pairwise-contingency-table.md
In statsExpressions: Tidy Dataframes and Expressions with Statistical Details

pairwise_contingency_table works - basic

Code
  select(df1, -expression)
Output
  # A tibble: 3 x 13
    group1 group2 p.value p.value.adj estimate conf.level conf.low conf.high
    <chr>  <chr>    <dbl>       <dbl>    <dbl>      <dbl>    <dbl>     <dbl>
  1 4      6      0.332        0.997     0.180       0.95        0     0.743
  2 4      8      0.00514      0.0154    0.568       0.95        0     0.983
  3 6      8      0.280        0.840     0.229       0.95        0     0.728
    effectsize        conf.method conf.distribution p.adjust.method
    <chr>             <chr>       <chr>             <chr>          
  1 Cramer's V (adj.) ncp         chisq             Bonferroni     
  2 Cramer's V (adj.) ncp         chisq             Bonferroni     
  3 Cramer's V (adj.) ncp         chisq             Bonferroni     
    test               
    <chr>              
  1 Fisher's exact test
  2 Fisher's exact test
  3 Fisher's exact test

Code
  df1[["expression"]]
Output
  [[1]]
  list(italic(p)["Bonferroni" - adj.] == "1.00")

  [[2]]
  list(italic(p)["Bonferroni" - adj.] == "0.02")

  [[3]]
  list(italic(p)["Bonferroni" - adj.] == "0.84")

pairwise_contingency_table works - with counts

Code
  select(df1, -expression)
Output
  # A tibble: 6 x 13
    group1 group2  p.value p.value.adj estimate conf.level conf.low conf.high
    <chr>  <chr>     <dbl>       <dbl>    <dbl>      <dbl>    <dbl>     <dbl>
  1 1st    2nd    2.78e- 7    4.17e- 7    0.207       0.95   0.125     0.287 
  2 1st    3rd    3.68e-30    1.10e-29    0.357       0.95   0.296     0.419 
  3 1st    Crew   1.81e-34    1.09e-33    0.359       0.95   0.302     0.415 
  4 2nd    3rd    8.19e- 7    9.83e- 7    0.157       0.95   0.0926    0.220 
  5 2nd    Crew   2.77e- 8    5.54e- 8    0.164       0.95   0.105     0.222 
  6 3rd    Crew   5.98e- 1    5.98e- 1    0           0.95   0         0.0581
    effectsize        conf.method conf.distribution p.adjust.method
    <chr>             <chr>       <chr>             <chr>          
  1 Cramer's V (adj.) ncp         chisq             FDR            
  2 Cramer's V (adj.) ncp         chisq             FDR            
  3 Cramer's V (adj.) ncp         chisq             FDR            
  4 Cramer's V (adj.) ncp         chisq             FDR            
  5 Cramer's V (adj.) ncp         chisq             FDR            
  6 Cramer's V (adj.) ncp         chisq             FDR            
    test               
    <chr>              
  1 Fisher's exact test
  2 Fisher's exact test
  3 Fisher's exact test
  4 Fisher's exact test
  5 Fisher's exact test
  6 Fisher's exact test

Code
  df1[["expression"]]
Output
  [[1]]
  list(italic(p)["FDR" - adj.] == "4.17e-07")

  [[2]]
  list(italic(p)["FDR" - adj.] == "1.10e-29")

  [[3]]
  list(italic(p)["FDR" - adj.] == "1.09e-33")

  [[4]]
  list(italic(p)["FDR" - adj.] == "9.83e-07")

  [[5]]
  list(italic(p)["FDR" - adj.] == "5.54e-08")

  [[6]]
  list(italic(p)["FDR" - adj.] == "0.60")

pairwise_contingency_table works - no adjustment

Code
  select(df1, -expression)
Output
  # A tibble: 3 x 13
    group1 group2 p.value p.value.adj estimate conf.level conf.low conf.high
    <chr>  <chr>    <dbl>       <dbl>    <dbl>      <dbl>    <dbl>     <dbl>
  1 4      6      0.332       0.332      0.180       0.95        0     0.743
  2 4      8      0.00514     0.00514    0.568       0.95        0     0.983
  3 6      8      0.280       0.280      0.229       0.95        0     0.728
    effectsize        conf.method conf.distribution p.adjust.method
    <chr>             <chr>       <chr>             <chr>          
  1 Cramer's V (adj.) ncp         chisq             None           
  2 Cramer's V (adj.) ncp         chisq             None           
  3 Cramer's V (adj.) ncp         chisq             None           
    test               
    <chr>              
  1 Fisher's exact test
  2 Fisher's exact test
  3 Fisher's exact test

Code
  df1[["expression"]]
Output
  [[1]]
  list(italic(p)[unadj.] == "0.33")

