jss references

DESCRIPTION

@@ -25,7 +25,7 @@ Authors@R:
              role = c("ctb"),
              comment = c(ORCID = "0000-0002-3948-3914"))
              )
-Description: Compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference.
+Description: Compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.
 License: GPL (>= 3)
 Copyright: inst/COPYRIGHTS
 LazyData: true

R/comparisons.R

@@ -85,6 +85,7 @@
 #' @param cross
 #' * `FALSE`: Contrasts represent the change in adjusted predictions when one predictor changes and all other variables are held constant.
 #' * `TRUE`: Contrasts represent the changes in adjusted predictions when all the predictors specified in the `variables` argument are manipulated simultaneously (a "cross-contrast").
+#' @template references
 #' @template deltamethod
 #' @template model_specific_arguments
 #' @template comparison_functions
@@ -93,7 +94,6 @@
 #' @template type
 #' @template order_of_operations
 #' @template parallel
-#' @template references
 #' @template options
 #'
 #' @return A `data.frame` with one row per observation (per term/group) and several columns:

R/package.R

@@ -5,76 +5,77 @@
 #' @useDynLib marginaleffects
 #' @import data.table
 utils::globalVariables(c(
-"marginaleffects_contrast_hi",
-"marginaleffects_contrast_lo",
-"..bycols",
-"..to_keep",
-"..cols",
-"..idx_by",
-"..idx_hi",
-"..cl",
-"..idx_lo",
-".data",
-"..idx_or",
-"..idx",
-"..idx1",
-"..idx2",
-"..nonfocal",
-"rowidcf",
-"elast",
-"..tmp",
-"..variables_grid",
-"..w",
-"marginaleffects_lab",
-"marginaleffects_ter",
-"..label_columns",
-"marginaleffects_internal_label",
-".",
-"tmp_idx",
-"chunk",
-"comparison",
-"condition_variable",
-"conf_int",
-"conf_level",
-"conf.high",
-"conf.low",
-"contrast",
-"draw",
-"dydx",
-"eps",
-"estimates",
-"estimate",
-"formatBicLL",
-"gn",
-"group",
-"logLik",
-"m",
-"marginaleffects_function",
-"marginaleffects_wts_internal",
-"marginalmean",
-"model",
-"N",
-"p.value",
-"part",
-"patterns",
-"position",
-"predicted_hi",
-"predicted_lo",
-"predicted_or",
-"predicted",
-"rowid",
-"rowidunique",
-"hi",
-"lo",
-"section",
-"stars_note",
-"statistic",
-"statistic1",
-"std.error",
-"term",
-"ticks",
-"tmp_grp",
-"comparison_idx",
-"value",
-"where",
-"wts"))
+  "marginaleffects_contrast_hi",
+  "marginaleffects_contrast_lo",
+  "..bycols",
+  "..to_keep",
+  "..cols",
+  "..idx_by",
+  "..idx_hi",
+  "..cl",
+  "..idx_lo",
+  ".data",
+  "..idx_or",
+  "..idx",
+  "..idx1",
+  "..idx2",
+  "..nonfocal",
+  "aa",
+  "rowidcf",
+  "elast",
+  "..tmp",
+  "..variables_grid",
+  "..w",
+  "marginaleffects_lab",
+  "marginaleffects_ter",
+  "..label_columns",
+  "marginaleffects_internal_label",
+  ".",
+  "tmp_idx",
+  "chunk",
+  "comparison",
+  "condition_variable",
+  "conf_int",
+  "conf_level",
+  "conf.high",
+  "conf.low",
+  "contrast",
+  "draw",
+  "dydx",
+  "eps",
+  "estimates",
+  "estimate",
+  "formatBicLL",
+  "gn",
+  "group",
+  "logLik",
+  "m",
+  "marginaleffects_function",
+  "marginaleffects_wts_internal",
+  "marginalmean",
+  "model",
+  "N",
+  "p.value",
+  "part",
+  "patterns",
+  "position",
+  "predicted_hi",
+  "predicted_lo",
+  "predicted_or",
+  "predicted",
+  "rowid",
+  "rowidunique",
+  "hi",
+  "lo",
+  "section",
+  "stars_note",
+  "statistic",
+  "statistic1",
+  "std.error",
+  "term",
+  "ticks",
+  "tmp_grp",
+  "comparison_idx",
+  "value",
+  "where",
+  "wts"))

