fix, lintr

R/1_model_parameters.R

@@ -576,14 +576,14 @@ model_parameters.default <- function(model,
       ci_method <- "quantile"
     }
 
-    args <- list(
+    fun_args <- list(
       model,
       iterations = iterations,
       ci = ci,
       ci_method = ci_method
     )
-    args <- c(args, dots)
-    params <- do.call("bootstrap_parameters", args)
+    fun_args <- c(fun_args, dots)
+    params <- do.call("bootstrap_parameters", fun_args)
 
     # Processing, non-bootstrapped parameters
   } else {
@@ -592,7 +592,7 @@ model_parameters.default <- function(model,
       ci_method <- "wald"
     }
 
-    args <- list(
+    fun_args <- list(
       model,
       ci = ci,
       component = component,
@@ -607,8 +607,8 @@ model_parameters.default <- function(model,
       vcov = vcov,
       vcov_args = vcov_args
     )
-    args <- c(args, dots)
-    params <- do.call(".extract_parameters_generic", args)
+    fun_args <- c(fun_args, dots)
+    params <- do.call(".extract_parameters_generic", fun_args)
   }
 
 
@@ -686,12 +686,12 @@ model_parameters.glm <- function(model,
   # tell user that profiled CIs don't respect vcov-args
   if (identical(ci_method, "profile") && (!is.null(vcov) || !is.null(vcov_args)) && isTRUE(verbose)) {
     insight::format_alert(
-      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.",
+      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.", # nolint
       "Use `ci_method=\"wald\"` to return confidence intervals based on robust standard errors."
     )
   }
 
-  args <- list(
+  fun_args <- list(
     model = model,
     ci = ci,
     ci_method = ci_method,
@@ -708,8 +708,8 @@ model_parameters.glm <- function(model,
     vcov_args = vcov_args,
     verbose = verbose
   )
-  args <- c(args, dots)
-  out <- do.call(".model_parameters_generic", args)
+  fun_args <- c(fun_args, dots)
+  out <- do.call(".model_parameters_generic", fun_args)
 
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out

R/3_p_value.R

@@ -105,13 +105,13 @@ p_value.default <- function(model,
     if (inherits(vcov, "data.frame") || "SE" %in% colnames(vcov)) {
       se <- vcov
     } else {
-      args <- list(model,
+      fun_args <- list(model,
         vcov_args = vcov_args,
         vcov = vcov,
         verbose = verbose
       )
-      args <- c(args, dots)
-      se <- do.call("standard_error", args)
+      fun_args <- c(fun_args, dots)
+      se <- do.call("standard_error", fun_args)
     }
 
     dof <- degrees_of_freedom(model, method = "wald", verbose = FALSE)

R/4_standard_error.R

@@ -88,8 +88,8 @@ standard_error.default <- function(model,
 
   # vcov: function which returns a matrix
   if (is.function(vcov)) {
-    args <- c(list(model), vcov_args, dots)
-    se <- .safe(sqrt(diag(do.call("vcov", args))))
+    fun_args <- c(list(model), vcov_args, dots)
+    se <- .safe(sqrt(diag(do.call("vcov", fun_args))))
   }
 
   # vcov: character (with backward compatibility for `robust = TRUE`)

R/ci_profile_boot.R

@@ -84,14 +84,14 @@
   dot_args <- .check_profile_uniroot_args(...)
 
   if (is.null(profiled)) {
-    args <- list(x, method = "profile", level = ci, dot_args)
-    out <- as.data.frame(do.call(stats::confint, args))
+    fun_args <- list(x, method = "profile", level = ci, dot_args)
+    out <- as.data.frame(do.call(stats::confint, fun_args))
   } else {
-    args <- list(profiled, level = ci, dot_args)
-    out <- .safe(as.data.frame(do.call(stats::confint, args)))
+    fun_args <- list(profiled, level = ci, dot_args)
+    out <- .safe(as.data.frame(do.call(stats::confint, fun_args)))
     if (is.null(out)) {
-      args <- list(x, method = "profile", level = ci, dot_args)
-      out <- as.data.frame(do.call(stats::confint, args))
+      fun_args <- list(x, method = "profile", level = ci, dot_args)
+      out <- as.data.frame(do.call(stats::confint, fun_args))
     }
   }
   .process_glmmTMB_CI(x, out, ci, component)
@@ -103,8 +103,8 @@
 .ci_uniroot_glmmTMB <- function(x, ci, component, ...) {
   # make sure "..." doesn't pass invalid arguments to package TMB
   dot_args <- .check_profile_uniroot_args(...)
-  args <- list(x, level = ci, method = "uniroot", dot_args)
-  out <- as.data.frame(do.call(stats::confint, args))
+  fun_args <- list(x, level = ci, method = "uniroot", dot_args)
+  out <- as.data.frame(do.call(stats::confint, fun_args))
   .process_glmmTMB_CI(x, out, ci, component)
 }
 

