rm_uv_mv: Combine univariate and multivariable regression tables

In reportRmd: Tidy Presentation of Clinical Reporting

Combine univariate and multivariable regression tables

Description

This function will combine rm_uvsum and rm_mvsum outputs into a single table. The tableOnly argument must be set to TRUE when tables to be combined are created. The resulting table will be in the same order as the uvsum table and will contain the same columns as the uvsum and mvsum tables, but the p-values will be combined into a single column. There must be a variable overlapping between the uvsum and mvsum tables and all variables in the mvsum table must also appear in the uvsum table.

Usage

rm_uv_mv(
  uvsumTable,
  mvsumTable,
  covTitle = "",
  vif = FALSE,
  showN = FALSE,
  showEvent = FALSE,
  caption = NULL,
  tableOnly = FALSE,
  chunk_label,
  fontsize
)

Arguments

uvsumTable	Output from rm_uvsum, with tableOnly=TRUE
mvsumTable	Output from rm_mvsum, with tableOnly=TRUE
covTitle	character with the names of the covariate (predictor) column. The default is to leave this empty for output or, for table only output to use the column name 'Covariate'.
vif	boolean indicating if the variance inflation factor should be shown if present in the mvsumTable. Default is FALSE.
showN	boolean indicating if sample sizes should be displayed.
showEvent	boolean indicating if number of events (dichotomous outcomes) should be displayed.
caption	table caption
tableOnly	boolean indicating if unformatted table should be returned
chunk_label	only used if output is to Word to allow cross-referencing
fontsize	PDF/HTML output only, manually set the table fontsize

Value

A character vector of the table source code, unless tableOnly=TRUE in which case a data frame is returned

See Also

rm_uvsum,rm_mvsum

Examples

require(survival)
data("pembrolizumab")
uvTab <- rm_uvsum(response = c('os_time','os_status'),
covs=c('age','sex','baseline_ctdna','l_size','change_ctdna_group'),
data=pembrolizumab,tableOnly=TRUE)
mv_surv_fit <- coxph(Surv(os_time,os_status)~age+sex+
baseline_ctdna+l_size+change_ctdna_group, data=pembrolizumab)
uvTab <- rm_mvsum(mv_surv_fit)

#linear model
uvtab<-rm_uvsum(response = 'baseline_ctdna',
covs=c('age','sex','l_size','pdl1','tmb'),
data=pembrolizumab,tableOnly=TRUE)
lm_fit=lm(baseline_ctdna~age+sex+l_size+tmb,data=pembrolizumab)
mvtab<-rm_mvsum(lm_fit,tableOnly = TRUE)
rm_uv_mv(uvtab,mvtab,tableOnly=TRUE)

#logistic model
uvtab<-rm_uvsum(response = 'os_status',
covs=c('age','sex','l_size','pdl1','tmb'),
data=pembrolizumab,family = binomial,tableOnly=TRUE)
logis_fit<-glm(os_status~age+sex+l_size+pdl1+tmb,data = pembrolizumab,family = 'binomial')
mvtab<-rm_mvsum(logis_fit,tableOnly = TRUE)
rm_uv_mv(uvtab,mvtab,tableOnly=TRUE)

reportRmd documentation built on April 4, 2025, 2:03 a.m.