* using log directory ‘/data/blackswan/ripley/R/packages/tests-devel/parameters.Rcheck’
* using R Under development (unstable) (2026-05-10 r90032)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (GCC) 14.2.1 20240912 (Red Hat 14.2.1-3)
    GNU Fortran (GCC) 14.2.1 20240912 (Red Hat 14.2.1-3)
* running under: Fedora Linux 40 (Workstation Edition)
* using session charset: UTF-8
* current time: 2026-05-10 14:46:43 UTC
* checking for file ‘parameters/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘parameters’ version ‘0.29.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘parameters’ can be installed ... [24s/24s] OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking whether startup messages can be suppressed ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [70s/72s] OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd line widths ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... [28s/28s] OK
* checking examples with --run-donttest ... [366s/380s] ERROR
Running examples in ‘parameters-Ex.R’ failed
The error most likely occurred in:

> ### Name: model_parameters.default
> ### Title: Parameters from (General) Linear Models
> ### Aliases: model_parameters.default
> 
> ### ** Examples
> 
> ## Don't show: 
> if (all(insight::check_if_installed(c("boot", "sandwich", "clubSandwich", "brglm2"), quietly = TRUE))) withAutoprint({ # examplesIf
+ ## End(Don't show)
+ library(parameters)
+ model <- lm(mpg ~ wt + cyl, data = mtcars)
+ 
+ model_parameters(model)
+ 
+ # bootstrapped parameters
+ model_parameters(model, bootstrap = TRUE)
+ 
+ # standardized parameters
+ model_parameters(model, standardize = "refit")
+ 
+ # robust, heteroskedasticity-consistent standard errors
+ model_parameters(model, vcov = "HC3")
+ 
+ model_parameters(model,
+   vcov = "vcovCL",
+   vcov_args = list(cluster = mtcars$cyl)
+ )
+ 
+ # different p-value style in output
+ model_parameters(model, p_digits = 5)
+ model_parameters(model, digits = 3, ci_digits = 4, p_digits = "scientific")
+ 
+ # report S-value or probability of direction for parameters
+ model_parameters(model, s_value = TRUE)
+ model_parameters(model, pd = TRUE)
+ 
+ ## No test: 
+ # logistic regression model
+ model <- glm(vs ~ wt + cyl, data = mtcars, family = "binomial")
+ model_parameters(model)
+ 
+ # show odds ratio / exponentiated coefficients
+ model_parameters(model, exponentiate = TRUE)
+ 
+ # bias-corrected logistic regression with penalized maximum likelihood
+ model <- glm(
+   vs ~ wt + cyl,
+   data = mtcars,
+   family = "binomial",
+   method = "brglmFit"
+ )
+ model_parameters(model)
+ ## End(No test)
+ ## Don't show: 
+ }) # examplesIf
> library(parameters)
> model <- lm(mpg ~ wt + cyl, data = mtcars)
> model_parameters(model)
Parameter   | Coefficient |   SE |         95% CI | t(29) |      p
------------------------------------------------------------------
(Intercept) |       39.69 | 1.71 | [36.18, 43.19] | 23.14 | < .001
wt          |       -3.19 | 0.76 | [-4.74, -1.64] | -4.22 | < .001
cyl         |       -1.51 | 0.41 | [-2.36, -0.66] | -3.64 | 0.001 

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model_parameters(model, bootstrap = TRUE)
Parameter   | Coefficient |         95% CI |      p
---------------------------------------------------
(Intercept) |       39.94 | [35.58, 44.01] | < .001
wt          |       -3.26 | [-4.89, -2.00] | < .001
cyl         |       -1.47 | [-2.22, -0.77] | < .001

Uncertainty intervals (equal-tailed) are naıve bootstrap intervals.
> model_parameters(model, standardize = "refit")
Parameter   | Coefficient |   SE |         95% CI |    t(29) |      p
---------------------------------------------------------------------
(Intercept) |    4.90e-17 | 0.08 | [-0.15,  0.15] | 6.50e-16 | > .999
wt          |       -0.52 | 0.12 | [-0.77, -0.27] |    -4.22 | < .001
cyl         |       -0.45 | 0.12 | [-0.70, -0.20] |    -3.64 | 0.001 

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model_parameters(model, vcov = "HC3")
Parameter   | Coefficient |   SE |         95% CI | t(29) |      p
------------------------------------------------------------------
(Intercept) |       39.69 | 2.30 | [34.97, 44.40] | 17.22 | < .001
wt          |       -3.19 | 0.78 | [-4.78, -1.60] | -4.10 | < .001
cyl         |       -1.51 | 0.39 | [-2.30, -0.72] | -3.90 | < .001

