pairwise_comparisons_within.md
In pairwiseComparisons: Multiple Pairwise Comparison Tests

`pairwise_comparisons()` works for within-subjects design - NAs

Code
  list(df1, df2, df3)
Output
  [[1]]
  # A tibble: 6 x 6
    group1 group2  p.value test.details     p.value.adjustment
    <chr>  <chr>     <dbl> <chr>            <chr>             
  1 HDHF   HDLF   3.18e- 3 Student's t-test Bonferroni        
  2 HDHF   LDHF   4.21e- 1 Student's t-test Bonferroni        
  3 HDHF   LDLF   3.95e-12 Student's t-test Bonferroni        
  4 HDLF   LDHF   3.37e- 1 Student's t-test Bonferroni        
  5 HDLF   LDLF   7.94e- 3 Student's t-test Bonferroni        
  6 LDHF   LDLF   1.33e- 8 Student's t-test Bonferroni        
    label                                           
    <chr>                                           
  1 list(~italic(p)[Bonferroni-corrected]==0.003)   
  2 list(~italic(p)[Bonferroni-corrected]==0.421)   
  3 list(~italic(p)[Bonferroni-corrected]==3.95e-12)
  4 list(~italic(p)[Bonferroni-corrected]==0.337)   
  5 list(~italic(p)[Bonferroni-corrected]==0.008)   
  6 list(~italic(p)[Bonferroni-corrected]==1.33e-08)

  [[2]]
  # A tibble: 6 x 11
    group1 group2 statistic  p.value alternative
    <chr>  <chr>      <dbl>    <dbl> <chr>      
  1 HDHF   HDLF        4.78 1.44e- 5 two.sided  
  2 HDHF   LDHF        2.44 4.47e- 2 two.sided  
  3 HDHF   LDLF        8.01 5.45e-13 two.sided  
  4 HDLF   LDHF        2.34 4.96e- 2 two.sided  
  5 HDLF   LDLF        3.23 5.05e- 3 two.sided  
  6 LDHF   LDLF        5.57 4.64e- 7 two.sided  
    method                                                                
    <chr>                                                                 
  1 Durbin's all-pairs test for a two-way balanced incomplete block design
  2 Durbin's all-pairs test for a two-way balanced incomplete block design
  3 Durbin's all-pairs test for a two-way balanced incomplete block design
  4 Durbin's all-pairs test for a two-way balanced incomplete block design
  5 Durbin's all-pairs test for a two-way balanced incomplete block design
  6 Durbin's all-pairs test for a two-way balanced incomplete block design
    distribution p.adjustment test.details        p.value.adjustment
    <chr>        <chr>        <chr>               <chr>             
  1 t            none         Durbin-Conover test BY                
  2 t            none         Durbin-Conover test BY                
  3 t            none         Durbin-Conover test BY                
  4 t            none         Durbin-Conover test BY                
  5 t            none         Durbin-Conover test BY                
  6 t            none         Durbin-Conover test BY                
    label                                   
    <chr>                                   
  1 list(~italic(p)[BY-corrected]==1.44e-05)
  2 list(~italic(p)[BY-corrected]==0.045)   
  3 list(~italic(p)[BY-corrected]==5.45e-13)
  4 list(~italic(p)[BY-corrected]==0.050)   
  5 list(~italic(p)[BY-corrected]==0.005)   
  6 list(~italic(p)[BY-corrected]==4.64e-07)