R/predictions.R

@@ -61,14 +61,14 @@
 #' first entry in the error message is used by default.
 #' @param transform A function applied to unit-level adjusted predictions and confidence intervals just before the function returns results. For bayesian models, this function is applied to individual draws from the posterior distribution, before computing summaries.
 #'
+#' @template references
 #' @template deltamethod
 #' @template model_specific_arguments
 #' @template bayesian
 #' @template equivalence
 #' @template type
 #' @template order_of_operations
 #' @template parallel
-#' @template references
 #' @template options
 #'
 #' @return A `data.frame` with one row per observation and several columns:

R/slopes.R

@@ -127,13 +127,13 @@
 #' using a simple epsilon difference approach: \eqn{\partial Y / \partial X = (f(X + \varepsilon/2) - f(X-\varepsilon/2)) / \varepsilon}{dY/dX = (f(X + e/2) - f(X-e/2)) / e},
 #' where f is the `predict()` method associated with the model class, and
 #' \eqn{\varepsilon}{e} is determined by the `eps` argument.
+#' @template references
 #' @template deltamethod
 #' @template model_specific_arguments
 #' @template bayesian
 #' @template equivalence
 #' @template type
 #' @template parallel
-#' @template references
 #' @template order_of_operations
 #' @template options
 #'

inst/CITATION

@@ -1,25 +1,20 @@
 bibentry(bibtype = "Article",
-  key = "R-marginaleffects",
-  title        = "How to Interpret Statistical Models Using \\texttt{marginaleffects} in \\texttt{R} and \\texttt{Python}",
-  author       = c(
-    person(given = "Vincent",
-           family = "Arel-Bundock",
-           email = "[email protected]"),
-    person(given = "Noah",
-           family = "Greifer",
-           email = "[email protected]"),
-    person(given = "Andrew",
-           family = "Heiss",
-           email = "[email protected]")
-  ),
-  year         = "Forthcoming",
+  title        = "How to Interpret Statistical Models Using {marginaleffects} for {R} and {Python}",
+  author       = c(person(given = "Vincent",
+                          family = "Arel-Bundock",
+                          email = "[email protected]"),
+                   person(given = "Noah",
+                          family = "Greifer",
+                          email = "[email protected]"),
+                   person(given = "Andrew",
+                          family = "Heiss",
+                          email = "[email protected]")),
   journal      = "Journal of Statistical Software",
-  url = "https://marginaleffects.com",
-  header       = "To cite marginaleffects in publications, please use:",
-  textVersion =
-  paste("Vincent Arel-Bundock, Noah Greifer, and Andrew Heiss.",
-        "Forthcoming.",
-        "How to Interpret Statistical Models Using marginaleffects in R and Python.",
-        "Journal of Statistical Software.",
-	"https://marginaleffects.com")
+  year         = "2024",
+  volume       = "111",
+  number       = "9",
+  pages        = "1--32",
+  doi          = "10.18637/jss.v111.i09",
+  header       = "To cite marginaleffects in publications use:"
 )
+

inst/tinytest/helpers.R

@@ -1,7 +1,7 @@
 rm(list = ls())
 rm(list = ls(.GlobalEnv), envir = .GlobalEnv)
 
-EXPENSIVE <- FALSE
+EXPENSIVE <- TRUE
 
 options("tinysnapshot_device" = "svglite")
 options("tinysnapshot_tol" = 200)

man-roxygen/references.R

@@ -1,4 +1,5 @@
 #' @references
-#' 
+#'
+#' * Arel-Bundock V, Greifer N, Heiss A (2024). “How to Interpret Statistical Models Using marginaleffects for R and Python.” _Journal of Statistical Software_, *111*(9), 1-32. doi:10.18637/jss.v111.i09 <https://doi.org/10.18637/jss.v111.i09>.
 #' * Greenland S. 2019. "Valid P-Values Behave Exactly as They Should: Some Misleading Criticisms of P-Values and Their Resolution With S-Values." The American Statistician. 73(S1): 106–114.
 #' * Cole, Stephen R, Jessie K Edwards, and Sander Greenland. 2020. "Surprise!" American Journal of Epidemiology 190 (2): 191–93. https://doi.org/10.1093/aje/kwaa136