R: T-statistics with subsets-CodePudding

I would like to have a table as ouptut where I have the t-statistics between the difference in means of certain variables and based on two specific subsets of my data.

I have the following data:

structure(list(Name = c("A", "A", "A", "A", "B", "B", "B", "B", 
"C", "C", "C", "C", "D", "D", "D", "D"), Date = c("20.10.2018", 
"30.09.2018", "25.11.2019", "23.10.2020", "20.03.2018", "30.07.2018", 
"25.08.2019", "23.10.2020", "20.12.2018", "30.01.2018", "25.02.2019", 
"23.06.2020", "20.11.2018", "30.12.2018", "25.11.2019", "23.09.2020"
), Return = c(0.01, 0.05, 0.08, 0.07, 0.04, 0.03, 0.01, 0.03, 
0.03, 0.05, 0.06, 0.07, 0.07, 0.04, 0.06, 0.08), Age = c(5L, 
5L, 6L, 7L, 8L, 8L, 9L, 10L, 4L, 4L, 5L, 6L, 1L, 1L, 2L, 3L), 
    Size = c(53336L, 75768L, 86548L, 94567L, 40234L, 40240L, 
    50243L, 60352L, 5069L, 6069L, 7092L, 8024L, 2456L, 3046L, 
    4056L, 5600L), Rating = c(1L, 1L, 1L, 2L, 5L, 5L, 3L, NA, 
    4L, 5L, 4L, 5L, NA, 4L, 5L, 4L)), class = "data.frame", row.names = c(NA, 
-16L))

More specifically, I would like to have a table where I have t-statistics for each differences of means between the variables Return, Age and Size for the observations with a Rating of 1 and 5. The t-statistics should be the column between Rating 1 and Rating 5 and should include the stars that indicate the p-value.

I tried using the t.test function but I have difficulties using it with subgroups only and create the t-statistics column in the middle between Rating 1 and Rating 5.

The output should have the layout like this:

structure(list(c("Return", "Age", "Size"), `Mean Rating 1` = c(NA, 
NA, NA), `t-statistics including p-value (indicated as stars)` = c(NA, 
NA, NA), `Mean Rating 5` = c(NA, NA, NA)), class = "data.frame", row.names = c(NA, 
-3L))

Could someone help me here with the code?

Thank you a lot in advance.

CodePudding user response：

You may easily loop over a subset=.

t(with(mtcars, sapply(unique(cyl), \(i) t.test(am, subset=cyl == i))))
#      statistic parameter p.value      conf.int  estimate null.value stderr     alternative method              data.name
# [1,] 4.605489  31        6.632258e-05 numeric,2 0.40625  0          0.08820997 "two.sided" "One Sample t-test" "am"     
# [2,] 4.605489  31        6.632258e-05 numeric,2 0.40625  0          0.08820997 "two.sided" "One Sample t-test" "am"     
# [3,] 4.605489  31        6.632258e-05 numeric,2 0.40625  0          0.08820997 "two.sided" "One Sample t-test" "am"

More specific for your data you could do this:

tcols <- c('Return', 'Age', 'Size')
r <- t(with(subset(dat, Rating %in% c(1, 5)), 
     sapply(setNames(tcols, tcols), \(i) unlist(
       t.test(reformulate('Rating', i))[
         c('estimate', 'statistic', 'p.value')]
       ))))
cbind(as.data.frame(r),
      ' '=c("   ", "*  ", "** ", "***")[
        rowSums(outer(r[, 'p.value'], c(Inf, 0.05, 0.01, 0.001), `<`))])
#        estimate.mean in group 1 estimate.mean in group 5 statistic.t   p.value    
# Return             4.666667e-02                     0.05  -0.1552301 0.8883096    
# Age                5.333333e 00                     5.60  -0.2198599 0.8353634    
# Size               7.188400e 04                 19724.60   4.0457818 0.0109848 *

Note R >= 4.1 used.