18  Univariate regressions, reported as a table

18.1 Univariate Regressions - reported as a table

The tbl_uvregression() function produces a table of univariate regression models. The function is a wrapper for tbl_regression(), and as a result, accepts nearly identical function arguments. The function’s results can be modified in similar ways to tbl_regression().

This example uses the built-in trial data set

library (gtsummary)
library(tidyverse)
library(knitr)

Show the data set

kable(head(trial,50))

trt	age	marker	stage	grade	response	death	ttdeath
Drug A	23	0.160	T1	II	0	0	24.00
Drug B	9	1.107	T2	I	1	0	24.00
Drug A	31	0.277	T1	II	0	0	24.00
Drug A	NA	2.067	T3	III	1	1	17.64
Drug A	51	2.767	T4	III	1	1	16.43
Drug B	39	0.613	T4	I	0	1	15.64
Drug A	37	0.354	T1	II	0	0	24.00
Drug A	32	1.739	T1	I	0	1	18.43
Drug A	31	0.144	T1	II	0	0	24.00
Drug B	34	0.205	T3	I	0	1	10.53
Drug B	42	0.513	T1	III	0	0	24.00
Drug B	63	0.060	T3	I	1	0	24.00
Drug B	54	0.831	T4	III	0	1	14.34
Drug B	21	0.258	T4	I	0	1	12.89
Drug B	48	0.128	T1	I	0	1	22.68
Drug B	71	0.445	T4	III	0	1	8.71
Drug A	38	2.083	T4	III	1	0	24.00
Drug B	49	0.157	T2	II	0	1	15.21
Drug A	57	0.066	T1	III	0	0	24.00
Drug A	46	0.325	T1	II	0	0	24.00
Drug A	47	0.266	T2	I	0	0	24.00
Drug A	52	0.719	T2	II	0	0	24.00
Drug A	61	1.713	T4	I	0	1	16.92
Drug A	38	0.096	T4	I	0	1	23.89
Drug B	34	0.105	T4	II	0	1	6.32
Drug B	49	0.043	T2	III	0	1	15.77
Drug A	63	0.981	T4	II	1	0	24.00
Drug B	67	1.156	T1	II	0	0	24.00
Drug B	68	0.105	T4	II	0	1	15.45
Drug A	78	0.175	T3	I	1	1	17.43
Drug B	36	0.309	T1	III	1	0	24.00
Drug A	37	1.869	T2	II	0	1	20.90
Drug B	53	2.008	T3	I	0	0	24.00
Drug A	36	1.894	T3	I	1	0	24.00
Drug A	51	0.160	T3	I	0	0	24.00
Drug A	48	1.209	T3	III	NA	1	21.19
Drug B	57	0.108	T1	II	0	1	12.52
Drug A	31	0.611	T1	II	1	0	24.00
Drug B	37	0.222	T4	III	0	1	15.59
Drug B	28	0.803	T4	II	0	1	18.00
Drug B	40	0.370	T3	II	0	1	18.02
Drug B	49	NA	T1	III	1	1	12.43
Drug A	61	0.177	T4	III	0	1	12.10
Drug B	56	1.479	T3	I	1	0	24.00
Drug A	54	0.161	T4	III	1	1	17.42
Drug B	71	0.737	T1	I	1	0	24.00
Drug A	38	0.124	T1	III	1	0	24.00
Drug B	31	0.092	T2	II	0	0	24.00
Drug B	48	0.385	T1	II	0	1	12.19
Drug B	NA	0.210	T4	II	0	1	10.02

Perform univariate analyses

trial %>%

  select(response, age, grade) %>%

  tbl_uvregression(
    method = glm,
    y = response,
    method.args = list(family = binomial),
    exponentiate = TRUE,
    pvalue_fun = ~style_pvalue(.x, digits = 2)
  ) %>%
  add_global_p() %>%  # add global p-value 
  add_nevent() %>%    # add number of events of the outcome
  add_q() %>%         # adjusts global p-values for multiple testing
  bold_p() %>%        # bold p-values under a given threshold (default 0.05)
  bold_p(t = 0.10, q = TRUE) %>% # now bold q-values under the threshold of 0.10
  bold_labels()

Characteristic	N	Event N	OR1	95% CI1	p-value	q-value2
Age	183	58	1.02	1.00, 1.04	0.091	0.18
Grade	193	61			0.93	0.93
I			—	—
II			0.95	0.45, 2.00
III			1.10	0.52, 2.29
1 OR = Odds Ratio, CI = Confidence Interval
2 False discovery rate correction for multiple testing