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I have the following dataset

# dput(head(dat, 130)) 
dat <- structure(list(
  Gender = c("Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women" ), 
  Education = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Basic", "Medium",  "Higher"), class = "factor"), 
  Efficacy = structure(c(24, 24,  24, 24, 24, 24, 24, 24, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29,  29, 29, 22, 22, 22, 22, 30, 30, 30, 30, 26, 26, 26, 26, 16, 16,  16, 16, 22, 22, 22, 22, 26, 26, 26, 26, 30, 30, 30, 30, 32, 32,  32, 32, 20, 20, 20, 20, 24, 24, 24, 24, 31, 31, 31, 31, 28, 28,  28, 28, 26, 26, 26, 26, 25, 25, 25, 25, 35, 35, 35, 35, 30, 30,  30, 30, 25, 25, 25, 25, 28, 28, 28, 28, 33, 33, 33, 33, 33, 33,  33, 33, 22, 22, 22, 22, 24, 24, 24, 24, 33, 33, 33, 33, 27, 27,  27, 27, 35, 35, 35, 35, 26, 26, 26, 26, 22, 22, 22, 22, 25, 25 ), format.spss = "F16.2"), 
  grp = c("Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring"), 
  points = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25,  11, 17, 10, 21, 12, 18, 13, 22, 12, 16, 11, 11, 8, 11, 10, 21,  14, 20, 8, 19, 5, 18, 5, 15, 7, 11, 6, 18, 12, 16, 7, 23, 10,  19, 8, 24, 15, 22, 12, 19, 10, 20, 6, 20, 7, 14, 9, 20, 7, 15,  10, 22, 7, 21, 9, 19, 13, 19, 11, 24, 7, 15, 9, 22, 9, 16, 13,  22, 12, 22, 11, 24, 13, 19, 10, 19, 11, 15, 10, 19, 11, 18, 14,  25, 15, 19, 13, 25, 7, 20, 9, 22, 5, 13, 8, 19, 5, 16, 11, 16,  10, 22, 7, 24, 12, 20, 13, 24, 13, 22, 6, 22, 4, 20, 8, 17, 8,  14, 10, 19)), row.names = c(NA, -130L), class = c("tbl_df", "tbl", "data.frame")
)

where I should extract some statistics from. I am applying the map function to get them. I have used the following code as a sample, that seems to work fine but not so precisely:

  dat %>%
  nest(data = -c(grp)) %>%
  mutate(test = map(data, ~ tidy(t.test(points ~ Gender, alternative = 'greater', .x))),
         sd = map(data, ~.x %>% group_by(Gender) %>% summarise(sd = sd(.data$points)))) %>%
  unnest(test, sd)

because I would like to fix the reference group (Women) and use them as alternative arguments for each string in the order reported in the hyp vector, one for each grp level:

hyp = c(rep('greater',2), 'less', 'greater')

I opted to choose the t_test function, but aside to do not knowing what put in the argument alternative

 library(rstatix)
    dat %>%
          nest(data = -c(grp)) %>% 
          mutate(test = map(data, ~ t_test(points ~ Gender, ref.group = 'Women', .x)),
                 sd = map(data, ~.x %>% group_by(Gender) %>% summarise(sd = sd(.data$points)))) %>%
          unnest(test, sd)

without it turns me the error

Error in `mutate()`:
! Problem while computing `test = map(...)`.
Caused by error in `x$terms %||% attr(x, "terms") %||% stop("no terms component nor attribute")`:
! no terms component nor attribute
Run `rlang::last_error()` to see where the error occurred.

