broom.helpers v1.0.0

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Helpers for Model Coefficients Tibbles

Provides suite of functions to work with regression model 'broom::tidy()' tibbles. The suite includes functions to group regression model terms by variable, insert reference and header rows for categorical variables, add variable labels, and more.

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broom.helpers

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The broom.helpers package provides suite of functions to work with regression model broom::tidy() tibbles. The suite includes functions to group regression model terms by variable, insert reference and header rows for categorical variables, add variable labels, and more.

Installation

This package is still experimental and under development.

To install it for testing purpose, use:

devtools::install_github("larmarange/broom.helpers")

Examples

all-in-one wrapper

mod1 <- lm(Sepal.Length ~ Sepal.Width + Species, data = iris)
library(broom.helpers)
mod1 %>% tidy_plus_plus()
#> # A tibble: 4 x 14
#>   term  variable var_label var_class var_type contrasts reference_row label
#>   <chr> <chr>    <chr>     <chr>     <chr>    <chr>     <lgl>         <chr>
#> 1 Sepa~ Sepal.W~ Sepal.Wi~ numeric   continu~ <NA>      NA            Sepa~
#> 2 Spec~ Species  Species   factor    categor~ contr.tr~ TRUE          seto~
#> 3 Spec~ Species  Species   factor    categor~ contr.tr~ FALSE         vers~
#> 4 Spec~ Species  Species   factor    categor~ contr.tr~ FALSE         virg~
#> # ... with 6 more variables: estimate <dbl>, std.error <dbl>, statistic <dbl>,
#> #   p.value <dbl>, conf.low <dbl>, conf.high <dbl>

mod2 <- glm(
  response ~ poly(age, 3) + stage + grade * trt,
  na.omit(gtsummary::trial),
  family = binomial,
  contrasts = list(
    stage = contr.treatment(4, base = 3),
    grade = contr.sum
  )
)
mod2 %>% 
  tidy_plus_plus(
    exponentiate = TRUE,
    variable_labels = c(age = "Age (in years)"),
    add_header_rows = TRUE,
    show_single_row = "trt"
  )
#> # A tibble: 17 x 15
#>    term  variable var_label var_class var_type header_row contrasts
#>    <chr> <chr>    <chr>     <chr>     <chr>    <lgl>      <chr>    
#>  1 <NA>  age      Age (in ~ nmatrix.3 continu~ TRUE       <NA>     
#>  2 poly~ age      Age (in ~ nmatrix.3 continu~ FALSE      <NA>     
#>  3 poly~ age      Age (in ~ nmatrix.3 continu~ FALSE      <NA>     
#>  4 poly~ age      Age (in ~ nmatrix.3 continu~ FALSE      <NA>     
#>  5 <NA>  stage    T Stage   factor    categor~ TRUE       contr.tr~
#>  6 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#>  7 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#>  8 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#>  9 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#> 10 <NA>  grade    Grade     factor    categor~ TRUE       contr.sum
#> 11 grad~ grade    Grade     factor    categor~ FALSE      contr.sum
#> 12 grad~ grade    Grade     factor    categor~ FALSE      contr.sum
#> 13 grad~ grade    Grade     factor    categor~ FALSE      contr.sum
#> 14 trtD~ trt      Chemothe~ character categor~ NA         contr.tr~
#> 15 <NA>  grade:t~ Grade * ~ <NA>      interac~ TRUE       <NA>     
#> 16 grad~ grade:t~ Grade * ~ <NA>      interac~ FALSE      <NA>     
#> 17 grad~ grade:t~ Grade * ~ <NA>      interac~ FALSE      <NA>     
#> # ... with 8 more variables: reference_row <lgl>, label <chr>, estimate <dbl>,
#> #   std.error <dbl>, statistic <dbl>, p.value <dbl>, conf.low <dbl>,
#> #   conf.high <dbl>

fine control

mod1 %>%
  # perform initial tidying of model
  tidy_and_attach() %>%
  # add reference row
  tidy_add_reference_rows() %>%
  # add term labels
  tidy_add_term_labels() %>%
  # remove intercept
  tidy_remove_intercept()
#> # A tibble: 4 x 12
#>   term  variable var_label var_class var_type contrasts reference_row label
#>   <chr> <chr>    <chr>     <chr>     <chr>    <chr>     <lgl>         <chr>
#> 1 Sepa~ Sepal.W~ Sepal.Wi~ numeric   continu~ <NA>      NA            Sepa~
#> 2 Spec~ Species  Species   factor    categor~ contr.tr~ TRUE          seto~
#> 3 Spec~ Species  Species   factor    categor~ contr.tr~ FALSE         vers~
#> 4 Spec~ Species  Species   factor    categor~ contr.tr~ FALSE         virg~
#> # ... with 4 more variables: estimate <dbl>, std.error <dbl>, statistic <dbl>,
#> #   p.value <dbl>

