Prepare CRAN submission

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-Version: 0.12.2
-Date: 2024-07-17 21:02:38 UTC
-SHA: d4c45126ca666644785dc64d2af6b87eee9ca39b
+Version: 0.12.3
+Date: 2024-09-02 16:10:51 UTC
+SHA: dfbe03fd4961ee9049d5169275248a4ef7a5a21e

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: performance
 Title: Assessment of Regression Models Performance
-Version: 0.12.2.13
+Version: 0.12.3
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -160,4 +160,3 @@ Config/Needs/website:
     r-lib/pkgdown,
     easystats/easystatstemplate
 Config/rcmdcheck/ignore-inconsequential-notes: true
-Remotes: easystats/see, easystats/insight

NAMESPACE

@@ -170,12 +170,14 @@ S3method(model_performance,censReg)
 S3method(model_performance,clm)
 S3method(model_performance,clm2)
 S3method(model_performance,coxph)
+S3method(model_performance,coxph_weightit)
 S3method(model_performance,default)
 S3method(model_performance,felm)
 S3method(model_performance,fixest)
 S3method(model_performance,fixest_multi)
 S3method(model_performance,flexsurvreg)
 S3method(model_performance,glm)
+S3method(model_performance,glm_weightit)
 S3method(model_performance,glmmTMB)
 S3method(model_performance,glmmadmb)
 S3method(model_performance,glmx)
@@ -197,9 +199,11 @@ S3method(model_performance,mixor)
 S3method(model_performance,mlogit)
 S3method(model_performance,model_fit)
 S3method(model_performance,multinom)
+S3method(model_performance,multinom_weightit)
 S3method(model_performance,negbinirr)
 S3method(model_performance,negbinmfx)
 S3method(model_performance,nestedLogit)
+S3method(model_performance,ordinal_weightit)
 S3method(model_performance,plm)
 S3method(model_performance,poissonirr)
 S3method(model_performance,poissonmfx)

R/check_dag.R

@@ -103,7 +103,7 @@
 #'   Interpreting Confounder and Modifier Coefficients. American Journal of
 #'   Epidemiology, 177(4), 292–298. \doi{10.1093/aje/kws412}
 #'
-#' @examplesIf require("ggdag", quietly = TRUE) && require("dagitty", quietly = TRUE) && require("see", quietly = TRUE)
+#' @examplesIf require("ggdag", quietly = TRUE) && require("dagitty", quietly = TRUE) && require("see", quietly = TRUE) && packageVersion("see") > "0.8.5"
 #' # no adjustment needed
 #' check_dag(
 #'   y ~ x + b,

R/check_singularity.R

@@ -97,6 +97,7 @@
 #' )
 #' check_singularity(model)
 #'
+#' \dontrun{
 #' # Fixing singularity issues using priors in glmmTMB
 #' # Example taken from `vignette("priors", package = "glmmTMB")`
 #' dat <- readRDS(system.file(
@@ -120,7 +121,7 @@
 #' model_with_priors <- update(model, priors = prior)
 #' # no singular fit
 #' check_singularity(model_with_priors)
-#'
+#' }
 #' @export
 check_singularity <- function(x, tolerance = 1e-5, ...) {
   UseMethod("check_singularity")

R/model_performance.lm.R

@@ -3,10 +3,10 @@
 #' Compute indices of model performance for regression models.
 #'
 #' @param model A model.
-#' @param metrics Can be `"all"`, `"common"` or a character vector of
-#'   metrics to be computed (one or more of `"AIC"`, `"AICc"`, `"BIC"`, `"R2"`,
-#'   `"R2_adj"`, `"RMSE"`, `"SIGMA"`, `"LOGLOSS"`, `"PCP"`, `"SCORE"`).
-#'   `"common"` will compute AIC, BIC, R2 and RMSE.
+#' @param metrics Can be `"all"`, `"common"` or a character vector of metrics to
+#'   be computed (one or more of `"AIC"`, `"AICc"`, `"BIC"`, `"R2"`, `"R2_adj"`,
+#'   `"RMSE"`, `"SIGMA"`, `"LOGLOSS"`, `"PCP"`, `"SCORE"`). `"common"` will
+#'   compute AIC, BIC, R2 and RMSE.
 #' @param verbose Toggle off warnings.
 #' @param ... Arguments passed to or from other methods.
 #'
@@ -39,7 +39,7 @@
 #' model <- glm(vs ~ wt + mpg, data = mtcars, family = "binomial")
 #' model_performance(model)
 #' @export
 model_performance.lm <- function(model, metrics = "all", verbose = TRUE, ...) {
   if (any(tolower(metrics) == "log_loss")) {
     metrics[tolower(metrics) == "log_loss"] <- "LOGLOSS"
   }
@@ -209,6 +209,18 @@
 #' @export
 model_performance.multinom <- model_performance.lm
 
+#' @export
+model_performance.multinom_weightit <- model_performance.lm
+
+#' @export
+model_performance.ordinal_weightit <- model_performance.lm
+
+#' @export
+model_performance.coxph_weightit <- model_performance.lm
+
+#' @export
+model_performance.glm_weightit <- model_performance.lm
+
 #' @export
 model_performance.plm <- model_performance.lm
 