  [[3]]
  # A tibble: 6 x 11
    group1 group2 estimate conf.level conf.low conf.high     p.value  p.crit
    <chr>  <chr>     <dbl>      <dbl>    <dbl>     <dbl>       <dbl>   <dbl>
  1 HDHF   HDLF      1.03        0.95   0.140      1.92  0.00999     0.0127 
  2 HDHF   LDHF      0.454       0.95  -0.104      1.01  0.0520      0.025  
  3 HDHF   LDLF      1.95        0.95   1.09       2.82  0.000000564 0.00851
  4 HDLF   LDHF     -0.676       0.95  -1.61       0.256 0.0520      0.05   
  5 HDLF   LDLF      0.889       0.95   0.0244     1.75  0.0203      0.0169 
  6 LDHF   LDLF      1.35        0.95   0.560      2.14  0.000102    0.0102 
    test.details              p.value.adjustment
    <chr>                     <chr>             
  1 Yuen's trimmed means test Hommel            
  2 Yuen's trimmed means test Hommel            
  3 Yuen's trimmed means test Hommel            
  4 Yuen's trimmed means test Hommel            
  5 Yuen's trimmed means test Hommel            
  6 Yuen's trimmed means test Hommel            
    label                                       
    <chr>                                       
  1 list(~italic(p)[Hommel-corrected]==0.010)   
  2 list(~italic(p)[Hommel-corrected]==0.052)   
  3 list(~italic(p)[Hommel-corrected]==5.64e-07)
  4 list(~italic(p)[Hommel-corrected]==0.052)   
  5 list(~italic(p)[Hommel-corrected]==0.020)   
  6 list(~italic(p)[Hommel-corrected]==1.02e-04)

`pairwise_comparisons()` works for within-subjects design - without NAs

Code
  list(df1, df2, df3)
Output
  [[1]]
  # A tibble: 3 x 6
    group1 group2  p.value test.details     p.value.adjustment
    <chr>  <chr>     <dbl> <chr>            <chr>             
  1 Wine A Wine B 0.732    Student's t-test None              
  2 Wine A Wine C 0.0142   Student's t-test None              
  3 Wine B Wine C 0.000675 Student's t-test None              
    label                               
    <chr>                               
  1 list(~italic(p)[uncorrected]==0.732)
  2 list(~italic(p)[uncorrected]==0.014)
  3 list(~italic(p)[uncorrected]==0.001)

  [[2]]
  # A tibble: 3 x 11
    group1 group2 statistic  p.value alternative
    <chr>  <chr>      <dbl>    <dbl> <chr>      
  1 Wine A Wine B      1.05 0.301    two.sided  
  2 Wine A Wine C      3.66 0.000691 two.sided  
  3 Wine B Wine C      2.62 0.0123   two.sided  
    method                                                                
    <chr>                                                                 
  1 Durbin's all-pairs test for a two-way balanced incomplete block design
  2 Durbin's all-pairs test for a two-way balanced incomplete block design
  3 Durbin's all-pairs test for a two-way balanced incomplete block design
    distribution p.adjustment test.details        p.value.adjustment
    <chr>        <chr>        <chr>               <chr>             
  1 t            none         Durbin-Conover test None              
  2 t            none         Durbin-Conover test None              
  3 t            none         Durbin-Conover test None              
    label                               
    <chr>                               
  1 list(~italic(p)[uncorrected]==0.301)
  2 list(~italic(p)[uncorrected]==0.001)
  3 list(~italic(p)[uncorrected]==0.012)

  [[3]]
  # A tibble: 3 x 11
    group1 group2 estimate conf.level conf.low conf.high p.value p.crit
    <chr>  <chr>     <dbl>      <dbl>    <dbl>     <dbl>   <dbl>  <dbl>
  1 Wine A Wine B   0.0214       0.95 -0.0216     0.0645 0.195   0.05  
  2 Wine A Wine C   0.114        0.95  0.0215     0.207  0.00492 0.0169
  3 Wine B Wine C   0.0821       0.95  0.00891    0.155  0.00878 0.025 
    test.details              p.value.adjustment
    <chr>                     <chr>             
  1 Yuen's trimmed means test None              
  2 Yuen's trimmed means test None              
  3 Yuen's trimmed means test None              
    label                               
    <chr>                               
  1 list(~italic(p)[uncorrected]==0.195)
  2 list(~italic(p)[uncorrected]==0.005)
  3 list(~italic(p)[uncorrected]==0.009)