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model_parameters(model, vcov = "vcovCL", vcov_args = list(cluster = mtcars$cyl))
Parameter   | Coefficient |   SE |         95% CI | t(29) |      p
------------------------------------------------------------------
(Intercept) |       39.69 | 1.50 | [36.61, 42.76] | 26.43 | < .001
wt          |       -3.19 | 1.20 | [-5.65, -0.73] | -2.65 | 0.013 
cyl         |       -1.51 | 0.40 | [-2.32, -0.70] | -3.82 | < .001

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model_parameters(model, p_digits = 5)
Parameter   | Coefficient |   SE |         95% CI | t(29) |           p
-----------------------------------------------------------------------
(Intercept) |       39.69 | 1.71 | [36.18, 43.19] | 23.14 | 3.04318e-20
wt          |       -3.19 | 0.76 | [-4.74, -1.64] | -4.22 | 0.00022    
cyl         |       -1.51 | 0.41 | [-2.36, -0.66] | -3.64 | 0.00106    

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model_parameters(model, digits = 3, ci_digits = 4, p_digits = "scientific")
Parameter   | Coefficient |    SE |             95% CI |  t(29) |           p
-----------------------------------------------------------------------------
(Intercept) |      39.686 | 1.715 | [36.1787, 43.1938] | 23.141 | 3.04318e-20
wt          |      -3.191 | 0.757 | [-4.7390, -1.6429] | -4.216 | 2.22020e-04
cyl         |      -1.508 | 0.415 | [-2.3559, -0.6597] | -3.636 | 1.06428e-03

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model_parameters(model, s_value = TRUE)
Parameter   | Coefficient |   SE |         95% CI | t(29) |     s
-----------------------------------------------------------------
(Intercept) |       39.69 | 1.71 | [36.18, 43.19] | 23.14 | 64.83
wt          |       -3.19 | 0.76 | [-4.74, -1.64] | -4.22 | 12.14
cyl         |       -1.51 | 0.41 | [-2.36, -0.66] | -3.64 |  9.88

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model_parameters(model, pd = TRUE)
Parameter   | Coefficient |   SE |         95% CI | t(29) |      p |     pd
---------------------------------------------------------------------------
(Intercept) |       39.69 | 1.71 | [36.18, 43.19] | 23.14 | < .001 |   100%
wt          |       -3.19 | 0.76 | [-4.74, -1.64] | -4.22 | < .001 | 99.99%
cyl         |       -1.51 | 0.41 | [-2.36, -0.66] | -3.64 | 0.001  | 99.95%

Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
  using a Wald t-distribution approximation.
> model <- glm(vs ~ wt + cyl, data = mtcars, family = "binomial")
> model_parameters(model)
Parameter   | Log-Odds |   SE |         95% CI |     z |     p
--------------------------------------------------------------
(Intercept) |    10.62 | 4.17 | [ 4.79, 22.66] |  2.55 | 0.011
wt          |     2.10 | 1.55 | [-0.53,  6.24] |  1.36 | 0.174
cyl         |    -2.93 | 1.38 | [-6.92, -1.07] | -2.12 | 0.034

Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
  computed using a Wald z-distribution approximation.

The model has a log- or logit-link. Consider using `exponentiate =
  TRUE` to interpret coefficients as ratios.
  
Some coefficients seem to be rather large, which may indicate issues
  with (quasi) complete separation. Consider using bias-corrected or
  penalized regression models.
> model_parameters(model, exponentiate = TRUE)
Parameter   | Odds Ratio |       SE |             95% CI |     z |     p
------------------------------------------------------------------------
(Intercept) |   40911.34 | 1.71e+05 | [120.16, 6.95e+09] |  2.55 | 0.011
wt          |       8.17 |    12.63 | [  0.59,   514.10] |  1.36 | 0.174
cyl         |       0.05 |     0.07 | [  0.00,     0.34] | -2.12 | 0.034

Uncertainty intervals (profile-likelihood) and p-values (two-tailed)
  computed using a Wald z-distribution approximation.
> model <- glm(vs ~ wt + cyl, data = mtcars, family = "binomial", method = "brglmFit")
Error in brglmFit(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  : 
  could not find function "brglmFit"
Calls: withAutoprint ... source -> withVisible -> eval -> eval -> glm -> eval -> eval
Execution halted
Error while shutting down parallel: unable to terminate some child processes
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’ [121s/62s]
 [121s/63s] OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* checking for non-standard things in the check directory ... OK
* checking for detritus in the temp directory ... OK
* checking for new files in some other directories ... OK
* DONE

Status: 1 ERROR
See
  ‘/data/blackswan/ripley/R/packages/tests-devel/parameters.Rcheck/00check.log’
for details.

Command exited with non-zero status 1
Time 10:59.93, 629.94 + 71.36