Merge pull request #439 from IndrajeetPatil/issue_436

stylistic changes

DESCRIPTION

@@ -141,7 +141,7 @@ Suggests:
     WRS2
 Encoding: UTF-8
 Language: en-US
-RoxygenNote: 7.1.1
+RoxygenNote: 7.1.1.9001
 VignetteBuilder: knitr
 Config/testthat/edition: 3
 Remotes: easystats/insight

R/1_model_parameters.R

@@ -213,7 +213,12 @@ model_parameters.default <- function(model,
 
   # Processing
   if (bootstrap) {
-    params <- bootstrap_parameters(model, iterations = iterations, ci = ci, ...)
+    params <- bootstrap_parameters(
+      model,
+      iterations = iterations,
+      ci = ci,
+      ...
+    )
   } else {
     params <- .extract_parameters_generic(
       model,

R/5_simulate_model.R

@@ -36,7 +36,7 @@
 #' model <- lm(Sepal.Length ~ Species * Petal.Width + Petal.Length, data = iris)
 #' head(simulate_model(model))
 #' \donttest{
-#' if (require("glmmTMB")) {
+#' if (require("glmmTMB", quietly = TRUE)) {
 #'   model <- glmmTMB(
 #'     count ~ spp + mined + (1 | site),
 #'     ziformula = ~mined,

R/bootstrap_model.R

@@ -26,7 +26,7 @@
 #'
 #' @examples
 #' \dontrun{
-#' if (require("boot")) {
+#' if (require("boot", quietly = TRUE)) {
 #'   model <- lm(mpg ~ wt + factor(cyl), data = mtcars)
 #'   b <- bootstrap_model(model)
 #'   print(head(b))
@@ -38,7 +38,10 @@
 #' }
 #' }
 #' @export
-bootstrap_model <- function(model, iterations = 1000, verbose = FALSE, ...) {
+bootstrap_model <- function(model,
+                            iterations = 1000,
+                            verbose = FALSE,
+                            ...) {
   UseMethod("bootstrap_model")
 }
 
@@ -50,7 +53,10 @@ bootstrap_model <- function(model, iterations = 1000, verbose = FALSE, ...) {
 #' @importFrom stats coef update setNames complete.cases
 #' @importFrom insight get_data find_parameters get_parameters
 #' @export
-bootstrap_model.default <- function(model, iterations = 1000, verbose = FALSE, ...) {
+bootstrap_model.default <- function(model,
+                                    iterations = 1000,
+                                    verbose = FALSE,
+                                    ...) {
   if (!requireNamespace("boot", quietly = TRUE)) {
     stop("Package 'boot' needed for this function to work. Please install it.")
   }
@@ -82,7 +88,12 @@ bootstrap_model.default <- function(model, iterations = 1000, verbose = FALSE, .
     return(params)
   }
 
-  results <- boot::boot(data = data, statistic = boot_function, R = iterations, model = model)
+  results <- boot::boot(
+    data = data,
+    statistic = boot_function,
+    R = iterations,
+    model = model
+  )
 
   out <- as.data.frame(results$t)
   out <- out[stats::complete.cases(out), ]
@@ -115,9 +126,18 @@ bootstrap_model.merMod <- function(model, iterations = 1000, verbose = FALSE, ..
   }
 
   if (verbose) {
-    results <- suppressMessages(lme4::bootMer(model, boot_function, nsim = iterations, verbose = FALSE))
+    results <- suppressMessages(lme4::bootMer(
+      model,
+      boot_function,
+      nsim = iterations,
+      verbose = FALSE
+    ))
   } else {
-    results <- lme4::bootMer(model, boot_function, nsim = iterations)
+    results <- lme4::bootMer(
+      model,
+      boot_function,
+      nsim = iterations
+    )
   }
 
   out <- as.data.frame(results$t)

R/bootstrap_parameters.R

@@ -28,7 +28,7 @@
 #'
 #' @examples
 #' \dontrun{
-#' if (require("boot")) {
+#' if (require("boot", quietly = TRUE)) {
 #'   set.seed(2)
 #'   model <- lm(Sepal.Length ~ Species * Petal.Width, data = iris)
 #'   b <- bootstrap_parameters(model)

R/demean.R

@@ -235,10 +235,13 @@ degroup <- function(x, select, group, center = "mean", suffix_demean = "_within"
   not_found <- setdiff(select, colnames(x))
 
   if (length(not_found) && isTRUE(verbose)) {
-    insight::print_color(sprintf("%i variables were not found in the dataset: %s\n",
-                                 length(not_found),
-                                 paste0(not_found, collapse = ", ")),
-                         color = "red")
+    insight::print_color(sprintf(
+      "%i variables were not found in the dataset: %s\n",
+      length(not_found),
+      paste0(not_found, collapse = ", ")
+    ),
+    color = "red"
+    )
   }
 
   select <- intersect(colnames(x), select)