Could someone help me please? Thanks

12666727b9
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  • I can't reproduce your error and the `hyp(??)` seems to throw off reprex() when I try. Can you provide a [reproducible example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) so I can try to help? – Mark Druffel Mar 15 '23 at 21:34
  • I know that the ? might have meaning in R but that simply means that I do not know (doubt marked with question mark) how the the vector with strings for alternative argument should be put like in the map() function. It is sufficiente to drop out the alternative argument from the code I reported to get the error. – 12666727b9 Mar 15 '23 at 21:53
  • I have deleted that argument as I wrote it, but the solution that I am looking for should have this argument too – 12666727b9 Mar 16 '23 at 05:40

1 Answers1

2

Using map over nested groups

Your data does not work so I modified the data to provide you a working example. I used pmap() because it allows more than two inputs to the function:

library(tidyverse, quietly = TRUE)
library(rstatix, quietly = TRUE)
library(magrittr)
#> 
dat <- structure(list(
  Gender = rep_len(c("Women", "Women", "Women", "Women", "Men", "Men", "Men", "Men"), length.out = 130), 
  Education = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Basic", "Medium",  "Higher"), class = "factor"), 
  Efficacy = structure(c(24, 24,  24, 24, 24, 24, 24, 24, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29,  29, 29, 22, 22, 22, 22, 30, 30, 30, 30, 26, 26, 26, 26, 16, 16,  16, 16, 22, 22, 22, 22, 26, 26, 26, 26, 30, 30, 30, 30, 32, 32,  32, 32, 20, 20, 20, 20, 24, 24, 24, 24, 31, 31, 31, 31, 28, 28,  28, 28, 26, 26, 26, 26, 25, 25, 25, 25, 35, 35, 35, 35, 30, 30,  30, 30, 25, 25, 25, 25, 28, 28, 28, 28, 33, 33, 33, 33, 33, 33,  33, 33, 22, 22, 22, 22, 24, 24, 24, 24, 33, 33, 33, 33, 27, 27,  27, 27, 35, 35, 35, 35, 26, 26, 26, 26, 22, 22, 22, 22, 25, 25 ), format.spss = "F16.2"), 
  grp = c("Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring"), 
  points = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25,  11, 17, 10, 21, 12, 18, 13, 22, 12, 16, 11, 11, 8, 11, 10, 21,  14, 20, 8, 19, 5, 18, 5, 15, 7, 11, 6, 18, 12, 16, 7, 23, 10,  19, 8, 24, 15, 22, 12, 19, 10, 20, 6, 20, 7, 14, 9, 20, 7, 15,  10, 22, 7, 21, 9, 19, 13, 19, 11, 24, 7, 15, 9, 22, 9, 16, 13,  22, 12, 22, 11, 24, 13, 19, 10, 19, 11, 15, 10, 19, 11, 18, 14,  25, 15, 19, 13, 25, 7, 20, 9, 22, 5, 13, 8, 19, 5, 16, 11, 16,  10, 22, 7, 24, 12, 20, 13, 24, 13, 22, 6, 22, 4, 20, 8, 17, 8,  14, 10, 19)), row.names = c(NA, -130L), class = c("tbl_df", "tbl", "data.frame")
)
dat |> 
  nest(data = -c(grp)) |> 
  mutate(alternative = c(rep('greater',2), 'less', 'greater')) %$% # Exposition pipe, allows plucking vectors from data frames https://magrittr.tidyverse.org/reference/exposition.html
  pmap_dfr(.l = list(grp = grp, alternative = alternative, dat = data), .f = function(grp = grp, alternative = alternative, dat = dat){
    some_other_operation_i_want_to_do_outside_my_pipeline <- dat |> group_by(Gender) |> tally()
    dat <- tibble::tibble(
      grp = grp,
      alternative = alternative,
      data = list(dat),
      gender_df = list(some_other_operation_i_want_to_do_outside_my_pipeline)
    ) |> 
      mutate(
        sd = sd(dat$points),
        t_test(data = dat, points ~ Gender, ref.group = "Women", alternative = alternative),
      )
    return(dat)
  })
#> # A tibble: 4 × 13
#>   grp    alter…¹ data     gender…²    sd .y.   group1 group2    n1    n2 stati…³
#>   <chr>  <chr>   <list>   <list>   <dbl> <chr> <chr>  <chr>  <int> <int>   <dbl>
#> 1 Avoid… greater <tibble> <tibble>  2.32 poin… Women  Men       17    16  -0.568
#> 2 Savor… greater <tibble> <tibble>  3.16 poin… Women  Men       17    16   0.610
#> 3 Coping less    <tibble> <tibble>  3.09 poin… Women  Men       16    16   0.113
#> 4 Obtai… greater <tibble> <tibble>  3.16 poin… Women  Men       16    16   0.275
#> # … with 2 more variables: df <dbl>, p <dbl>, and abbreviated variable names
#> #   ¹​alternative, ²​gender_df, ³​statistic

