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This function provides a convenience interface for generating generalizations of a 2-way frequency table. Row and column space can be facetted by variables, and an analysis function can be specified. The function then builds a layout with the specified layout and applies it to the data provided.

Usage

qtable_layout(
  data,
  row_vars = character(),
  col_vars = character(),
  avar = NULL,
  row_labels = NULL,
  afun = NULL,
  summarize_groups = FALSE,
  title = "",
  subtitles = character(),
  main_footer = character(),
  prov_footer = character(),
  show_colcounts = TRUE,
  drop_levels = TRUE,
  ...,
  .default_rlabel = NULL
)

qtable(
  data,
  row_vars = character(),
  col_vars = character(),
  avar = NULL,
  row_labels = NULL,
  afun = NULL,
  summarize_groups = FALSE,
  title = "",
  subtitles = character(),
  main_footer = character(),
  prov_footer = character(),
  show_colcounts = TRUE,
  drop_levels = TRUE,
  ...
)

Arguments

data

(data.frame)
the data to tabulate.

row_vars

(character)
the names of variables to be used in row facetting.

col_vars

(character)
the names of variables to be used in column facetting.

avar

(string)
the variable to be analyzed. Defaults to the first variable in data.

row_labels

(character or NULL)
row label(s) which should be applied to the analysis rows. Length must match the number of rows generated by afun.

afun

(function)
the function to generate the analysis row cell values. This can be a proper analysis function, or a function which returns a vector or list. Vectors are taken as multi-valued single cells, whereas lists are interpreted as multiple cells.

summarize_groups

(flag)
whether each level of nesting should include marginal summary rows. Defaults to FALSE.

title

(string)
single string to use as main title (formatters::main_title()). Ignored for subtables.

subtitles

(character)
a vector of strings to use as subtitles (formatters::subtitles()), where every element is printed on a separate line. Ignored for subtables.

(character)
a vector of strings to use as main global (non-referential) footer materials (formatters::main_footer()), where every element is printed on a separate line.

(character)
a vector of strings to use as provenance-related global footer materials (formatters::prov_footer()), where every element is printed on a separate line.

show_colcounts

(logical(1))
Indicates whether the lowest level of applied to data. NA, the default, indicates that the show_colcounts argument(s) passed to the relevant calls to split_cols_by* functions. Non-missing values will override the behavior specified in column splitting layout instructions which create the lowest level, or leaf, columns.

drop_levels

(flag)
whether unobserved factor levels should be dropped during facetting. Defaults to TRUE.

...

additional arguments passed to afun.

.default_rlabel

(string)
this is an implementation detail that should not be set by end users.

Value

  • qtable returns a built TableTree object representing the desired table

  • qtable_layout returns a PreDataTableLayouts object declaring the structure of the desired table, suitable for passing to build_table().

Details

This function creates a table with a single top-level structure in both row and column dimensions involving faceting by 0 or more variables in each dimension.

The display of the table depends on certain details of the tabulation. In the case of an afun which returns a single cell's contents (either a scalar or a vector of 2 or 3 elements), the label rows for the deepest-nested row facets will be hidden and the labels used there will be used as the analysis row labels. In the case of an afun which returns a list (corresponding to multiple cells), the names of the list will be used as the analysis row labels and the deepest-nested facet row labels will be visible.

The table will be annotated in the top-left area with an informative label displaying the analysis variable (avar), if set, and the function used (captured via substitute) where possible, or 'count' if not. One exception where the user may directly modify the top-left area (via row_labels) is the case of a table with row facets and an afun which returns a single row.

