行百分比的 Express 和卡方检验

Question

如何使用 expss 包对行百分比执行卡方检验？ 我知道列百分比的显着性测试应该应用于 tab_stat_cpct 与总行的结果。 但我有一个像这样的表，我的卡方 p 值在我的表中是空白的。

d=mtcars
banner <- d %>%  tab_cells(vs, am)
# column percentage significacne
tab_cpct_sig=. %>% 
tab_stat_cpct() %>%
 tab_total_row_position("below") %>% 
    tab_total_statistic("u_rpct")


Table1 = function (Q, banner) {
    eval.parent(substitute(
        {
            banner %>%
                tab_cols (Q) %>%
                 tab_stat_rpct() %>% 
          tab_cols(total(Q)) %>% 
          tab_stat_cases() %>% 
        tab_last_sig_cases(sig_level = 0.05) %>%
        tab_pivot(stat_position = "outside_columns")  %>%  
               
            
            set_caption("Tableau 1") #%>%
         
           
              
        }
    ))
}
A1=Table1(gear,banner)
A1

Answer 1

目前expss仅支持对整个表进行卡方检验。但是，我们可以创建一个函数来添加行卡方统计量：

chi_sq_row = function(df){
    totals = grepl("#", df[[1]])
    df_matr = as.matrix(df[,-1][!totals])
    df_matr[is.na(df_matr)] = 0
    df[!totals,"chisq"] = apply(df_matr, 1,
                                   function(each_row) chisq.test(
                                       head(each_row, -1)*tail(each_row, 1)/100
                                   )$statistic
    )
    df[!totals, "pvalue"] = apply(df_matr, 1,
                                   function(each_row) chisq.test(
                                       head(each_row, -1)*tail(each_row, 1)/100
                                   )$p.value
    )
    df
}

Table1 = function (Q, banner) {
    eval.parent(substitute(
        {
            banner %>%
                tab_cols (Q) %>%
                tab_stat_rpct() %>% 
                tab_cols(total(Q)) %>% 
                tab_stat_cases() %>% 
                tab_pivot(stat_position = "outside_columns")  %>%  
                chi_sq_row() %>% 
                set_caption("Tableau 1")
            
            
            
        }
    ))
}
A1=Table1(gear,banner)
A1