'    depending on `model`.
 #'
 #'  - `random`, the "random effects" part from the model (or the
@@ -49,7 +49,7 @@
 #'    `feisr::feis()`, the formula for the slope parameters
 #'
 #'  - `precision`, for `DirichletRegModel` models from
-#'    {DirichletReg}, when parametrization (i.e. `model`) is
+#'    **DirichletReg**, when parametrization (i.e. `model`) is
 #'    `"alternative"`.
 #'
 #' @note For models of class `lme` or `gls` the correlation-component

R/find_parameters.R

@@ -6,13 +6,13 @@
 #' names equal the column names of the posterior samples after coercion
 #' from `as.data.frame()`. See the documentation for your object's class:
 #'
-#' - [Bayesian models][find_parameters.BGGM] ({rstanarm}, {brms}, {MCMCglmm}, ...)
-#' - [Generalized additive models][find_parameters.gamlss] ({mgcv}, {VGAM}, ...)
-#' - [Marginal effects models][find_parameters.betamfx] ({mfx})
-#' - [Estimated marginal means][find_parameters.emmGrid] ({emmeans})
-#' - [Mixed models][find_parameters.glmmTMB] ({lme4}, {glmmTMB}, {GLMMadaptive}, ...)
-#' - [Zero-inflated and hurdle models][find_parameters.zeroinfl] ({pscl}, ...)
-#' - [Models with special components][find_parameters.averaging] ({betareg}, {MuMIn}, ...)
+#' - [Bayesian models][find_parameters.BGGM] (**rstanarm**, **brms**, **MCMCglmm**, ...)
+#' - [Generalized additive models][find_parameters.gamlss] (**mgcv**, **VGAM**, ...)
+#' - [Marginal effects models][find_parameters.betamfx] (**mfx**)
+#' - [Estimated marginal means][find_parameters.emmGrid] (**emmeans**)
+#' - [Mixed models][find_parameters.glmmTMB] (**lme4**, **glmmTMB**, **GLMMadaptive**, ...)
+#' - [Zero-inflated and hurdle models][find_parameters.zeroinfl] (**pscl**, ...)
+#' - [Models with special components][find_parameters.averaging] (**betareg**, **MuMIn**, ...)
 #'
 #' @param verbose Toggle messages and warnings.
 #' @param ... Currently not used.

R/find_parameters_bayesian.R

@@ -27,15 +27,15 @@
 #'   component of the model
 #' - `smooth_terms`, the smooth parameters
 #'
-#' Furthermore, some models, especially from {brms}, can also return auxiliary
+#' Furthermore, some models, especially from **brms**, can also return auxiliary
 #' parameters. These may be one of the following:
 #'
 #' - `sigma`, the residual standard deviation (auxiliary parameter)
 #' - `dispersion`, the dispersion parameters (auxiliary parameter)
 #' - `beta`, the beta parameter (auxiliary parameter)
-#' - `simplex`, simplex parameters of monotonic effects (\pkg{brms} only)
-#' - `mix`, mixture parameters (\pkg{brms} only)
-#' - `shiftprop`, shifted proportion parameters (\pkg{brms} only)
+#' - `simplex`, simplex parameters of monotonic effects (**brms** only)
+#' - `mix`, mixture parameters (**brms** only)
+#' - `shiftprop`, shifted proportion parameters (**brms** only)
 #'
 #' @examples
 #' data(mtcars)

R/find_parameters_mfx.R

@@ -9,7 +9,7 @@
 #'   term, the instrumental variables or marginal effects be returned? Applies
 #'   to models with zero-inflated and/or dispersion formula, or to models with
 #'   instrumental variables (so called fixed-effects regressions), or models
-#'   with marginal effects from \pkg{mfx}. May be abbreviated. Note that the
+#'   with marginal effects from **mfx**. May be abbreviated. Note that the
 #'   *conditional* component is also called *count* or *mean*
 #'   component, depending on the model. There are three convenient shortcuts:
 #'   `component = "all"` returns all possible parameters.