Created on 2023-03-16 with reprex v2.0.2

Invalid t-test

t_test() does not work for your dataset. Referencing another answer from Jouni Helske:

All standard variants of t-test use sample variances in their formulas, and you cannot compute that from one observation as you are dividing with n-1, where n is sample size.

library(tidyverse, quietly = TRUE)
library(rstatix, quietly = TRUE)
#> 
dat <- structure(list(
  Gender = c("Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women",  "Women", "Women", "Women", "Women", "Women", "Women", "Women" ), 
  Education = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Basic", "Medium",  "Higher"), class = "factor"), 
  Efficacy = structure(c(24, 24,  24, 24, 24, 24, 24, 24, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29,  29, 29, 22, 22, 22, 22, 30, 30, 30, 30, 26, 26, 26, 26, 16, 16,  16, 16, 22, 22, 22, 22, 26, 26, 26, 26, 30, 30, 30, 30, 32, 32,  32, 32, 20, 20, 20, 20, 24, 24, 24, 24, 31, 31, 31, 31, 28, 28,  28, 28, 26, 26, 26, 26, 25, 25, 25, 25, 35, 35, 35, 35, 30, 30,  30, 30, 25, 25, 25, 25, 28, 28, 28, 28, 33, 33, 33, 33, 33, 33,  33, 33, 22, 22, 22, 22, 24, 24, 24, 24, 33, 33, 33, 33, 27, 27,  27, 27, 35, 35, 35, 35, 26, 26, 26, 26, 22, 22, 22, 22, 25, 25 ), format.spss = "F16.2"), 
  grp = c("Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring"), 
  points = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25,  11, 17, 10, 21, 12, 18, 13, 22, 12, 16, 11, 11, 8, 11, 10, 21,  14, 20, 8, 19, 5, 18, 5, 15, 7, 11, 6, 18, 12, 16, 7, 23, 10,  19, 8, 24, 15, 22, 12, 19, 10, 20, 6, 20, 7, 14, 9, 20, 7, 15,  10, 22, 7, 21, 9, 19, 13, 19, 11, 24, 7, 15, 9, 22, 9, 16, 13,  22, 12, 22, 11, 24, 13, 19, 10, 19, 11, 15, 10, 19, 11, 18, 14,  25, 15, 19, 13, 25, 7, 20, 9, 22, 5, 13, 8, 19, 5, 16, 11, 16,  10, 22, 7, 24, 12, 20, 13, 24, 13, 22, 6, 22, 4, 20, 8, 17, 8,  14, 10, 19)), row.names = c(NA, -130L), class = c("tbl_df", "tbl", "data.frame")
)
t_test(dat, points ~  Gender, ref.group = "Women", alternative = "less")
#> Error in t.test.default(x = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25, 11, : not enough 'y' observations