R/dominance_analysis.R

@@ -347,11 +347,10 @@ dominance_analysis <- function(model, sets = NULL, all = NULL,
 
   # quote arguments for domin
   for (arg in quote_args) {
-    if (!(arg %in% names(args))) {
-      insight::format_error(arg, " in `quote_args` not among arguments in model.")
+    if (arg %in% names(args)) {
+      args[[arg]] <- str2lang(paste0("quote(", deparse(args[[arg]]), ")", collapse = ""))
     } else {
-      args[[arg]] <-
-        str2lang(paste0("quote(", deparse(args[[arg]]), ")", collapse = ""))
+      insight::format_error(arg, " in `quote_args` not among arguments in model.")
     }
   }
 

R/methods_betareg.R

@@ -32,7 +32,7 @@ model_parameters.betareg <- function(model,
 
   ## TODO check merge by
 
-  args <- list(
+  fun_args <- list(
     model,
     ci = ci,
     component = component,
@@ -48,9 +48,9 @@ model_parameters.betareg <- function(model,
     vcov = NULL,
     vcov_args = NULL
   )
-  args <- c(args, dot_args)
+  fun_args <- c(fun_args, dot_args)
 
-  out <- do.call(".model_parameters_generic", args)
+  out <- do.call(".model_parameters_generic", fun_args)
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
 }

R/methods_brglm2.R

@@ -45,7 +45,7 @@ model_parameters.bracl <- function(model,
     merge_by <- "Parameter"
   }
 
-  args <- list(
+  fun_args <- list(
     model,
     ci = ci,
     bootstrap = bootstrap,
@@ -60,9 +60,9 @@ model_parameters.bracl <- function(model,
     vcov = NULL,
     vcov_args = NULL
   )
-  args <- c(args, dot_args)
+  fun_args <- c(fun_args, dot_args)
 
-  out <- do.call(".model_parameters_generic", args)
+  out <- do.call(".model_parameters_generic", fun_args)
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
 }

R/methods_car.R

@@ -37,7 +37,7 @@ model_parameters.deltaMethod <- function(model, p_adjust = NULL, verbose = TRUE,
     params <- .p_adjust(params, p_adjust, model, verbose)
   }
 
-  args <- list(
+  fun_args <- list(
     params,
     model,
     ci = ci,
@@ -49,9 +49,9 @@ model_parameters.deltaMethod <- function(model, p_adjust = NULL, verbose = TRUE,
     summary = FALSE,
     verbose = verbose
   )
-  args <- c(args, dots)
+  fun_args <- c(fun_args, dots)
 
-  params <- do.call(".add_model_parameters_attributes", args)
+  params <- do.call(".add_model_parameters_attributes", fun_args)
 
   class(params) <- c("parameters_model", "see_parameters_model", class(params))
   attr(params, "object_name") <- insight::safe_deparse_symbol(substitute(model))

R/methods_cgam.R

@@ -60,7 +60,7 @@ model_parameters.cgam <- function(model,
       ...
     )
   } else {
-    args <- list(
+    fun_args <- list(
       model,
       ci = ci,
       ci_method = ci_method,
@@ -74,8 +74,8 @@ model_parameters.cgam <- function(model,
       vcov = NULL,
       vcov_args = NULL
     )
-    args <- c(args, dot_args)
-    params <- do.call(".extract_parameters_generic", args)
+    fun_args <- c(fun_args, dot_args)
+    params <- do.call(".extract_parameters_generic", fun_args)
   }
 
   # fix statistic column

R/methods_glmmTMB.R

@@ -81,7 +81,7 @@ model_parameters.glmmTMB <- function(model,
         }
       }
     } else {
-      args <- list(
+      fun_args <- list(
         model,
         ci = ci,
         component = component,
@@ -100,8 +100,8 @@ model_parameters.glmmTMB <- function(model,
         wb_component = wb_component,
         summary = summary
       )
-      args <- c(args, dot_args)
-      params <- do.call(".extract_parameters_generic", args)
+      fun_args <- c(fun_args, dot_args)
+      params <- do.call(".extract_parameters_generic", fun_args)
     }
 
     # add dispersion parameter
@@ -131,7 +131,7 @@ model_parameters.glmmTMB <- function(model,
             if (verbose) {
               insight::format_alert(
                 "Cannot compute standard errors and confidence intervals for sigma parameter.",
-                "Your model may suffer from singularity (see '?lme4::isSingular' and '?performance::check_singularity')."
+                "Your model may suffer from singularity (see '?lme4::isSingular' and '?performance::check_singularity')." # nolint
               )
             }
             c(NA, NA)
@@ -157,7 +157,7 @@ model_parameters.glmmTMB <- function(model,
       params_random <- .extract_random_parameters(model, ci = ci, effects = effects, component = component)
       if (length(random_effects) > 1) {
         insight::format_alert(
-          "Cannot extract confidence intervals for random variance parameters from models with more than one grouping factor."
+          "Cannot extract confidence intervals for random variance parameters from models with more than one grouping factor." # nolint
         )
       }
     } else {

