Badanie normujące JP

library(tidyverse)

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library(flextable)

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## Dołączanie pakietu: 'flextable'

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library(lubridate)

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## Następujące obiekty zostały zakryte z 'package:base':
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options(digits = 3)
data <- read_csv("data/results-survey811918.csv")

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Wyniki ankiety

data <- data %>% filter((`attCheck1[Satz]` == 0) & (`attCheck2[Satz]` == 'plus2'))
data_long <- pivot_longer(data, cols = ends_with("[Satz]"), names_to = "sentence", values_to = "score")
data_long$score <- recode(data_long$score,
                          `min2` = -2,
                          `min1` = -1,
                          `0` = 0,
                          `plus1` = 1,
                          `plus2` = 2,
                          )
data_long <- data_long %>% rowwise() %>% mutate(popr = str_split(sentence, "X", simplify = T)[3])
summ <- data_long %>%
          filter(! sentence %in% c('attCheck1[Satz]', 'attCheck2[Satz]') ) %>%
          group_by(popr, sentence) %>% summarise(M = mean(score), SD = sd(score)) %>% arrange(M) 

## `summarise()` has grouped output by 'popr'. You can override using the `.groups` argument.

pvals <- data_long %>% filter(! sentence %in% c('attCheck1[Satz]', 'attCheck2[Satz]') ) %>%
          group_by(popr, sentence) %>% rstatix::t_test(data = ., score ~ 1, mu = 0) %>%
          rowwise() %>%
          mutate(p = scales::pvalue(p))
left_join(summ, pvals, by = c('sentence', 'popr')) %>% select(popr, sentence, M, SD, p) %>% flextable()