67 lines
2.1 KiB
R
67 lines
2.1 KiB
R
# Load required libraries
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library(Hmisc)
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library(knitr)
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library(dplyr)
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library(corrr)
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library(broom)
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library(purrr)
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library(tidyr)
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library(tibble)
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library(boot)
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options(scipen = 999)
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setwd("C:/Users/irina/Documents/DND/EOHI/eohi1")
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# Load data
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df1 <- read.csv("exp1.csv")
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# Remove columns with all NA values
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df1 <- df1 %>% select(where(~ !all(is.na(.))))
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# --- Brier score correlations vs EOHIs and Calibration ---
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# Variables
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bs_vars <- c("bs_28", "bs_easy", "bs_hard")
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eohi_vars <- c(
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"eohi_pref","eohi_pers","eohi_val","eohi_life","eohi_mean",
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"eohiDGEN_pref","eohiDGEN_pers","eohiDGEN_val","eohiDGEN_life","eohiDGEN_mean"
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)
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cal_vars <- c("cal_selfActual","cal_global")
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# Helper: tidy correlation (Pearson), pairwise complete
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corr_tidy <- function(df, x_vars, y_vars) {
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grid <- expand.grid(x = x_vars, y = y_vars, stringsAsFactors = FALSE)
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results <- purrr::pmap_dfr(grid, function(x, y) {
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xv <- df[[x]]; yv <- df[[y]]
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ok <- is.finite(xv) & is.finite(yv)
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if (sum(ok) < 3) {
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return(tibble::tibble(var_x = x, var_y = y, n = sum(ok), r = NA_real_, p = NA_real_))
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}
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ct <- suppressWarnings(cor.test(xv[ok], yv[ok], method = "pearson"))
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tibble::tibble(var_x = x, var_y = y, n = sum(ok), r = unname(ct$estimate), p = ct$p.value)
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})
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dplyr::arrange(results, var_x, var_y)
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}
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# Compute correlations
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corr_bs_eohi <- corr_tidy(df1, bs_vars, eohi_vars)
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corr_bs_cal <- corr_tidy(df1, bs_vars, cal_vars)
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# Wide r-only tables (optional)
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to_wide <- function(d) {
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tidyr::pivot_wider(d, id_cols = var_x, names_from = var_y, values_from = r)
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}
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wide_bs_eohi <- to_wide(corr_bs_eohi)
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wide_bs_cal <- to_wide(corr_bs_cal)
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# Display
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print("Correlations: Brier vs EOHIs (r, p, n)")
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print(corr_bs_eohi)
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print("Correlations: Brier vs Calibration (r, p, n)")
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print(corr_bs_cal)
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# If you want to export CSVs, uncomment:
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# write.csv(corr_bs_eohi, "corr_bs_eohi.csv", row.names = FALSE)
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# write.csv(corr_bs_cal, "corr_bs_cal.csv", row.names = FALSE)
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# write.csv(wide_bs_eohi, "corr_bs_eohi_wide.csv", row.names = FALSE)
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# write.csv(wide_bs_cal, "corr_bs_cal_wide.csv", row.names = FALSE) |