Merge branch 'main' into strengejacke/issue697

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
+Version: 0.12.3.3
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",
@@ -52,7 +52,11 @@ Authors@R:
              "Bacher", ,
              "[email protected]",
              role = "ctb",
-             comment = c(ORCID = "0000-0002-9271-5075")))
+             comment = c(ORCID = "0000-0002-9271-5075")),
+      person(given = "Joseph",
+             family = "Luchman",
+             role = "ctb",
+             comment = c(ORCID = "0000-0002-8886-9717")))
 Maintainer: Daniel Lüdecke <[email protected]>
 Description: Utilities for computing measures to assess model quality,
     which are not directly provided by R's 'base' or 'stats' packages.
@@ -89,6 +93,7 @@ Suggests:
     CompQuadForm,
     correlation,
     cplm,
+    dagitty,
     dbscan,
     DHARMa,
     estimatr,
@@ -97,7 +102,7 @@ Suggests:
     forecast,
     ftExtra,
     gamm4,
-    ggplot2,
+    ggdag,
     glmmTMB,
     graphics,
     Hmisc,

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)
@@ -269,6 +273,7 @@ S3method(plot,binned_residuals)
 S3method(plot,check_autocorrelation)
 S3method(plot,check_clusterstructure)
 S3method(plot,check_collinearity)
+S3method(plot,check_dag)
 S3method(plot,check_distribution)
 S3method(plot,check_distribution_numeric)
 S3method(plot,check_heteroscedasticity)
@@ -289,6 +294,7 @@ S3method(print,binned_residuals)
 S3method(print,check_autocorrelation)
 S3method(print,check_collinearity)
 S3method(print,check_concurvity)
+S3method(print,check_dag)
 S3method(print,check_distribution)
 S3method(print,check_distribution_numeric)
 S3method(print,check_heterogeneity_bias)
@@ -484,6 +490,7 @@ S3method(r2_mcfadden,serp)
 S3method(r2_mcfadden,truncreg)
 S3method(r2_mcfadden,vglm)
 S3method(r2_mckelvey,default)
+S3method(r2_mlm,mlm)
 S3method(r2_nagelkerke,BBreg)
 S3method(r2_nagelkerke,DirichletRegModel)
 S3method(r2_nagelkerke,bife)
@@ -538,12 +545,14 @@ S3method(test_vuong,default)
 S3method(test_wald,ListNestedRegressions)
 S3method(test_wald,ListNonNestedRegressions)
 S3method(test_wald,default)
+export(as.dag)
 export(binned_residuals)
 export(check_autocorrelation)
 export(check_clusterstructure)
 export(check_collinearity)
 export(check_concurvity)
 export(check_convergence)
+export(check_dag)
 export(check_distribution)
 export(check_factorstructure)
 export(check_heterogeneity_bias)
@@ -606,6 +615,7 @@ export(r2_loo)
 export(r2_loo_posterior)
 export(r2_mcfadden)
 export(r2_mckelvey)
+export(r2_mlm)
 export(r2_nagelkerke)
 export(r2_nakagawa)
 export(r2_posterior)

NEWS.md

@@ -1,3 +1,24 @@
+# performance 0.12.4
+
+## Changes
+
+* `check_dag()` now also checks for colliders, and suggests removing it in the
+  printed output.
+
+* Minor revisions to the printed output of `check_dag()`.
+
+# performance 0.12.3
+
+## New functions
+
+* `check_dag()`, to check DAGs for correct adjustment sets.
+
+## Changes
+
+* `check_heterogeneity_bias()` gets a `nested` argument. Furthermore, `by` can
+  specify more than one variable, meaning that nested or cross-classified
+  model designs can also be tested for heterogeneity bias.
+
 # performance 0.12.2
 
 Patch release, to ensure that _performance_ runs with older version of