Adds the global p-value for a categorical variables in fmt_uni_regression objects

This function uses Anova from the car package with type = "III" to calculate global p-values.

# S3 method for fmt_uni_regression
add_global(x, ...)

Arguments

x	object with class fmt_uni_regression from the fmt_uni_regression function
...	arguments to be passed to Anova. Adding test.statistic = can change the type of test (e.g. Likelihood-ratio, Wald, etc.).

Examples

fmt_uni_regression(
  trial,
  method = "glm",
  y = "response",
  method.args = list(family = binomial),
  exponentiate = TRUE
) %>%
  add_global()
#> 
#> Variable                N                       OR                      95% CI                  p-value                
#> Treatment Randomization 191                                                                     0.011                  
#> Drug                                            Ref.                                                                   
#> Placebo                                         0.47                    0.26, 0.84                                     
#> Age, yrs                183                     1.00                    0.98, 1.02              >0.9                   
#> Marker Level, ng/mL     183                     0.92                    0.65, 1.30              0.6                    
#> T Stage                 191                                                                     0.055                  
#> T1                                              Ref.                                                                   
#> T2                                              1.40                    0.63, 3.14                                     
#> T3                                              0.63                    0.26, 1.50                                     
#> T4                                              0.50                    0.22, 1.11                                     
#> Grade                   191                                                                     0.4                    
#> I                                               Ref.                                                                   
#> II                                              0.60                    0.29, 1.25                                     
#> III                                             0.76                    0.38, 1.51