Examples

qtable(ex_adsl)
#>         all obs
#>         (N=400)
#> ———————————————
#> count     400  
qtable(ex_adsl, row_vars = "ARM")
#>                  all obs
#> count            (N=400)
#> ————————————————————————
#> A: Drug X          134  
#> B: Placebo         134  
#> C: Combination     132  
qtable(ex_adsl, col_vars = "ARM")
#>         A: Drug X   B: Placebo   C: Combination
#>          (N=134)     (N=134)        (N=132)    
#> ———————————————————————————————————————————————
#> count      134         134            132      
qtable(ex_adsl, row_vars = "SEX", col_vars = "ARM")
#>                    A: Drug X   B: Placebo   C: Combination
#> count               (N=134)     (N=134)        (N=132)    
#> ——————————————————————————————————————————————————————————
#> F                     79           77             66      
#> M                     51           55             60      
#> U                      3           2              4       
#> UNDIFFERENTIATED       1           0              2       
qtable(ex_adsl, row_vars = c("COUNTRY", "SEX"), col_vars = c("ARM", "STRATA1"))
#>                             A: Drug X                  B: Placebo               C: Combination     
#>                        A        B        C        A        B        C        A        B        C   
#> count                (N=38)   (N=47)   (N=49)   (N=44)   (N=45)   (N=45)   (N=40)   (N=43)   (N=49)
#> ———————————————————————————————————————————————————————————————————————————————————————————————————
#> CHN                                                                                                
#>   F                    11       15       18       12       15       18       8        9        12  
#>   M                    9        7        11       8        12       15       10       10       10  
#>   U                    1        0        1        1        0        0        1        0        2   
#>   UNDIFFERENTIATED     0        0        1        0        0        0        1        0        1   
#> USA                                                                                                
#>   F                    1        3        3        1        4        3        2        4        4   
#>   M                    1        2        0        3        1        1        1        3        3   
#> BRA                                                                                                
#>   F                    3        1        1        2        1        0        0        3        2   
#>   M                    1        7        0        4        0        0        2        3        0   
#> PAK                                                                                                
#>   F                    3        1        4        4        0        0        2        1        1   
#>   M                    2        1        1        2        2        1        1        3        2   
#> NGA                                                                                                
#>   F                    0        1        2        2        1        2        1        0        4   
#>   M                    2        1        1        0        1        1        4        1        1   
#>   U                    0        1        0        0        0        0        0        0        0   
#> RUS                                                                                                
#>   F                    0        2        2        2        1        2        1        1        2   
#>   M                    1        0        0        1        1        1        0        0        1   
#>   U                    0        0        0        0        0        0        0        1        0   
#> JPN                                                                                                
#>   F                    1        1        2        0        2        1        3        2        2   
#>   M                    0        1        0        0        0        0        1        0        1   
#>   U                    0        0        0        0        1        0        0        0        0   
#> GBR                                                                                                
#>   F                    1        0        1        0        2        0        0        1        0   
#>   M                    0        1        1        1        0        0        0        0        1   
#> CAN                                                                                                
#>   F                    1        1        0        1        1        0        1        0        0   
#>   M                    0        1        0        0        0        0        1        1        0   
qtable(ex_adsl,
  row_vars = c("COUNTRY", "SEX"),
  col_vars = c("ARM", "STRATA1"), avar = "AGE", afun = mean
)
#>                             A: Drug X                  B: Placebo               C: Combination     
#>                        A        B        C        A        B        C        A        B        C   
#> AGE - mean           (N=38)   (N=47)   (N=49)   (N=44)   (N=45)   (N=45)   (N=40)   (N=43)   (N=49)
#> ———————————————————————————————————————————————————————————————————————————————————————————————————
#> CHN                                                                                                
#>   F                  31.09    30.67    32.56    33.08    35.73    35.28    35.25    33.89    35.75 
#>   M                  34.44    36.43    35.73    38.38    35.25    37.60    30.80    35.20    38.60 