R/describe_distribution.R

@@ -81,7 +81,12 @@ describe_distribution.numeric <- function(x,
     if (!requireNamespace("boot", quietly = TRUE)) {
       warning("Package 'boot' needed for bootstrapping confidence intervals.", call. = FALSE)
     } else {
-      results <- boot::boot(data = x, statistic = .boot_distribution, R = iterations, centrality = centrality)
+      results <- boot::boot(
+        data = x,
+        statistic = .boot_distribution,
+        R = iterations,
+        centrality = centrality
+      )
       out_ci <- bayestestR::ci(results$t, ci = ci, verbose = FALSE)
       out <- cbind(out, data.frame(CI_low = out_ci$CI_low[1], CI_high = out_ci$CI_high[1]))
     }

R/dof.R

@@ -36,12 +36,12 @@
 #' model <- glm(vs ~ mpg * cyl, data = mtcars, family = "binomial")
 #' dof(model)
 #' \dontrun{
-#' if (require("lme4")) {
+#' if (require("lme4", quietly = TRUE)) {
 #'   model <- lmer(Sepal.Length ~ Petal.Length + (1 | Species), data = iris)
 #'   dof(model)
 #' }
 #'
-#' if (require("rstanarm")) {
+#' if (require("rstanarm", quietly = TRUE)) {
 #'   model <- stan_glm(
 #'     Sepal.Length ~ Petal.Length * Species,
 #'     data = iris,

R/equivalence_test.R

@@ -130,7 +130,7 @@ bayestestR::equivalence_test
 #' equivalence_test(model, rule = "cet")
 #'
 #' # plot method
-#' if (require("see")) {
+#' if (require("see", quietly = TRUE)) {
 #'   result <- equivalence_test(model)
 #'   plot(result)
 #' }

R/format.R

@@ -15,7 +15,7 @@ format.parameters_model <- function(x,
                                     zap_small = FALSE,
                                     format = NULL,
                                     ...) {
-    # save attributes
+  # save attributes
   coef_name <- attributes(x)$coefficient_name
   s_value <- attributes(x)$s_value
   m_class <- attributes(x)$model_class

R/methods_DirichletReg.R

@@ -40,7 +40,10 @@ model_parameters.DirichletRegModel <- function(model,
 
 #' @rdname ci.merMod
 #' @export
-ci.DirichletRegModel <- function(x, ci = .95, component = c("all", "conditional", "precision"), ...) {
+ci.DirichletRegModel <- function(x,
+                                 ci = .95,
+                                 component = c("all", "conditional", "precision"),
+                                 ...) {
   component <- match.arg(component)
   params <- insight::get_parameters(x, component = component)
   out <- ci_wald(model = x, ci = ci, dof = Inf, ...)
@@ -61,7 +64,9 @@ ci.DirichletRegModel <- function(x, ci = .95, component = c("all", "conditional"
 
 #' @rdname standard_error
 #' @export
-standard_error.DirichletRegModel <- function(model, component = c("all", "conditional", "precision"), ...) {
+standard_error.DirichletRegModel <- function(model,
+                                             component = c("all", "conditional", "precision"),
+                                             ...) {
   component <- match.arg(component)
   params <- insight::get_parameters(model)
 
@@ -102,7 +107,9 @@ standard_error.DirichletRegModel <- function(model, component = c("all", "condit
 #' @importFrom stats pnorm
 #' @importFrom insight get_parameters
 #' @export
-p_value.DirichletRegModel <- function(model, component = c("all", "conditional", "precision"), ...) {
+p_value.DirichletRegModel <- function(model,
+                                      component = c("all", "conditional", "precision"),
+                                      ...) {
   component <- match.arg(component)
   params <- insight::get_parameters(model)
 

R/methods_averaging.R

@@ -15,7 +15,7 @@
 #'
 #' @examples
 #' library(parameters)
-#' if (require("brglm2")) {
+#' if (require("brglm2", quietly = TRUE)) {
 #'   data("stemcell")
 #'   model <- bracl(
 #'     research ~ as.numeric(religion) + gender,

R/methods_betareg.R

@@ -39,15 +39,20 @@ model_parameters.betareg <- function(model,
 
 #' @rdname ci.merMod
 #' @export
-ci.betareg <- function(x, ci = .95, component = c("all", "conditional", "precision"), ...) {
+ci.betareg <- function(x,
+                       ci = .95,
+                       component = c("all", "conditional", "precision"),
+                       ...) {
   component <- match.arg(component)
   ci_wald(model = x, ci = ci, dof = Inf, component = component)
 }
 
 
 #' @rdname standard_error
 #' @export
-standard_error.betareg <- function(model, component = c("all", "conditional", "precision"), ...) {
+standard_error.betareg <- function(model,
+                                   component = c("all", "conditional", "precision"),
+                                   ...) {
   component <- match.arg(component)
 
   params <- insight::get_parameters(model)
@@ -70,7 +75,9 @@ standard_error.betareg <- function(model, component = c("all", "conditional", "p
 
