tidy_stats_to_data_frame converts a tidystats list to a data frame, which can then be used to extract specific statistics using standard subsetting functions (e.g., dplyr::filter).

tidy_stats_to_data_frame(x)

Arguments

x

A tidystats list.

Examples

# Load dplyr for access to the piping operator library(dplyr) # t-test: sleep_test <- t.test(extra ~ group, data = sleep, paired = TRUE) # lm: ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14) trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69) group <- gl(2, 10, 20, labels = c("Ctl", "Trt")) weight <- c(ctl, trt) lm_D9 <- lm(weight ~ group) # ANOVA: npk_aov <- aov(yield ~ block + N*P*K, npk) #' # Create an empty list results <- list() # Add output to the results list results <- results %>% add_stats(sleep_test) %>% add_stats(lm_D9, type = "primary", preregistered = TRUE) %>% add_stats(npk_aov, notes = "An ANOVA example") # Convert the list to a data frame results_df <- tidy_stats_to_data_frame(results) # Select all the p-values filter(results_df, statistic == "p")
#> # A tibble: 11 x 8 #> identifier term statistic value extra method type preregistered #> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> #> 1 sleep_test NA p 2.83e- 3 NA Paired t-te… NA NA #> 2 lm_D9 NA p 2.49e- 1 NA Linear regr… prim… yes #> 3 lm_D9 (Interc… p 9.55e-15 NA Linear regr… prim… yes #> 4 lm_D9 groupTrt p 2.49e- 1 NA Linear regr… prim… yes #> 5 npk_aov block p 1.59e- 2 NA ANOVA NA NA #> 6 npk_aov N p 4.37e- 3 NA ANOVA NA NA #> 7 npk_aov P p 4.75e- 1 NA ANOVA NA NA #> 8 npk_aov K p 2.88e- 2 NA ANOVA NA NA #> 9 npk_aov N:P p 2.63e- 1 NA ANOVA NA NA #> 10 npk_aov N:K p 1.69e- 1 NA ANOVA NA NA #> 11 npk_aov P:K p 8.63e- 1 NA ANOVA NA NA