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Produce a data frame to summarise discrete variables coded as Yes/No

yn_table.Rd

Takes a data frame and produces the number and percentage for yes/no variables. Note that the denominator currently always excludes missing values.

Usage

yn_table(df = ., ..., group, time, digits = 1, total = TRUE, show_denom = TRUE)

Arguments

df

Data Frame

...

Variables to be summarised

group

Optional variable that defines the grouping

time

Optional variable for repeated measures (currently must me used with group)

digits

Number of digits to display percentages to, default is 1

total

Logical indicating whether a total column should be created

show_denom

Logical, should the denominator for each variable be shown. Default is TRUE.

Value

A tibble data frame summarising the data

Examples

yn_table(outcome, limp_yn, group = group)
#> # A tibble: 2 × 5
#>   variable scoring B              A              Total        
#>   <chr>    <chr>   <chr>          <chr>          <chr>        
#> 1 NA       NA      N = 324        N = 276        N = 600      
#> 2 limp_yn  ""      59/307 (19.2%) 54/258 (20.9%) 113/565 (20%)
yn_table(outcome, limp_yn, group = group, total = FALSE)
#> # A tibble: 2 × 4
#>   variable scoring B              A             
#>   <chr>    <chr>   <chr>          <chr>         
#> 1 NA       NA      N = 324        N = 276       
#> 2 limp_yn  ""      59/307 (19.2%) 54/258 (20.9%)
yn_table(outcome, limp_yn, show_denom = FALSE)
#> # A tibble: 2 × 3
#>   variable scoring value    
#>   <chr>    <chr>   <chr>    
#> 1 NA       NA      N = 600  
#> 2 limp_yn  ""      113 (20%)
yn_table(outcome, limp_yn, group = group, time = event_name, total = F)
#> # A tibble: 4 × 5
#>   variable event_name scoring B              A            
#>   <chr>    <chr>      <chr>   <chr>          <chr>        
#> 1 NA       NA         NA      N = 108        N = 92       
#> 2 limp_yn  Baseline   ""      19/100 (19%)   11/86 (12.8%)
#> 3 limp_yn  6 Weeks    ""      19/104 (18.3%) 26/86 (30.2%)
#> 4 limp_yn  12 Weeks   ""      21/103 (20.4%) 17/86 (19.8%)