 #' @rdname p_value.DirichletRegModel
 #' @export
-p_value.betareg <- function(model, component = c("all", "conditional", "precision"), ...) {
+p_value.betareg <- function(model,
+                            component = c("all", "conditional", "precision"),
+                            ...) {
   component <- match.arg(component)
 
   params <- insight::get_parameters(model)
@@ -92,7 +99,10 @@ p_value.betareg <- function(model, component = c("all", "conditional", "precisio
 
 
 #' @export
-simulate_model.betareg <- function(model, iterations = 1000, component = c("all", "conditional", "precision"), ...) {
+simulate_model.betareg <- function(model,
+                                   iterations = 1000,
+                                   component = c("all", "conditional", "precision"),
+                                   ...) {
   component <- match.arg(component)
   out <- .simulate_model(model, iterations, component = component)
 

R/methods_cplm.R

@@ -120,10 +120,12 @@ standard_error.zcpglm <- function(model, component = c("all", "conditional", "zi
 #' @inheritParams standard_error
 #' @inheritParams ci.merMod
 #'
-#' @return A data frame with at least two columns: the parameter names and the p-values. Depending on the model, may also include columns for model components etc.
+#' @return A data frame with at least two columns: the parameter names and the
+#'   p-values. Depending on the model, may also include columns for model
+#'   components etc.
 #'
 #' @examples
-#' if (require("pscl")) {
+#' if (require("pscl", quietly = TRUE)) {
 #'   data("bioChemists")
 #'   model <- zeroinfl(art ~ fem + mar + kid5 | kid5 + phd, data = bioChemists)
 #'   p_value(model)

R/methods_epi2x2.R

@@ -38,4 +38,4 @@ model_parameters.epi.2by2 <- function(model, verbose = TRUE, ...) {
   attr(params, "pretty_names") <- stats::setNames(pretty_names, params$Parameter)
   class(params) <- c("parameters_model", "see_parameters_model", class(params))
   params
-}
+}

R/methods_gam.R

@@ -19,7 +19,12 @@ model_parameters.gam <- function(model,
 
   # Processing
   if (bootstrap) {
-    parameters <- bootstrap_parameters(model, iterations = iterations, ci = ci, ...)
+    parameters <- bootstrap_parameters(
+      model,
+      iterations = iterations,
+      ci = ci,
+      ...
+    )
   } else {
     parameters <-
       .extract_parameters_generic(

R/methods_glmmTMB.R

@@ -45,7 +45,12 @@ model_parameters.glmmTMB <- function(model,
   if (effects %in% c("fixed", "all")) {
     # Processing
     if (bootstrap) {
-      params <- bootstrap_parameters(model, iterations = iterations, ci = ci, ...)
+      params <- bootstrap_parameters(
+        model,
+        iterations = iterations,
+        ci = ci,
+        ...
+      )
     } else {
       params <- .extract_parameters_generic(
         model,

R/methods_lavaan.R

@@ -67,7 +67,7 @@ p_value.blavaan <- function(model, ...) {
 #' library(parameters)
 #'
 #' # lavaan -------------------------------------
-#' if (require("lavaan")) {
+#' if (require("lavaan", quietly = TRUE)) {
 #'
 #'   # Confirmatory Factor Analysis (CFA) ---------
 #'
@@ -102,8 +102,12 @@ p_value.blavaan <- function(model, ...) {
 #' @return A data frame of indices related to the model's parameters.
 #'
 #' @references \itemize{
-#'   \item Rosseel Y (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36.
-#'   \item Merkle EC , Rosseel Y (2018). blavaan: Bayesian Structural Equation Models via Parameter Expansion. Journal of Statistical Software, 85(4), 1-30. http://www.jstatsoft.org/v85/i04/
+#'   \item Rosseel Y (2012). lavaan: An R Package for Structural Equation
+#'   Modeling. Journal of Statistical Software, 48(2), 1-36.
+#'
+#'   \item Merkle EC , Rosseel Y (2018). blavaan: Bayesian Structural Equation
+#'   Models via Parameter Expansion. Journal of Statistical Software, 85(4),
+#'   1-30. http://www.jstatsoft.org/v85/i04/
 #' }
 #' @export
 model_parameters.lavaan <- function(model,
@@ -112,7 +116,12 @@ model_parameters.lavaan <- function(model,
                                     type = c("regression", "correlation", "loading", "defined"),
                                     verbose = TRUE,
                                     ...) {
-  params <- .extract_parameters_lavaan(model, ci = ci, standardize = standardize, verbose = verbose, ...)
+  params <- .extract_parameters_lavaan(model,
+    ci = ci,
+    standardize = standardize,
+    verbose = verbose,
+    ...
+  )
 
   # Filter
   if (all(type == "all")) {