Created on 2023-03-16 with reprex v2.0.2

Adding another Gender to the data set will resolve that issue:

library(tidyverse, quietly = TRUE)
library(rstatix, quietly = TRUE)
#> 
dat <- structure(list(
  Gender = rep_len(c("Women","Men"), length.out = 130), 
  Education = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Basic", "Medium",  "Higher"), class = "factor"), 
  Efficacy = structure(c(24, 24,  24, 24, 24, 24, 24, 24, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29,  29, 29, 22, 22, 22, 22, 30, 30, 30, 30, 26, 26, 26, 26, 16, 16,  16, 16, 22, 22, 22, 22, 26, 26, 26, 26, 30, 30, 30, 30, 32, 32,  32, 32, 20, 20, 20, 20, 24, 24, 24, 24, 31, 31, 31, 31, 28, 28,  28, 28, 26, 26, 26, 26, 25, 25, 25, 25, 35, 35, 35, 35, 30, 30,  30, 30, 25, 25, 25, 25, 28, 28, 28, 28, 33, 33, 33, 33, 33, 33,  33, 33, 22, 22, 22, 22, 24, 24, 24, 24, 33, 33, 33, 33, 27, 27,  27, 27, 35, 35, 35, 35, 26, 26, 26, 26, 22, 22, 22, 22, 25, 25 ), format.spss = "F16.2"), 
  grp = c("Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring"), 
  points = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25,  11, 17, 10, 21, 12, 18, 13, 22, 12, 16, 11, 11, 8, 11, 10, 21,  14, 20, 8, 19, 5, 18, 5, 15, 7, 11, 6, 18, 12, 16, 7, 23, 10,  19, 8, 24, 15, 22, 12, 19, 10, 20, 6, 20, 7, 14, 9, 20, 7, 15,  10, 22, 7, 21, 9, 19, 13, 19, 11, 24, 7, 15, 9, 22, 9, 16, 13,  22, 12, 22, 11, 24, 13, 19, 10, 19, 11, 15, 10, 19, 11, 18, 14,  25, 15, 19, 13, 25, 7, 20, 9, 22, 5, 13, 8, 19, 5, 16, 11, 16,  10, 22, 7, 24, 12, 20, 13, 24, 13, 22, 6, 22, 4, 20, 8, 17, 8,  14, 10, 19)), row.names = c(NA, -130L), class = c("tbl_df", "tbl", "data.frame")
)
t_test(dat, points ~  Gender, ref.group = "Women", alternative = "less")
#> # A tibble: 1 × 8
#>   .y.    group1 group2    n1    n2 statistic    df       p
#> * <chr>  <chr>  <chr>  <int> <int>     <dbl> <dbl>   <dbl>
#> 1 points Women  Men       65    65     -17.0  120. 6.1e-34

Created on 2023-03-16 with reprex v2.0.2

If I understand your write-up correctly, you want to perform this t-test for each grp in the data frame. That still won't work because we run into the same error due to not having multiple genders in each grp:

library(tidyverse, quietly = TRUE)
library(rstatix, quietly = TRUE)
#> 
dat <- structure(list(
  Gender = rep_len(c("Women","Men"), length.out = 130), 
  Education = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Basic", "Medium",  "Higher"), class = "factor"), 
  Efficacy = structure(c(24, 24,  24, 24, 24, 24, 24, 24, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29,  29, 29, 22, 22, 22, 22, 30, 30, 30, 30, 26, 26, 26, 26, 16, 16,  16, 16, 22, 22, 22, 22, 26, 26, 26, 26, 30, 30, 30, 30, 32, 32,  32, 32, 20, 20, 20, 20, 24, 24, 24, 24, 31, 31, 31, 31, 28, 28,  28, 28, 26, 26, 26, 26, 25, 25, 25, 25, 35, 35, 35, 35, 30, 30,  30, 30, 25, 25, 25, 25, 28, 28, 28, 28, 33, 33, 33, 33, 33, 33,  33, 33, 22, 22, 22, 22, 24, 24, 24, 24, 33, 33, 33, 33, 27, 27,  27, 27, 35, 35, 35, 35, 26, 26, 26, 26, 22, 22, 22, 22, 25, 25 ), format.spss = "F16.2"), 
  grp = c("Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring"), 
  points = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25,  11, 17, 10, 21, 12, 18, 13, 22, 12, 16, 11, 11, 8, 11, 10, 21,  14, 20, 8, 19, 5, 18, 5, 15, 7, 11, 6, 18, 12, 16, 7, 23, 10,  19, 8, 24, 15, 22, 12, 19, 10, 20, 6, 20, 7, 14, 9, 20, 7, 15,  10, 22, 7, 21, 9, 19, 13, 19, 11, 24, 7, 15, 9, 22, 9, 16, 13,  22, 12, 22, 11, 24, 13, 19, 10, 19, 11, 15, 10, 19, 11, 18, 14,  25, 15, 19, 13, 25, 7, 20, 9, 22, 5, 13, 8, 19, 5, 16, 11, 16,  10, 22, 7, 24, 12, 20, 13, 24, 13, 22, 6, 22, 4, 20, 8, 17, 8,  14, 10, 19)), row.names = c(NA, -130L), class = c("tbl_df", "tbl", "data.frame")
)
dat |> 
  filter(grp == "Avoiding") |> 
  t_test(points ~  Gender, ref.group = "Women", alternative = "less")
#> Error in t.test.default(x = c(9, 10, 12, 10, 13, 11, 10, 8, 5, 6, 7, 8, : not enough 'y' observations

