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Prepare CRAN submission (#767)
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strengejacke committed Sep 2, 2024
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6 changes: 3 additions & 3 deletions CRAN-SUBMISSION
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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
3 changes: 1 addition & 2 deletions DESCRIPTION
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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",
Expand Down Expand Up @@ -160,4 +160,3 @@ Config/Needs/website:
r-lib/pkgdown,
easystats/easystatstemplate
Config/rcmdcheck/ignore-inconsequential-notes: true
Remotes: easystats/see, easystats/insight
4 changes: 4 additions & 0 deletions NAMESPACE
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Expand Up @@ -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)
Expand All @@ -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)
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2 changes: 1 addition & 1 deletion R/check_dag.R
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Expand Up @@ -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"

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file=R/check_dag.R,line=106,col=121,[line_length_linter] Lines should not be more than 120 characters. This line is 154 characters.
#' # no adjustment needed
#' check_dag(
#' y ~ x + b,
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3 changes: 2 additions & 1 deletion R/check_singularity.R
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Expand Up @@ -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(
Expand All @@ -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")
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20 changes: 16 additions & 4 deletions R/model_performance.lm.R
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Expand Up @@ -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.
#'
Expand Down Expand Up @@ -209,6 +209,18 @@ model_performance.lm_robust <- model_performance.lm
#' @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

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1 change: 0 additions & 1 deletion R/r2.R
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Expand Up @@ -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 {
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20 changes: 10 additions & 10 deletions R/r2_coxsnell.R
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Expand Up @@ -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.
#'
Expand All @@ -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, ...) {
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4 changes: 2 additions & 2 deletions R/r2_mlm.R
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Expand Up @@ -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.
Expand All @@ -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))
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2 changes: 1 addition & 1 deletion cran-comments.md
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This is a patch release that fixes failing CRAN checks for Mac OS old-rel.
Maintance release.
2 changes: 1 addition & 1 deletion man/check_dag.Rd

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2 changes: 2 additions & 0 deletions man/check_singularity.Rd

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8 changes: 4 additions & 4 deletions man/model_performance.lm.Rd

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20 changes: 10 additions & 10 deletions man/r2_coxsnell.Rd

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16 changes: 16 additions & 0 deletions tests/testthat/test-check_heterogeneity_bias.R
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Expand Up @@ -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)
})
2 changes: 1 addition & 1 deletion tests/testthat/test-model_performance.bayesian.R
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Expand Up @@ -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"
))
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