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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

Improve this question
3
  • I can't reproduce your error and the hyp(??) seems to throw off reprex() when I try. Can you provide a reproducible example so I can try to help? Commented Mar 15, 2023 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. Commented Mar 15, 2023 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 Commented Mar 16, 2023 at 5:40

1 Answer 1

Reset to default
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.

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