Created on 2023-03-16 with reprex v2.0.2 Created on 2023-03-16 with reprex v2.0.2

We can fix that by modifying Gender further to have at least two genders represented in each grp:

library(tidyverse, quietly = TRUE)
library(rstatix, quietly = TRUE)
#> 
dat <- structure(list(
  Gender = rep_len(c("Women", "Women", "Women", "Women", "Men", "Men", "Men", "Men"), length.out = 130), 
  Education = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Basic", "Medium",  "Higher"), class = "factor"), 
  Efficacy = structure(c(24, 24,  24, 24, 24, 24, 24, 24, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29,  29, 29, 22, 22, 22, 22, 30, 30, 30, 30, 26, 26, 26, 26, 16, 16,  16, 16, 22, 22, 22, 22, 26, 26, 26, 26, 30, 30, 30, 30, 32, 32,  32, 32, 20, 20, 20, 20, 24, 24, 24, 24, 31, 31, 31, 31, 28, 28,  28, 28, 26, 26, 26, 26, 25, 25, 25, 25, 35, 35, 35, 35, 30, 30,  30, 30, 25, 25, 25, 25, 28, 28, 28, 28, 33, 33, 33, 33, 33, 33,  33, 33, 22, 22, 22, 22, 24, 24, 24, 24, 33, 33, 33, 33, 27, 27,  27, 27, 35, 35, 35, 35, 26, 26, 26, 26, 22, 22, 22, 22, 25, 25 ), format.spss = "F16.2"), 
  grp = c("Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring"), 
  points = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25,  11, 17, 10, 21, 12, 18, 13, 22, 12, 16, 11, 11, 8, 11, 10, 21,  14, 20, 8, 19, 5, 18, 5, 15, 7, 11, 6, 18, 12, 16, 7, 23, 10,  19, 8, 24, 15, 22, 12, 19, 10, 20, 6, 20, 7, 14, 9, 20, 7, 15,  10, 22, 7, 21, 9, 19, 13, 19, 11, 24, 7, 15, 9, 22, 9, 16, 13,  22, 12, 22, 11, 24, 13, 19, 10, 19, 11, 15, 10, 19, 11, 18, 14,  25, 15, 19, 13, 25, 7, 20, 9, 22, 5, 13, 8, 19, 5, 16, 11, 16,  10, 22, 7, 24, 12, 20, 13, 24, 13, 22, 6, 22, 4, 20, 8, 17, 8,  14, 10, 19)), row.names = c(NA, -130L), class = c("tbl_df", "tbl", "data.frame")
)
dat |> 
  filter(grp == "Avoiding") |> 
  t_test(points ~  Gender, ref.group = "Women", alternative = "less")
#> # A tibble: 1 × 8
#>   .y.    group1 group2    n1    n2 statistic    df     p
#> * <chr>  <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl>
#> 1 points Women  Men       17    16    -0.568  30.9 0.287

