marp: MARP: Many Analysts Religion Project Dataset

Description

A cross-cultural dataset from the Many-Analysts Religion Project (MARP), which investigated the relationship between religiosity and well-being across 24 countries and diverse religious traditions.

Usage

data(marp)

Arguments

Format

A data frame with 10,535 rows (participants) and 48 variables:

subject: Unique subject identifier (integer).
country: Country of residence (character string).
rel_1: Importance of religion in daily life (0–10 scale).
rel_2: Frequency of religious service attendance (ordinal).
rel_3: Self-rated religiosity (0–10 scale).
rel_4: Belief in God (binary: yes/no).
rel_5: Prayer frequency (ordinal).
rel_6: Bible/study frequency (ordinal).
rel_7: Religious upbringing (binary: yes/no).
rel_8: Current religious denomination (categorical).
rel_9: Change in religiosity over lifetime (ordinal).
cnorm_1: Perceived cultural norm: importance of religious lifestyle for average person in country (0–10).
cnorm_2: Perceived cultural norm: importance of belief in God for average person in country (0–10).
wb_gen_1: Overall life satisfaction (1–5 Likert).
wb_gen_2: Overall happiness (1–5 Likert).
wb_phys_1: Energy level (1–5).
wb_phys_2: Sleep quality (1–5).
wb_phys_3: Appetite (1–5).
wb_phys_4: Physical pain/discomfort (1–5).
wb_phys_5: General health (1–5).
wb_phys_6: Exercise frequency (1–5).
wb_phys_7: Illness burden (1–5).
wb_psych_1: Positive affect (1–5).
wb_psych_2: Negative affect (reverse coded; 1–5).
wb_psych_3: Meaning in life (1–5).
wb_psych_4: Purpose in life (1–5).
wb_psych_5: Hopefulness (1–5).
wb_psych_6: Anxiety (reverse coded; 1–5).
wb_soc_1: Social support (1–5).
wb_soc_2: Loneliness (reverse coded; 1–5).
wb_soc_3: Community belonging (1–5).
wb_overall_mean: Mean of all well-being items (numeric).
wb_phys_mean: Mean of physical well-being items (numeric).
wb_psych_mean: Mean of psychological well-being items (numeric).
wb_soc_mean: Mean of social well-being items (numeric).
age: Age in years (integer).
gender: Self-reported gender (character: e.g., "Male", "Female", "Other").
ses: Socioeconomic status composite (numeric).
education: Highest education level completed (ordinal integer).
ethnicity: Self-reported ethnicity (character).
denomination: Religious denomination (character).
gdp: GDP per capita (PPP, USD) for country (numeric).
gdp_scaled: Scaled GDP (mean = 0, sd = 1) used in analyses (numeric).
sample_type: Recruitment method: e.g., "online panel", "student sample" (character).
compensation: Type of compensation: e.g., "monetary", "entry into lottery" (character).
attention_check: Score on embedded attention check task (integer).

Examples

Run this code

library(dplyr)
data(marp)
# Dimensions
dim(marp)
# Quick overview
if (requireNamespace("dplyr", quietly = TRUE)) {
  library(dplyr)

  marp |>
    group_by(country) |>
    summarise(
      mean_wb = mean(wb_overall_mean, na.rm = TRUE),
      .groups = "drop"
    )
}

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