vignettes/inline_text.Rmd
inline_text.Rmd
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.
This vignette will walk a reader through the inline_text()
function, and the various functions available to modify and make additions. The inline.text()
function works with tables made using tbl_summary()
, tbl_regression()
, tbl_uvregression()
, and tbl_survival()
.
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).
tab1 < tbl_summary(trial2, by = trt) 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
}
Statistics presented: 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()
, tbl_uvregression()
, and tbl_survival()
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 m1 = glm(response ~ age + stage, trial, family = binomial(link = "logit"))
Now summarize the results with tbl_regression()
; exponentiate to get the odds ratios.
tbl_m1 < tbl_regression(m1, exponentiate = TRUE) tbl_m1
Characteristic  OR^{1}  95% CI^{1}  pvalue 

Age, yrs  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.
{estimate} primary estimate (e.g. model coefficient, odds ratio)
{conf.low} lower limit of confidence interval
{conf.high} upper limit of confidence interval
{p.value} pvalue
{conf.level} confidence level of interval
{N} 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.