Created on 2023-03-16 with reprex v2.0.2

You don't actually need to use map() to do a t-test for each group once the data is valid:

library(tidyverse, quietly = TRUE)
library(rstatix, quietly = TRUE)
#> 
dat <- structure(list(
  Gender = rep_len(c("Women", "Women", "Women", "Women", "Men", "Men", "Men", "Men"), length.out = 130), 
  Education = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L,  2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Basic", "Medium",  "Higher"), class = "factor"), 
  Efficacy = structure(c(24, 24,  24, 24, 24, 24, 24, 24, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29,  29, 29, 22, 22, 22, 22, 30, 30, 30, 30, 26, 26, 26, 26, 16, 16,  16, 16, 22, 22, 22, 22, 26, 26, 26, 26, 30, 30, 30, 30, 32, 32,  32, 32, 20, 20, 20, 20, 24, 24, 24, 24, 31, 31, 31, 31, 28, 28,  28, 28, 26, 26, 26, 26, 25, 25, 25, 25, 35, 35, 35, 35, 30, 30,  30, 30, 25, 25, 25, 25, 28, 28, 28, 28, 33, 33, 33, 33, 33, 33,  33, 33, 22, 22, 22, 22, 24, 24, 24, 24, 33, 33, 33, 33, 27, 27,  27, 27, 35, 35, 35, 35, 26, 26, 26, 26, 22, 22, 22, 22, 25, 25 ), format.spss = "F16.2"), 
  grp = c("Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring", "Coping", "Obtaining", "Avoiding", "Savoring", "Coping",  "Obtaining", "Avoiding", "Savoring", "Coping", "Obtaining", "Avoiding",  "Savoring"), 
  points = c(9, 20, 12, 15, 10, 22, 8, 14, 12, 25,  11, 17, 10, 21, 12, 18, 13, 22, 12, 16, 11, 11, 8, 11, 10, 21,  14, 20, 8, 19, 5, 18, 5, 15, 7, 11, 6, 18, 12, 16, 7, 23, 10,  19, 8, 24, 15, 22, 12, 19, 10, 20, 6, 20, 7, 14, 9, 20, 7, 15,  10, 22, 7, 21, 9, 19, 13, 19, 11, 24, 7, 15, 9, 22, 9, 16, 13,  22, 12, 22, 11, 24, 13, 19, 10, 19, 11, 15, 10, 19, 11, 18, 14,  25, 15, 19, 13, 25, 7, 20, 9, 22, 5, 13, 8, 19, 5, 16, 11, 16,  10, 22, 7, 24, 12, 20, 13, 24, 13, 22, 6, 22, 4, 20, 8, 17, 8,  14, 10, 19)), row.names = c(NA, -130L), class = c("tbl_df", "tbl", "data.frame")
)
dat |> 
  group_by(grp) |> 
  t_test(points ~  Gender, ref.group = "Women", alternative = "less")
#> # A tibble: 4 × 9
#>   grp       .y.    group1 group2    n1    n2 statistic    df     p
#> * <chr>     <chr>  <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl>
#> 1 Avoiding  points Women  Men       17    16    -0.568  30.9 0.287
#> 2 Coping    points Women  Men       16    16     0.113  29.8 0.544
#> 3 Obtaining points Women  Men       16    16     0.275  26.7 0.607
#> 4 Savoring  points Women  Men       17    16     0.610  27.5 0.727

Created on 2023-03-16 with reprex v2.0.2

Please provide reproducible examples

Please take the time to create a reproducible question, it's worth the investment. You'll get better answers more quickly and it will help you reason through your question. Refer to this helpful guide and / or use reprex when working with R because it makes it way easier.

Mark Druffel
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