Stratified univariable regression

Fit univariable regression models within each level of a stratifier and combine the results into a stratified table rendered with gt or flextable.

Usage

stratified_uni_reg(
  data,
  outcome,
  exposures,
  stratifier,
  approach = "logit",
  format = c("flextable", "gt"),
  theme = c("minimal"),
  show_ref = TRUE
)

Arguments

data: A data frame containing the variables.
outcome: Character scalar; name of the outcome variable. Quoted and bare names are accepted.
exposures: Character vector of exposure variables to model. Quoted names are recommended in scripts, and bare names are also accepted.
stratifier: Character scalar; name of the stratifying variable. Quoted and bare names are accepted.
approach: Modeling approach. One of "logit", "firth", "logbinomial", "poisson", "robpoisson", "linear", or "negbin".
format: Output table format; one of "flextable" (default) or "gt".
theme: Table styling preset or theme primitives.
show_ref: Logical; if TRUE (default), display reference-category rows as "Ref.". If FALSE, hide reference rows; a message reminds users to use show_ref = TRUE when reference rows are needed.

Value

A list of class c("gtregression", "stratified_uni_reg", ...) with elements:

table: A rendered gt_tbl or flextable.
table_display: Display-ready wide stratified results.
per_stratum: List of complete uni_reg() results by stratum.
models: List of fitted model objects by stratum.
model_summaries: List of model summaries by stratum.
variable_labels: Named character vector of display labels used for exposure variables.
reg_check: Regression diagnostics by stratum.
by: The stratifier variable.
levels: Strata included in the analysis.
approach: The regression approach used.
format: The output format used.
source: Function identifier ("stratified_uni_reg").

Details

If exposure variables have a "label" attribute, for example from labelled::var_label(), those labels are used automatically in the displayed table. Internal matching still uses the original column names.

Accessors

$table: Rendered stratified regression table.
$table_display: Wide display data used to build the table.
$per_stratum: Full uni_reg() result objects by stratum.
$models: List of fitted model objects for each stratum.
$model_summaries: List of model summaries.
$reg_check: Diagnostic check results (when applicable).

Examples

birthwt_data <- data_birthwt |>
  transform(
    race = factor(race, levels = c(1, 2, 3),
                  labels = c("White", "Black", "Other")),
    smoke = factor(smoke, levels = c(0, 1), labels = c("No", "Yes")),
    low = factor(low, levels = c(0, 1),
                 labels = c("Normal BW", "Low BW"))
  )

stratified_uni <- stratified_uni_reg(
  data = birthwt_data,
  outcome = "low",
  exposures = c("age", "lwt", "smoke"),
  stratifier = "race",
  approach = "logit",
  format = "gt"
)
#> Running stratified univariate regression by: race
#>   > Stratum: race = White
#>   > Stratum: race = Black
#>   > Stratum: race = Other

stratified_uni$table


  Characteristic
      
        race = White
      
      
        race = Black
      
      
        race = Other
      
    
N
      OR (95% CI)
      p-value
      N
      OR (95% CI)
      p-value
      N
      OR (95% CI)
      p-value
    
age
96
0.95 (0.86–1.04)
0.226
26
1.05 (0.90–1.23)
0.526
67
0.94 (0.84–1.05)
0.297
lwt
96
0.98 (0.97–1.00)
0.123
26
0.99 (0.97–1.01)
0.517
67
0.97 (0.95–1.00)
0.056
smoke
96


26


67

  No

Ref.


Ref.


Ref.
  Yes

5.76 (1.78–18.60)
0.003

3.30 (0.63–17.16)
0.156

1.25 (0.35–4.46)
0.731
Abbreviations: OR = Odds Ratio; CI = Confidence Interval.
    
Ref. = reference category.