R/find_statistic.R

@@ -120,8 +120,8 @@ find_statistic <- function(x, ...) {
     "deltaMethod", "DirichletRegModel",
     "ergm",
     "feglm", "flexsurvreg",
-    "gee", "glimML", "glmm", "glmmadmb", "glmmFit", "glmmLasso", "glmmTMB",
-    "glmx", "gmnl",
+    "gee", "ggcomparisons", "glimML", "glmm", "glmmadmb", "glmmFit", "glmmLasso",
+    "glmmTMB", "glmx", "gmnl",
     "hurdle",
     "lavaan", "loggammacenslmrob", "logitmfx", "logitor", "logitr", "LORgee", "lrm",
     "margins", "marginaleffects", "marginaleffects.summary", "metaplus", "mixor",

R/format_table.R

@@ -8,7 +8,7 @@
 #'   converts all columns into character vectors!
 #'
 #' @param x A data frame of model's parameters, as returned by various functions
-#'   of the {easystats}-packages. May also be a result from
+#'   of the **easystats**-packages. May also be a result from
 #'   `broom::tidy()`.
 #' @param pretty_names Return "pretty" (i.e. more human readable) parameter
 #'   names.

R/get_auxiliary.R

@@ -37,7 +37,7 @@
 #' degrees of freedom. For models of class `glmmTMB`, dispersion is
 #' \ifelse{html}{\out{&sigma;<sup>2</sup>}}{\eqn{\sigma^2}}.
 #' }
-#' \subsection{\pkg{brms} models}{
+#' \subsection{**brms** models}{
 #' For models of class `brmsfit`, there are different options for the
 #' `type` argument. See a list of supported auxiliary parameters here:
 #' [find_parameters.BGGM()].

R/get_data.R

@@ -2168,10 +2168,10 @@ get_data.rma <- function(x,
     mf_attr[c("yi.names", "vi.names", "digits", "class")]
   )
   if (isTRUE(include_interval)) {
-    model_response <- tryCatch(mf[[find_response(x)]], error = function(x) NULL)
-    sei <- tryCatch(mf[[model_call$sei]], error = function(x) NULL)
+    model_response <- .safe(mf[[find_response(x)]])
+    sei <- .safe(mf[[model_call$sei]])
     if (is.null(sei)) {
-      sei <- tryCatch(sqrt(mf[[model_call$vi]]), error = function(x) NULL)
+      sei <- .safe(sqrt(mf[[model_call$vi]]))
     }
     if (is.null(sei)) {
       format_error("Could not find `sei` or `vi` for this model.")

R/get_loglikelihood.R

@@ -28,7 +28,7 @@
 #' @return An object of class `"logLik"`, also containing the
 #'   log-likelihoods for each observation as a `per_observation` attribute
 #'   (`attributes(get_loglikelihood(x))$per_observation`) when possible.
-#'   The code was partly inspired from the {nonnest2} package.
+#'   The code was partly inspired from the **nonnest2** package.
 #'
 #' @examples
 #' x <- lm(Sepal.Length ~ Petal.Width + Species, data = iris)

R/get_parameters.R

@@ -4,13 +4,13 @@
 #' @description Returns the coefficients (or posterior samples for Bayesian
 #' models) from a model. See the documentation for your object's class:
 #'
-#' - [Bayesian models][get_parameters.BGGM] ({rstanarm}, {brms}, {MCMCglmm}, ...)
-#' - [Estimated marginal means][get_parameters.emmGrid] ({emmeans})
-#' - [Generalized additive models][get_parameters.gamm] ({mgcv}, {VGAM}, ...)
-#' - [Marginal effects models][get_parameters.betamfx] ({mfx})
-#' - [Mixed models][get_parameters.glmm] ({lme4}, {glmmTMB}, {GLMMadaptive}, ...)
-#' - [Zero-inflated and hurdle models][get_parameters.zeroinfl] ({pscl}, ...)
-#' - [Models with special components][get_parameters.betareg] ({betareg}, {MuMIn}, ...)
+#' - [Bayesian models][get_parameters.BGGM] (**rstanarm**, **brms**, **MCMCglmm**, ...)
+#' - [Estimated marginal means][get_parameters.emmGrid] (**emmeans**)
+#' - [Generalized additive models][get_parameters.gamm] (**mgcv**, **VGAM**, ...)
+#' - [Marginal effects models][get_parameters.betamfx] (**mfx**)
+#' - [Mixed models][get_parameters.glmm] (**lme4**, **glmmTMB**, **GLMMadaptive**, ...)
+#' - [Zero-inflated and hurdle models][get_parameters.zeroinfl] (**pscl**, ...)
+#' - [Models with special components][get_parameters.betareg] (**betareg**, **MuMIn**, ...)
 #' - [Hypothesis tests][get_parameters.htest] (`htest`)
 #'
 #' @param verbose Toggle messages and warnings.

