summaryLevels

The function summaryLevels() produces a table with descriptive statistics for levels of a categorical variable, when those are saved as binary variables in different columns. It is largely based on the function gtsummary::tbl_summary(). The changes as compared to tbl_summary are:

Setup and data

To demonstrate the various functionalities of the function, we will create a small dataset. The factor of interest is ‘Site of progression’. For each site of progression, presence or absence is decoded in a separate column. In addition, we have a grouping variable called ‘arm’.

data<- as.data.frame(cbind(c(1:10), c("A","A","A","A","A","B","B","B","B","B"),
                            c("absent","present","absent","present","absent","absent","present","absent","present","absent"),
                            c("absent","absent","present","absent","absent","absent","absent","absent","absent","absent"),
                            c("present","absent","present","present","present","present","present","present","present","present")))
names(data)<-c("upn", "arm", "liver", "lung", "brain")

Basic table

Now, we use summarySCI::summaryLevels to collapse the columns ‘liver’, ‘lung’ and ‘brain’ into a single factor named ‘Site of progression’. The presence of each site of progression is decoded as ‘present’. We need to define the columns containing the factor levels using the vars argument.

summarySCI::summaryLevels(data=data,
                      vars = c("liver", "lung", "brain"),
                      label = "Site of progression",
                      levels= "present",)

Site of progression1	N = 102
liver	4 (40%)
lung	1 (10%)
brain	9 (90%)
1More than one entry possible
2n (%)

The footnote emphazises that a patient may have more than one site of progression. Therefore, the column percentages do not neccessarily add up to 100%.

By group

We can stratify the table by groups via the group argument. The overall column can still be shown if desired, using the overall = TRUE argument.

summarySCI::summaryLevels(data=data,
                      vars = c("liver", "lung", "brain"),
                      group = "arm",
                      label = "Site of progression",
                      levels= "present")

Site of progression1	A N = 52	B N = 52
liver	2 (40%)	2 (40%)
lung	1 (20%)	0 (0%)
brain	4 (80%)	5 (100%)
1More than one entry possible
2n (%)

summarySCI::summaryLevels(data=data,
                      vars = c("liver", "lung", "brain"),
                      group = "arm",
                      label = "Site of progression",
                      levels= "present",
                      overall = TRUE)

Site of progression1	Overall N = 102	A N = 52	B N = 52
liver	4 (40%)	2 (40%)	2 (40%)
lung	1 (10%)	1 (20%)	0 (0%)
brain	9 (90%)	4 (80%)	5 (100%)
1More than one entry possible
2n (%)

Performing a statistical test

A statistical test can be performed for each level separately when the argument test is set to TRUE. The type of test can be changed with the test_cat argument. Options include chisq.test, chisq.test.no.correct, fisher.test (default)

summarySCI::summaryLevels(data=data,
                      vars = c("liver", "lung", "brain"),
                      group = "arm",
                      label = "Site of progression",
                      test = TRUE,,
                      levels= "present")

Site of progression1	A N = 52	B N = 52	p-value3
liver	2 (40%)	2 (40%)	>0.99
lung	1 (20%)	0 (0%)	>0.99
brain	4 (80%)	5 (100%)	>0.99
1More than one entry possible
2n (%)
3Fisher's exact test

summarySCI::summaryLevels(data=data,
                      vars = c("liver", "lung", "brain"),
                      group = "arm",
                      levels= "present",
                      label = "Site of progression",
                      test = TRUE,
                      test_cat = "chisq.test")
#> The following warnings were returned during `add_p()`:
#> ! For variable `liver` (`arm`) and "statistic", "p.value", and "parameter"
#>   statistics: Chi-Quadrat-Approximation kann inkorrekt sein
#> The following warnings were returned during `add_p()`:
#> ! For variable `lung` (`arm`) and "statistic", "p.value", and "parameter"
#>   statistics: Chi-Quadrat-Approximation kann inkorrekt sein
#> The following warnings were returned during `add_p()`:
#> ! For variable `brain` (`arm`) and "statistic", "p.value", and "parameter"
#>   statistics: Chi-Quadrat-Approximation kann inkorrekt sein

Site of progression1	A N = 52	B N = 52	p-value3
liver	2 (40%)	2 (40%)	>0.99
lung	1 (20%)	0 (0%)	>0.99
brain	4 (80%)	5 (100%)	>0.99
1More than one entry possible
2n (%)
3Pearson's Chi-squared test

Add a confidence interval

A confidence interval can be added, if requested using the statement ci = TRUE. The confidence level can be adjusted by conf_level. The type of confidence interval can be chosen using the command ci_cat.

summarySCI::summaryLevels(data=data,
                      vars = c("liver", "lung", "brain"),
                      group = "arm",
                      label = "Site of progression",
                      levels= "present",
                      test = TRUE,
                      test_cat = "fisher.test",
                      ci=TRUE,
                      conf_level = 0.9,
                      overall = FALSE)