  [[2]]
  list(italic(p)[unadj.] == "5.14e-03")

  [[3]]
  list(italic(p)[unadj.] == "0.28")

pairwise_contingency_table works - data with NAs

Code
  select(df1, -expression)
Output
  # A tibble: 6 x 13
    group1  group2  p.value p.value.adj estimate conf.level conf.low conf.high
    <chr>   <chr>     <dbl>       <dbl>    <dbl>      <dbl>    <dbl>     <dbl>
  1 carni   herbi     0.783       1        0           0.95        0     0.180
  2 carni   insecti   0.712       1        0           0.95        0     0.499
  3 carni   omni      0.138       0.828    0.306       0.95        0     0.713
  4 herbi   insecti   0.537       1        0           0.95        0     0.395
  5 herbi   omni      0.292       1        0.243       0.95        0     0.569
  6 insecti omni      0.455       1        0.343       0.95        0     1    
    effectsize        conf.method conf.distribution p.adjust.method
    <chr>             <chr>       <chr>             <chr>          
  1 Cramer's V (adj.) ncp         chisq             Holm           
  2 Cramer's V (adj.) ncp         chisq             Holm           
  3 Cramer's V (adj.) ncp         chisq             Holm           
  4 Cramer's V (adj.) ncp         chisq             Holm           
  5 Cramer's V (adj.) ncp         chisq             Holm           
  6 Cramer's V (adj.) ncp         chisq             Holm           
    test               
    <chr>              
  1 Fisher's exact test
  2 Fisher's exact test
  3 Fisher's exact test
  4 Fisher's exact test
  5 Fisher's exact test
  6 Fisher's exact test

Code
  df1[["expression"]]
Output
  [[1]]
  list(italic(p)["Holm" - adj.] == "1.00")

  [[2]]
  list(italic(p)["Holm" - adj.] == "1.00")

  [[3]]
  list(italic(p)["Holm" - adj.] == "0.83")

  [[4]]
  list(italic(p)["Holm" - adj.] == "1.00")

  [[5]]
  list(italic(p)["Holm" - adj.] == "1.00")

  [[6]]
  list(italic(p)["Holm" - adj.] == "1.00")

pairwise_contingency_table works - custom conf.level and alternative

Code
  select(df1, -expression)
Output
  # A tibble: 3 x 13
    group1 group2 p.value p.value.adj estimate conf.level conf.low conf.high
    <chr>  <chr>    <dbl>       <dbl>    <dbl>      <dbl>    <dbl>     <dbl>
  1 4      6        0.961           1    0.180        0.9    0             1
  2 4      8        1.000           1    0.568        0.9    0.272         1
  3 6      8        0.975           1    0.229        0.9    0             1
    effectsize        conf.method conf.distribution p.adjust.method
    <chr>             <chr>       <chr>             <chr>          
  1 Cramer's V (adj.) ncp         chisq             Holm           
  2 Cramer's V (adj.) ncp         chisq             Holm           
  3 Cramer's V (adj.) ncp         chisq             Holm           
    test               
    <chr>              
  1 Fisher's exact test
  2 Fisher's exact test
  3 Fisher's exact test

Code
  df1[["expression"]]
Output
  [[1]]
  list(italic(p)["Holm" - adj.] == "1.00")

  [[2]]
  list(italic(p)["Holm" - adj.] == "1.00")

  [[3]]
  list(italic(p)["Holm" - adj.] == "1.00")

pairwise_contingency_table works - custom digits

Code
  select(df1, -expression)
Output
  # A tibble: 3 x 13
    group1 group2 p.value p.value.adj estimate conf.level conf.low conf.high
    <chr>  <chr>    <dbl>       <dbl>    <dbl>      <dbl>    <dbl>     <dbl>
  1 4      6      0.332        0.332     0.180       0.95        0     0.743
  2 4      8      0.00514      0.0154    0.568       0.95        0     0.983
  3 6      8      0.280        0.332     0.229       0.95        0     0.728
    effectsize        conf.method conf.distribution p.adjust.method
    <chr>             <chr>       <chr>             <chr>          
  1 Cramer's V (adj.) ncp         chisq             FDR            
  2 Cramer's V (adj.) ncp         chisq             FDR            
  3 Cramer's V (adj.) ncp         chisq             FDR            
    test               
    <chr>              
  1 Fisher's exact test
  2 Fisher's exact test
  3 Fisher's exact test

Code
  df1[["expression"]]
Output
  [[1]]
  list(italic(p)["FDR" - adj.] == "0.3322")

  [[2]]
  list(italic(p)["FDR" - adj.] == "0.0154")

  [[3]]
  list(italic(p)["FDR" - adj.] == "0.3322")