R/get_parameters_bayesian.R

@@ -31,8 +31,8 @@
 #' `effects` and `component` can be used.
 #'
 #' @section BFBayesFactor Models:
-#' Note that for `BFBayesFactor` models (from the \pkg{BayesFactor}
-#' package), posteriors are only extracted from the first numerator model (i.e.,
+#' Note that for `BFBayesFactor` models (from the **BayesFactor** package),
+#' posteriors are only extracted from the first numerator model (i.e.,
 #' `model[1]`). If you want to apply some function `foo()` to another
 #' model stored in the `BFBayesFactor` object, index it directly, e.g.
 #' `foo(model[2])`, `foo(1/model[5])`, etc.

R/get_parameters_emmeans.R

@@ -14,7 +14,7 @@
 #'
 #' @note
 #' Note that `emmGrid` or `emm_list` objects returned by functions from
-#' {emmeans} have a different structure compared to usual regression models.
+#' **emmeans** have a different structure compared to usual regression models.
 #' Hence, the `Parameter` column does not always contain names of *variables*,
 #' but may rather contain *values*, e.g. for contrasts. See an example for
 #' pairwise comparisons below.

R/get_parameters_mixed.R

@@ -13,7 +13,7 @@
 #'   parameter names and the related point estimates. If `effects =
 #'   "random"`, a list of data frames with the random effects (as returned by
 #'   `ranef()`), unless the random effects have the same simplified
-#'   structure as fixed effects (e.g. for models from {MCMCglmm}).
+#'   structure as fixed effects (e.g. for models from **MCMCglmm**).
 #'
 #' @details In most cases when models either return different "effects" (fixed,
 #' random) or "components" (conditional, zero-inflated, ...), the arguments

R/get_parameters_others.R

@@ -364,3 +364,31 @@ get_parameters.deltaMethod <- function(x, ...) {
     row.names = NULL
   )
 }
+
+
+#' @export
+get_parameters.ggcomparisons <- function(x, merge_parameters = FALSE, ...) {
+  estimate_pos <- which(colnames(x) == attr(x, "estimate_name"))
+  params <- x[, seq_len(estimate_pos - 1), drop = FALSE]
+
+  if (isTRUE(merge_parameters) && ncol(params) > 1L) {
+    r <- apply(params, 1, function(i) paste0(colnames(params), " [", i, "]"))
+    out <- data.frame(
+      Parameter = unname(vapply(as.data.frame(r), toString, character(1))),
+      Estimate = x[[estimate_pos]],
+      stringsAsFactors = FALSE,
+      row.names = NULL
+    )
+  } else {
+    out <- data.frame(
+      params,
+      Estimate = x[[estimate_pos]],
+      stringsAsFactors = FALSE,
+      row.names = NULL
+    )
+    if (isTRUE(merge_parameters)) {
+      colnames(out)[1] <- "Parameter"
+    }
+  }
+  text_remove_backticks(out)
+}

R/get_predicted.R

@@ -90,7 +90,7 @@
 #'   + `NULL` uses the default method, which varies based on the model type.
 #'   + Most frequentist models: `"wald"` (default), `"residual"` or `"normal"`.
 #'   + Bayesian models:  `"quantile"`  (default), `"hdi"`, `"eti"`, and `"spi"`.
-#'   + Mixed effects {lme4} models: `"wald"` (default), `"residual"`, `"normal"`,
+#'   + Mixed effects **lme4** models: `"wald"` (default), `"residual"`, `"normal"`,
 #'   `"satterthwaite"`, and `"kenward-roger"`.
 #'
 #'   See [`get_df()`] for details.