R/methods_hglm.R

@@ -223,13 +223,13 @@ p_value.hglm <- function(model,
                          ...) {
   dots <- list(...)
   dots$component <- NULL
-  args <- list(
+  fun_args <- list(
     model,
     dof = dof,
     component = "conditional",
     method = method,
     verbose = verbose
   )
-  args <- c(args, dots)
-  do.call("p_value.default", args)
+  fun_args <- c(fun_args, dots)
+  do.call("p_value.default", fun_args)
 }

R/methods_lme4.R

@@ -197,7 +197,7 @@ model_parameters.merMod <- function(model,
         }
       }
     } else {
-      args <- list(
+      fun_args <- list(
         model,
         ci = ci,
         ci_method = ci_method,
@@ -212,8 +212,8 @@ model_parameters.merMod <- function(model,
         vcov = vcov,
         vcov_args = vcov_args
       )
-      args <- c(args, dots)
-      params <- do.call(".extract_parameters_mixed", args)
+      fun_args <- c(fun_args, dots)
+      params <- do.call(".extract_parameters_mixed", fun_args)
     }
 
     params$Effects <- "fixed"
@@ -348,12 +348,12 @@ standard_error.merMod <- function(model,
   }
 
   if (!is.null(vcov) || isTRUE(dots[["robust"]])) {
-    args <- list(model,
+    fun_args <- list(model,
       vcov = vcov,
       vcov_args = vcov_args
     )
-    args <- c(args, dots)
-    out <- do.call("standard_error.default", args)
+    fun_args <- c(fun_args, dots)
+    out <- do.call("standard_error.default", fun_args)
     return(out)
   }
 

R/methods_mice.R

@@ -108,7 +108,7 @@ model_parameters.mipo <- function(model,
     merge_by <- "Parameter"
   }
 
-  args <- list(
+  fun_args <- list(
     model,
     ci = ci,
     merge_by = merge_by,
@@ -119,9 +119,9 @@ model_parameters.mipo <- function(model,
     vcov = NULL,
     vcov_args = NULL
   )
-  args <- c(args, dot_args)
+  fun_args <- c(fun_args, dot_args)
 
-  out <- do.call(".model_parameters_generic", args)
+  out <- do.call(".model_parameters_generic", fun_args)
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
 }

R/methods_nestedLogit.R

@@ -45,12 +45,12 @@ model_parameters.nestedLogit <- function(model,
   # tell user that profiled CIs don't respect vcov-args
   if (identical(ci_method, "profile") && (!is.null(vcov) || !is.null(vcov_args)) && isTRUE(verbose)) {
     insight::format_alert(
-      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.",
+      "When `ci_method=\"profile\"`, `vcov` only modifies standard errors, test-statistic and p-values, but not confidence intervals.", # nolint
       "Use `ci_method=\"wald\"` to return confidence intervals based on robust standard errors."
     )
   }
 
-  args <- list(
+  fun_args <- list(
     model = model,
     ci = ci,
     ci_method = ci_method,
@@ -67,8 +67,8 @@ model_parameters.nestedLogit <- function(model,
     vcov = vcov,
     vcov_args = vcov_args
   )
-  args <- c(args, dots)
-  out <- do.call(".model_parameters_generic", args)
+  fun_args <- c(fun_args, dots)
+  out <- do.call(".model_parameters_generic", fun_args)
 
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
   out
@@ -89,19 +89,17 @@ degrees_of_freedom.nestedLogit <- function(model,
     dof <- rep(vapply(model$models, stats::df.residual, numeric(1)), each = nrow(cf))
     if (!is.null(component) && !identical(component, "all")) {
       comp <- intersect(names(dof), component)
-      if (!length(comp)) {
+      if (length(comp)) {
+        dof <- dof[comp]
+      } else {
         if (verbose) {
-          insight::format_alert(
-            paste0(
-              "No matching model found. Possible values for `component` are ",
-              toString(paste0("'", names(model$models), "'")),
-              "."
-            )
-          )
+          insight::format_alert(paste0(
+            "No matching model found. Possible values for `component` are ",
+            toString(paste0("'", names(model$models), "'")),
+            "."
+          ))
         }
         dof <- Inf
-      } else {
-        dof <- dof[comp]
       }
     }
   } else {
@@ -128,8 +126,8 @@ standard_error.nestedLogit <- function(model,
 
   # vcov: function which returns a matrix
   if (is.function(vcov)) {
-    args <- c(list(model), vcov_args, dots)
-    se <- .safe(sqrt(diag(do.call("vcov", args))))
+    fun_args <- c(list(model), vcov_args, dots)
+    se <- .safe(sqrt(diag(do.call("vcov", fun_args))))
   }
 
   # vcov: character (with backward compatibility for `robust = TRUE`)