Reproducible reports are an important part of good practices. We often need to report the results from a table in the text of an R markdown report. Inline reporting has been made simple with inline_text()
. The inline_text()
function reports statistics from {gtsummary} tables inline in an R markdown report.
Before going through the tutorial, install and load {gtsummary}.
# install.packages("gtsummary")
library(gtsummary)
We’ll be using the trial
data set throughout this example.
For brevity in the tutorial, let’s keep a subset of the variables from the trial data set.
<
trial2 %>%
trial select(trt, marker, stage)
First create a basic summary table using tbl_summary()
(review tbl_summary()
vignette for detailed overview of this function if needed).
< tbl_summary(trial2, by = trt)
tab1 tab1
Characteristic  Drug A, N = 98^{1}  Drug B, N = 102^{1} 

Marker Level (ng/mL)  0.84 (0.24, 1.57)  0.52 (0.19, 1.20) 
Unknown  6  4 
T Stage  
T1  28 (29%)  25 (25%) 
T2  25 (26%)  29 (28%) 
T3  22 (22%)  21 (21%) 
T4  23 (23%)  27 (26%) 
^{
1
}
Median (IQR); n (%)

To report the median (IQR) of the marker levels in each group, use the following commands inline.
The median (IQR) marker level in the Drug A and Drug B groups are
`r inline_text(tab1, variable = marker, column = "Drug A")`
and`r inline_text(tab1, variable = marker, column = "Drug B")`
, respectively.
Here’s how the line will appear in your report.
The median (IQR) marker level in the Drug A and Drug B groups are 0.84 (0.24, 1.57) and 0.52 (0.19, 1.20), respectively.
If you display a statistic from a categorical variable, include the level
argument.
`r inline_text(tab1, variable = stage, level = "T1", column = "Drug B")`
resolves to “25 (25%)”
Similar syntax is used to report results from tbl_regression()
and tbl_uvregression()
tables. Refer to the tbl_regression()
vignette if you need detailed guidance on using these functions.
Let’s first create a regression model.
# build logistic regression model
< glm(response ~ age + stage, trial, family = binomial(link = "logit")) m1
Now summarize the results with tbl_regression()
; exponentiate to get the odds ratios.
< tbl_regression(m1, exponentiate = TRUE)
tbl_m1 tbl_m1
Characteristic  OR^{1}  95% CI^{1}  pvalue 

Age  1.02  1.00, 1.04  0.091 
T Stage  
T1  —  —  
T2  0.58  0.24, 1.37  0.2 
T3  0.94  0.39, 2.28  0.9 
T4  0.79  0.33, 1.90  0.6 
^{
1
}
OR = Odds Ratio, CI = Confidence Interval

To report the result for age
, use the following commands inline.
`r inline_text(tbl_m1, variable = age)`
Here’s how the line will appear in your report.
1.02 (95% CI 1.00, 1.04; p=0.091)
It is reasonable that you’ll need to modify the text. To do this, use the pattern
argument. The pattern
argument syntax follows glue::glue()
format with referenced R objects being inserted between curly brackets. The default is pattern = "{estimate} ({conf.level*100}% CI {conf.low}, {conf.high}; {p.value})"
. You have access the to following fields within the pattern
argument.
Parameter  Description 


primary estimate (e.g. model coefficient, odds ratio) 

lower limit of confidence interval 

upper limit of confidence interval 

pvalue 

confidence level of interval 

number of observations 
Age was not significantly associated with tumor response
`r inline_text(tbl_m1, variable = age, pattern = "(OR {estimate}; 95% CI {conf.low}, {conf.high}; {p.value})")`
.
Age was not significantly associated with tumor response (OR 1.02; 95% CI 1.00, 1.04; p=0.091).
If you’re printing results from a categorical variable, include the level
argument, e.g. inline_text(tbl_m1, variable = stage, level = "T3")
resolves to “0.94 (95% CI 0.39, 2.28; p=0.9)”.
The inline_text
function has arguments for rounding the pvalue (pvalue_fun
) and the coefficients and confidence interval (estimate_fun
). These default to the same rounding performed in the table, but can be modified when reporting inline.
For more details about inline code, review to the RStudio documentation page.