compare_variables.md
In tern: Create Common TLGs Used in Clinical Trials

s_compare works for numeric

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  res
Output
   [1] "n"               "sum"             "mean"            "sd"             
   [5] "se"              "mean_sd"         "mean_se"         "mean_ci"        
   [9] "mean_sei"        "mean_sdi"        "mean_ci_3d"      "mean_pval"      
  [13] "median"          "mad"             "median_ci"       "median_ci_3d"   
  [17] "quantiles"       "iqr"             "range"           "min"            
  [21] "max"             "median_range"    "cv"              "geom_mean"      
  [25] "geom_sd"         "geom_mean_sd"    "geom_mean_ci"    "geom_cv"        
  [29] "geom_mean_ci_3d" "pval"

s_compare for numeric does not give p-value when not at least 2 values in each group

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Output
  numeric(0)

s_compare for factor works in usual case

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Output
  [1] "n"                       "count"                  
  [3] "count_fraction"          "count_fraction_fixed_dp"
  [5] "fraction"                "n_blq"                  
  [7] "pval_counts"

Code
  res
Output
  [1] 0.7659283

s_compare for factor handles explicit NAs as expected

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  res
Output
  [1] 0.7659283

Code
  res
Output
  [1] 0.9063036

s_compare for character works as expected

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  res
Output
  $n
  $n$n
  n 
  5


  $count
  $count$a
  count 
      3

  $count$b
  count 
      1

  $count$c
  count 
      1


  $count_fraction
  $count_fraction$a
  count     p 
    3.0   0.6

  $count_fraction$b
  count     p 
    1.0   0.2

  $count_fraction$c
  count     p 
    1.0   0.2


  $count_fraction_fixed_dp
  $count_fraction_fixed_dp$a
  count     p 
    3.0   0.6

  $count_fraction_fixed_dp$b
  count     p 
    1.0   0.2

  $count_fraction_fixed_dp$c
  count     p 
    1.0   0.2


  $fraction
  $fraction$a
    num denom 
      3     5

  $fraction$b
    num denom 
      1     5

  $fraction$c
    num denom 
      1     5


  $n_blq
  $n_blq$n_blq
  n_blq 
      0


  $pval_counts
  [1] 0.7659283

s_compare for logical works as expected

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  res
Output
  [1] 0.2702894

compare_vars works with default settings in rtables layout pipeline

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Output
                                   ARM B        ARM A        ARM C   
  ———————————————————————————————————————————————————————————————————
  AGE                                                                
    n                                73           69           58    
    Mean (SD)                    35.8 (7.1)   34.1 (6.8)   36.1 (7.4)
    p-value (t-test)                            0.1446       0.8212  
  SEX                                                                
    n                                73           69           58    
    F                            40 (54.8%)   38 (55.1%)   32 (55.2%)
    M                            33 (45.2%)   31 (44.9%)   26 (44.8%)
    p-value (chi-squared test)                  1.0000       1.0000

compare_vars works with custom settings

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Output
                                     ARM C            ARM A            ARM B     
  ———————————————————————————————————————————————————————————————————————————————
  AGE                                                                            
    Mean, SD                       36.1, 7.4        34.1, 6.8        35.8, 7.1   
    p-value (t-test)                                  0.1176           0.8212    
  SEX                                                                            
    F                            32.00 (55.17%)   38.00 (55.07%)   40.00 (54.79%)
    M                            26.00 (44.83%)   31.00 (44.93%)   33.00 (45.21%)
    p-value (chi-squared test)                        1.0000           1.0000

compare_vars 'na_str' argument works as expected

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Output
                                 ARM B       ARM A       ARM C  
  ——————————————————————————————————————————————————————————————
  n                               73          69          58    
  A: Drug X                        0       69 (100%)       0    
  B: Placebo                   73 (100%)       0           0    
  C: Combination                   0           0       58 (100%)
  p-value (chi-squared test)                   -           -