mod2 %>%
  # perform initial tidying of model
  tidy_and_attach(exponentiate = TRUE) %>%
  # add variable labels, including a custom value for age
  tidy_add_variable_labels(labels = c(age = "Age in years")) %>%
  # add reference rows for categorical variables
  tidy_add_reference_rows() %>%
  # add a, estimate value of reference terms
  tidy_add_estimate_to_reference_rows(exponentiate = TRUE) %>%
  # add header rows for categorical variables
  tidy_add_header_rows()
#> # A tibble: 20 x 13
#>    term  variable var_label var_class var_type header_row contrasts
#>    <chr> <chr>    <chr>     <chr>     <chr>    <lgl>      <chr>    
#>  1 (Int~ <NA>     (Interce~ <NA>      interce~ NA         <NA>     
#>  2 <NA>  age      Age in y~ nmatrix.3 continu~ TRUE       <NA>     
#>  3 poly~ age      Age in y~ nmatrix.3 continu~ FALSE      <NA>     
#>  4 poly~ age      Age in y~ nmatrix.3 continu~ FALSE      <NA>     
#>  5 poly~ age      Age in y~ nmatrix.3 continu~ FALSE      <NA>     
#>  6 <NA>  stage    T Stage   factor    categor~ TRUE       contr.tr~
#>  7 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#>  8 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#>  9 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#> 10 stag~ stage    T Stage   factor    categor~ FALSE      contr.tr~
#> 11 <NA>  grade    Grade     factor    categor~ TRUE       contr.sum
#> 12 grad~ grade    Grade     factor    categor~ FALSE      contr.sum
#> 13 grad~ grade    Grade     factor    categor~ FALSE      contr.sum
#> 14 grad~ grade    Grade     factor    categor~ FALSE      contr.sum
#> 15 <NA>  trt      Chemothe~ character categor~ TRUE       contr.tr~
#> 16 trtD~ trt      Chemothe~ character categor~ FALSE      contr.tr~
#> 17 trtD~ trt      Chemothe~ character categor~ FALSE      contr.tr~
#> 18 <NA>  grade:t~ Grade * ~ <NA>      interac~ TRUE       <NA>     
#> 19 grad~ grade:t~ Grade * ~ <NA>      interac~ FALSE      <NA>     
#> 20 grad~ grade:t~ Grade * ~ <NA>      interac~ FALSE      <NA>     
#> # ... with 6 more variables: reference_row <lgl>, label <chr>, estimate <dbl>,
#> #   std.error <dbl>, statistic <dbl>, p.value <dbl>

Functions in broom.helpers

Name Description
model_identify_variables Identify for each coefficient of a model the corresponding variable
model_get_model_frame Get the model frame of a model
model_get_xlevels Get xlevels used in the model
model_get_model_matrix Get the model matrix of a model
model_list_terms_levels List levels of categorical terms
tidy_add_contrasts Add contrasts type for categorical variables
model_get_contrasts Get contrasts used in the model
reexports Objects exported from other packages
model_list_contrasts List contrasts used by a model
tidy_add_estimate_to_reference_rows Add an estimate value to references rows for categorical variables
model_list_variables List all the variables used in a model
tidy_add_variable_labels Add variable labels
tidy_plus_plus Tidy a model and compute additional informations
tidy_identify_variables Identify the variable corresponding to each model coefficient
tidy_add_header_rows Add header rows variables with several terms
tidy_attach_model Attach a full model to the tibble of model terms
tidy_add_term_labels Add term labels
tidy_add_reference_rows Add references rows for categorical variables
tidy_remove_intercept Remove intercept(s)
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Vignettes of broom.helpers

Name
tidy.Rmd
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Details

License GPL-3
URL https://larmarange.github.io/broom.helpers/
BugReports https://github.com/larmarange/broom.helpers/issues
VignetteBuilder knitr
RdMacros lifecycle
Encoding UTF-8
LazyData true
RoxygenNote 7.1.1
NeedsCompilation no
Packaged 2020-09-11 11:22:18 UTC; josep
Repository CRAN
Date/Publication 2020-09-18 12:00:24 UTC

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