crosstable

Let’s start with crosstable, the package that requires the least amount of code and has good default settings. In its simplest form, the code for this package couldn’t be shorter:

crosstable(df) 

## # A tibble: 13 × 4
##    .id       label     variable   value           
##    <chr>     <chr>     <chr>      <chr>           
##  1 age       age       Min / Max  13.0 / 71.0     
##  2 age       age       Med [IQR]  26.0 [24.0;29.0]
##  3 age       age       Mean (std) 28.8 (9.3)      
##  4 age       age       N (NA)     377 (1)         
##  5 gender    gender    1          269 (71.16%)    
##  6 gender    gender    2          109 (28.84%)    
##  7 student   student   1          229 (61.07%)    
##  8 student   student   2          146 (38.93%)    
##  9 student   student   NA         3               
## 10 condition condition 1          94 (24.87%)     
## 11 condition condition 2          91 (24.07%)     
## 12 condition condition 3          101 (26.72%)    
## 13 condition condition 4          92 (24.34%)

By default, crosstable displays the table in the console. A nicer output (e.g., for websites or R Studio’s viewer) can be obtained via knitr::kable(). Grouping the data by a column (here the experimental condition) is also easy.

crosstable(df, by = "condition") %>% 
  select(-".id") %>% # remove first column
  # optimize formatting for web display (table looks better without next line)
  knitr::kable()

With the following code, it is also possible to save the table as a Word file (see here and here).

# Specify properties for the target document
library(officer)
sect_properties <- prop_section(
  page_size(width = 21, height = 29.7, orient = "portrait"),
  type = "continuous",
  page_margins = page_mar())

# create table
df %>% 
  crosstable::crosstable(by = "condition") %>%
  # needs to be a flex_table 
  crosstable::as_flextable() %>% 
  # use flextable package to save table as word
  flextable::save_as_docx(path = "descriptives_crosstable.docx", pr_section = sect_properties)

# for more details about last step, see https://davidgohel.github.io/flextable/reference/save_as_docx.html

gtsummary

There is also a very quick way to get a descriptive table with the package gtsummary:

df %>% 
  gtsummary::tbl_summary() %>% 
  # for nicer display on website
  gtsummary::as_kable()

The information for the categorical / ordinal variables looks fine (frequencies and percentages). However, for interval scale variables such as age I’d rather have the mean and standard deviation than the median and the interquartile range. The “by” command can be used to summarize the data by group.

df %>% 
  gtsummary::tbl_summary( 
    by = condition,
    statistic = list(age = "{mean} ({sd})")) %>%
  # for nicer display on website
  gtsummary::as_kable()

This is how gtsummary saves tables as Word files:

# set documents properties
library(officer)
sect_properties <- prop_section(
  page_size(width = 21, height = 29.7, orient = "portrait"),
  type = "continuous",
  page_margins = page_mar()
)

df %>% 
  gtsummary::tbl_summary( 
    by = condition,
    statistic = list(age = "{mean} ({sd})")) %>% 
  # this changes the table to a different format that can be saved as Word
  as_flex_table() %>% 
  # use flextable package to save table as word
  flextable::save_as_docx(path = "descriptives_gtsummary.docx", pr_section = sect_properties)
# for more details about last step, see https://davidgohel.github.io/flextable/reference/save_as_docx.html

To the best of my knowledge, gtsummary is the only package that can export tables as Excel files:

df %>% 
  gtsummary::tbl_summary( 
    by = condition,
    statistic = list(age = "{mean} ({sd})"),
    digits = all_continuous() ~ 2) %>% 
  # export to Excel
  as_hux_xlsx("descriptives_gtsummary.xlsx") 

arsenal

arsenal also exports tables as Word files but requires a bit more coding. For instance, it is necessary to specify all the variables to include in the table. Note that by default arsenal shows the total and performs statistical tests when comparing groups (this can be turned off, though).

# create table
arsenal::tableby(condition~ age + gender + student, 
                 data = df, 
                 total = FALSE, # don't show column with total numbers
                 test = FALSE) %>% # don't perform test for group comparisons
  # display table  
  summary()

Saving the table as word file should be simple. However, for reasons unknown to me this doesn’t always work on my computer.

# save table as Word document  
descriptives <- arsenal::tableby(condition~ age + gender + student, data = df) 
arsenal::write2word(descriptives, "descriptives_arsenal.docx", title = "My table",
                    quiet = TRUE) # to suppress the command line output

table1

table1 is another package that requires only little code to create a descriptive table. Group-comparisons are easy (specify grouping variable with “|”). Unfortunately, I couldn’t figure out how to render the table on the website.

# not working on server
table1::table1(~age + gender + student | condition, data = df) 

table1 has its own function t1flex to convert the table into a flextable object, which can then be conveniently be saved as a Word file.

descriptive_table <- table1::table1(~age + gender + student | condition, data = df) 
# convert to flextable and save
table1::t1flex(descriptive_table) %>% 
  flextable::save_as_docx(path="descriptives_table1.docx",pr_section = sect_properties) # see previous sections for how to define "sect_properties"

tableone

tableone also requires only little code to create a descriptive table. strata can be used to group the data by a column. By default, tableone omits one level of categorical variables. If you want to see all levels, you need to change this manually (showAllLevels = TRUE). Note that when comparing groups, the default is to also conduct a statistical test (this can be turned off, though).

tableone::CreateTableOne(vars = c("age", "gender", "student"), 
                         data = df, strata = "condition",
                         test = FALSE) %>% # don't perform test for group comparison
  print(showAllLevels = TRUE) %>% 
  # use kableone for nicer display
  tableone::kableone()

tableone doesn’t offer a direct way to export tables as Word files. However, with some additional code (partially taken from here) the table can be converted into a flextable object and then be saved as a Word file.

(Note that tableone can also prepare the table in a way that makes it easy to copy-and-paste to Excel (look for “quote = TRUE” here and here.)

# save as word by using the print function and by converting the table to a flextable 
descriptives_tableone <- tableone::CreateTableOne(data = df, strata = "condition")
descriptives_tableone <- print(descriptives_tableone,printToggle = FALSE)
descriptives_tableone %>% 
  as.data.frame() %>% 
  rownames_to_column("Variables") %>%
  flextable() %>%
  flextable::save_as_docx(path = "descriptives_tableone.docx", pr_section = sect_properties) # see previous sections for how to define "sect_properties"

furniture

Another package that quickly generates descriptive tables is furniture.

furniture::table1(df, age, gender, student, splitby = ~condition) %>% 
  # for some reason this only works if the object is converted 
  kableExtra::kable()

When passed on to flextable, tables can be saved as Word files.

furniture::table1(df, age, gender, student, splitby = ~condition) %>% 
  as.data.frame() %>% 
  flextable() %>%
  flextable::save_as_docx(path="descriptives_furniture.docx",pr_section = sect_properties) # see previous sections for how to define "sect_properties"