R/r2.R

@@ -251,7 +251,6 @@ r2.aov <- function(model, ci = NULL, ...) {
 #' @rdname r2
 #' @export
 r2.mlm <- function(model, multivariate = TRUE, ...) {
-
   if (multivariate) {
     out <- r2_mlm(model)
   } else {

R/r2_coxsnell.R

@@ -8,12 +8,12 @@
 #' @param ... Currently not used.
 #'
 #' @details
-#' This index was proposed by *Cox and Snell (1989, pp. 208-9)* and,
-#' apparently independently, by *Magee (1990)*; but had been suggested
-#' earlier for binary response models by *Maddala (1983)*. However, this
-#' index achieves a maximum of less than 1 for discrete models (i.e. models
-#' whose likelihood is a product of probabilities) which have a maximum of 1,
-#' instead of densities, which can become infinite *(Nagelkerke, 1991)*.
+#' This index was proposed by *Cox and Snell (1989, pp. 208-9)* and, apparently
+#' independently, by *Magee (1990)*; but had been suggested earlier for binary
+#' response models by *Maddala (1983)*. However, this index achieves a maximum
+#' of less than 1 for discrete models (i.e. models whose likelihood is a product
+#' of probabilities) which have a maximum of 1, instead of densities, which can
+#' become infinite *(Nagelkerke, 1991)*.
 #'
 #' @return A named vector with the R2 value.
 #'
@@ -24,12 +24,12 @@
 #' @references
 #' - Cox, D. R., Snell, E. J. (1989). Analysis of binary data (Vol. 32).
 #'   Monographs on Statistics and Applied Probability.
-#' - Magee, L. (1990). R 2 measures based on Wald and likelihood ratio
-#'   joint significance tests. The American Statistician, 44(3), 250-253.
+#' - Magee, L. (1990). R 2 measures based on Wald and likelihood ratio joint
+#'   significance tests. The American Statistician, 44(3), 250-253.
 #' - Maddala, G. S. (1986). Limited-dependent and qualitative variables in
 #'   econometrics (No. 3). Cambridge university press.
-#' - Nagelkerke, N. J. (1991). A note on a general definition of the
-#'   coefficient of determination. Biometrika, 78(3), 691-692.
+#' - Nagelkerke, N. J. (1991). A note on a general definition of the coefficient
+#'   of determination. Biometrika, 78(3), 691-692.
 #'
 #' @export
 r2_coxsnell <- function(model, ...) {

R/r2_mlm.R

@@ -53,7 +53,7 @@
 #' - Azen, R., & Budescu, D. V. (2006). Comparing predictors in
 #'   multivariate regression models: An extension of dominance analysis.
 #'   Journal of Educational and Behavioral Statistics, 31(2), 157-180.
-#'-  Cramer, E. M., & Nicewander, W. A. (1979). Some symmetric,
+#' -  Cramer, E. M., & Nicewander, W. A. (1979). Some symmetric,
 #'   invariant measures of multivariate association. Psychometrika, 44, 43-54.
 #' - Van den Burg, W., & Lewis, C. (1988). Some properties of two
 #'   measures of multivariate association. Psychometrika, 53, 109-122.
@@ -73,7 +73,7 @@ r2_mlm.mlm <- function(model, verbose = TRUE, ...) {
     insight::get_predictors(model),
     insight::get_response(model)
   )$cor^2
-  R_xy  <- 1 - Reduce(`*`, rho2_vec, 1)
+  R_xy <- 1 - Reduce(`*`, rho2_vec, 1)
 
   resid_cov <- stats::cov(residuals(model))
   resp_cov <- stats::cov(insight::get_response(model))

cran-comments.md

@@ -1 +1 @@
-This is a patch release that fixes failing CRAN checks for Mac OS old-rel.
+Maintance release.

tests/testthat/test-check_heterogeneity_bias.R

@@ -32,3 +32,19 @@ test_that("check_heterogeneity_bias", {
     "Possible heterogeneity bias due to following predictors: Petal\\.Length, Petal\\.Width, Species"
   )
 })
+
+test_that("check_heterogeneity_bias", {
+  skip_if_not_installed("datawizard", minimum_version = "0.12.3")
+  data(efc, package = "datawizard")
+  dat <- na.omit(efc)
+  dat$e42dep <- factor(dat$e42dep)
+  dat$c172code <- factor(dat$c172code)
+
+  out <- check_heterogeneity_bias(
+    dat,
+    select = "c12hour",
+    by = c("e42dep", "c172code"),
+    nested = TRUE
+  )
+  expect_equal(out, "c12hour", ignore_attr = TRUE)
+})

tests/testthat/test-model_performance.bayesian.R

@@ -60,7 +60,7 @@ test_that("model_performance.brmsfit", {
   expect_equal(perf$R2, 0.954538, tolerance = 1e-3)
   expect_equal(perf$R2_adjusted, 0.9529004, tolerance = 1e-3)
   expect_equal(perf$ELPD, -70.40493, tolerance = 1e-3)
-  expect_identical(colnames(perf), c(
+  expect_named(perf, c(
     "ELPD", "ELPD_SE", "LOOIC", "LOOIC_SE", "WAIC", "R2", "R2_marginal",
     "R2_adjusted", "R2_adjusted_marginal", "ICC", "RMSE", "Sigma"
   ))