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Question: does a mp object store anything related to vcov? #1249

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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
Type: Package
Package: parameters
Title: Processing of Model Parameters
Version: 0.29.2.5
Version: 0.29.2.6
Authors@R:
c(person(given = "Daniel",
family = "Lüdecke",
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1 change: 1 addition & 0 deletions R/1_model_parameters.R
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Expand Up @@ -732,6 +732,7 @@ model_parameters.default <- function(
p_adjust = p_adjust,
include_info = include_info,
effects = effects,
vcov = vcov,
verbose = verbose,
...
)
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1 change: 1 addition & 0 deletions R/methods_coxme.R
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Expand Up @@ -190,6 +190,7 @@ model_parameters.coxme <- function(
group_level = group_level,
effects = effects,
wb_component = wb_component,
vcov = vcov,
...
)

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1 change: 1 addition & 0 deletions R/methods_glmmTMB.R
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Expand Up @@ -357,6 +357,7 @@
include_info = include_info,
wb_component = wb_component,
modelinfo = modelinfo,
vcov = vcov,
...
)

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if (effects == "random") {
.se_random_effects_glmmTMB(model)
} else if (!is.null(vcov)) {

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GitHub Actions / lint-changed-files / lint-changed-files 

file=R/methods_glmmTMB.R,line=600,col=14,[if_not_else_linter] Prefer `if (A) x else y` to the less-readable `if (!A) y else x` in a simple if/else statement.
.se_robust_glmmTMB(model, component, vcov, vcov_args, verbose, ...)
} else {
.se_fixed_effects_glmmTMB(model, component, method, verbose)
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.se_robust_glmmTMB <- function(
model,
component = "all",
vcov,

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file=R/methods_glmmTMB.R,line=648,col=3,[function_argument_linter] Arguments without defaults should come before arguments with defaults.
vcov_args = NULL,
verbose = TRUE,
...
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3 changes: 2 additions & 1 deletion R/utils_model_parameters.R
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Expand Up @@ -4,7 +4,7 @@
#'
#' @keywords internal
#' @noRd
.add_model_parameters_attributes <- function(

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file=R/utils_model_parameters.R,line=7,col=1,[cyclocomp_linter] Reduce the cyclomatic complexity of this expression from 46 to at most 40. Consider replacing high-complexity sections like loops and branches with helper functions.
params,
model,
ci,
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attr(params, "bootstrap") <- bootstrap
attr(params, "iterations") <- iterations
attr(params, "p_adjust") <- p_adjust
attr(params, "robust_vcov") <- "vcov" %in% names(list(...))
attr(params, "robust_vcov") <- "vcov" %in% names(dot.arguments)
attr(params, "robust_vcov_type") <- dot.arguments$vcov
attr(params, "ignore_group") <- isFALSE(group_level)
attr(params, "ran_pars") <- isFALSE(group_level)
# some methods resolve the "grouplevel" alias into effects = "random" plus
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