R/get_statistic.R

@@ -1598,6 +1598,33 @@ get_statistic.emm_list <- function(x, ci = 0.95, adjust = "none", ...) {
 }
 
 
+#' @export
+get_statistic.ggcomparisons <- function(x, merge_parameters = FALSE, ...) {
+  estimate_pos <- which(colnames(x) == attr(x, "estimate_name"))
+  if (isTRUE(merge_parameters)) {
+    params <- get_parameters(x, merge_parameters = TRUE)["Parameter"]
+  } else {
+    params <- x[, seq_len(estimate_pos - 1), drop = FALSE]
+  }
+
+  stat <- .safe(x[[estimate_pos]] / attributes(x)$standard_error)
+  if (is.null(stat)) {
+    return(NULL)
+  }
+
+  out <- data.frame(
+    params,
+    Statistic = as.vector(stat),
+    stringsAsFactors = FALSE,
+    row.names = NULL
+  )
+
+  out <- text_remove_backticks(out)
+  attr(out, "statistic") <- find_statistic(x)
+  out
+}
+
+
 #' @export
 get_statistic.robmixglm <- function(x, ...) {
   cs <- stats::coef(summary(x))

R/get_varcov.R

@@ -37,11 +37,11 @@
 #'    - Other `sandwich` package functions: `"vcovHAC"`, `"vcovPC"`, `"vcovCL"`,
 #'      `"vcovPL"`.
 #' @param vcov_args List of arguments to be passed to the function identified by
-#'   the `vcov` argument. This function is typically supplied by the {sandwich}
-#'   or {clubSandwich} packages. Please refer to their documentation (e.g.,
+#'   the `vcov` argument. This function is typically supplied by the **sandwich**
+#'   or **clubSandwich** packages. Please refer to their documentation (e.g.,
 #'   `?sandwich::vcovHAC`) to see the list of available arguments. If no estimation
 #'   type (argument `type`) is given, the default type for `"HC"` (or `"vcovHC"`)
-#'   equals the default from the {sandwich} package; for type `"CR"` (or
+#'   equals the default from the **sandwich** package; for type `"CR"` (or
 #'   `"vcoCR"`), the default is set to `"CR3"`.
 #' @param verbose Toggle warnings.
 #' @param ... Currently not used.
@@ -295,10 +295,27 @@ get_varcov.glmx <- function(x,
 
 
 #' @export
-get_varcov.pgmm <- function(x, component = c("conditional", "all"), verbose = TRUE, ...) {
+get_varcov.pgmm <- function(x,
+                            component = c("conditional", "all"),
+                            vcov = NULL,
+                            vcov_args = NULL,
+                            verbose = TRUE,
+                            ...) {
   .check_get_varcov_dots(x, ...)
+  # process vcov-argument
+  vcov <- .check_vcov_args(x, vcov = vcov, verbose = verbose, ...)
   component <- match.arg(component)
-  vc <- stats::vcov(x)
+
+  if (is.null(vcov)) {
+    vc <- suppressWarnings(stats::vcov(x))
+  } else {
+    vc <- .get_varcov_sandwich(x,
+      vcov_fun = vcov,
+      vcov_args = vcov_args,
+      verbose = FALSE,
+      ...
+    )
+  }
 
   if (component != "all") {
     keep <- match(find_parameters(x)[[component]], rownames(vc))

R/get_variances.R

@@ -94,9 +94,9 @@
 #' intercepts and slopes.
 #'
 #' @note This function supports models of class `merMod` (including models
-#' from {blme}), `clmm`, `cpglmm`, `glmmadmb`, `glmmTMB`, `MixMod`, `lme`,
+#' from **blme**), `clmm`, `cpglmm`, `glmmadmb`, `glmmTMB`, `MixMod`, `lme`,
 #' `mixed`, `rlmerMod`, `stanreg`, `brmsfit` or `wbm`. Support for objects of
-#' class `MixMod` ({GLMMadaptive}), `lme` ({nlme}) or `brmsfit` ({brms}) is
+#' class `MixMod` (**GLMMadaptive**), `lme` (**nlme**) or `brmsfit` (**brms**) is
 #' experimental and may not work for all models.
 #'
 #' @references

R/insight-package.R

@@ -8,10 +8,10 @@
 #' to obtain model information and data, many package-specific modelling functions
 #' do not provide such methods to allow users to access such valuable information.
 #'
-#' {insight} is an R-package that fills this important gap by providing a
+#' **insight** is an R-package that fills this important gap by providing a
 #' suite of functions to support almost any model (see a list of the many models
 #' supported below in the **List of Supported Packages and Models** section).
-#' The goal of {insight}, then, is to provide tools to provide *easy*,
+#' The goal of **insight**, then, is to provide tools to provide *easy*,
 #' *intuitive*, and *consistent* access to information contained in model
 #' objects. These tools aid applied research in virtually any field who fit,
 #' diagnose, and present statistical models by streamlining access to every