#>   U                  33.00      NA     34.00    27.00      NA       NA     38.00      NA     33.00 
#>   UNDIFFERENTIATED     NA       NA     28.00      NA       NA       NA     44.00      NA     46.00 
#> USA                                                                                                
#>   F                  24.00    38.00    35.00    46.00    40.75    32.33    36.50    30.50    36.00 
#>   M                  40.00    34.50      NA     38.67    53.00    30.00    47.00    38.00    29.00 
#> BRA                                                                                                
#>   F                  35.33    38.00    44.00    27.50    25.00      NA       NA     46.33    33.00 
#>   M                  43.00    35.14      NA     36.00      NA       NA     28.50    40.33      NA  
#> PAK                                                                                                
#>   F                  28.00    38.00    29.50    30.75      NA       NA     33.00    23.00    49.00 
#>   M                  39.00    37.00    31.00    41.50    28.50    33.00    40.00    35.33    35.50 
#> NGA                                                                                                
#>   F                    NA     25.00    35.00    26.50    37.00    32.00    31.00      NA     32.75 
#>   M                  29.50    29.00    50.00      NA     40.00    24.00    34.50    32.00    28.00 
#>   U                    NA     28.00      NA       NA       NA       NA       NA       NA       NA  
#> RUS                                                                                                
#>   F                    NA     36.50    39.50    31.00    36.00    39.50    30.00    44.00    26.00 
#>   M                  40.00      NA       NA     36.00    58.00    29.00      NA       NA     28.00 
#>   U                    NA       NA       NA       NA       NA       NA       NA     37.00      NA  
#> JPN                                                                                                
#>   F                  29.00    34.00    37.50      NA     29.00    28.00    32.33    47.50    34.00 
#>   M                    NA     48.00      NA       NA       NA       NA     45.00      NA     26.00 
#>   U                    NA       NA       NA       NA     35.00      NA       NA       NA       NA  
#> GBR                                                                                                
#>   F                  28.00      NA     36.00      NA     28.00      NA       NA     40.00      NA  
#>   M                    NA     27.00    28.00    62.00      NA       NA       NA       NA     69.00 
#> CAN                                                                                                
#>   F                  41.00    39.00      NA     34.00    43.00      NA     37.00      NA       NA  
#>   M                    NA     31.00      NA       NA       NA       NA     36.00    32.00      NA  
summary_list <- function(x, ...) as.list(summary(x))
qtable(ex_adsl, row_vars = "SEX", col_vars = "ARM", avar = "AGE", afun = summary_list)
#>                      A: Drug X   B: Placebo   C: Combination
#> AGE - summary_list    (N=134)     (N=134)        (N=132)    
#> ————————————————————————————————————————————————————————————
#> F                                                           
#>   Min.                 21.00       23.00          21.00     
#>   1st Qu.              28.00       29.00          31.25     
#>   Median               32.00       32.00          35.00     
#>   Mean                 32.76       34.12          35.20     
#>   3rd Qu.              37.00       37.00          38.00     
#>   Max.                 47.00       58.00          64.00     
#> M                                                           
#>   Min.                 23.00       21.00          20.00     
#>   1st Qu.              29.50       32.50          29.00     
#>   Median               37.00       37.00          33.50     
#>   Mean                 35.57       37.44          35.38     
#>   3rd Qu.              40.50       41.50          40.00     
#>   Max.                 50.00       62.00          69.00     
#> U                                                           
#>   Min.                 28.00       27.00          31.00     
#>   1st Qu.              30.50       29.00          34.00     
#>   Median               33.00       31.00          36.00     
#>   Mean                 31.67       31.00          35.25     
#>   3rd Qu.              33.50       33.00          37.25     
#>   Max.                 34.00       35.00          38.00     
#> UNDIFFERENTIATED                                            
#>   Min.                 28.00         NA           44.00     
#>   1st Qu.              28.00         NA           44.50     
#>   Median               28.00         NA           45.00     
#>   Mean                 28.00         NA           45.00     
#>   3rd Qu.              28.00         NA           45.50     
#>   Max.                 28.00         NA           46.00     
suppressWarnings(qtable(ex_adsl,
  row_vars = "SEX",
  col_vars = "ARM", avar = "AGE", afun = range
))
#>                     A: Drug X    B: Placebo    C: Combination
#> AGE - range          (N=134)       (N=134)        (N=132)    
#> —————————————————————————————————————————————————————————————
#> F                  21.0 / 47.0   23.0 / 58.0    21.0 / 64.0  
#> M                  23.0 / 50.0   21.0 / 62.0    20.0 / 69.0  
#> U                  28.0 / 34.0   27.0 / 35.0    31.0 / 38.0  
#> UNDIFFERENTIATED   28.0 / 28.0   Inf / -Inf     44.0 / 46.0