weighted_mean_score {WeightMyItems} | R Documentation |
Calculate Weighted Mean Scores Using the Kılıç & Doğan (2019) Method
Description
This function first weights an item-response matrix using the 'item_weighting' function and then calculates the mean score for each individual.
Usage
weighted_mean_score(x, threshold = 1)
Arguments
x |
A numeric data.frame or matrix. Rows should represent individuals, and columns should represent items. The method was designed for dichotomous (0-1) data. |
threshold |
The threshold value for applying the weighting, passed to the 'item_weighting' function. The article uses a value of 1. |
Value
A numeric vector containing the weighted mean score for each individual (each row).
Examples
# Generate sample dichotomous data
set.seed(123)
my_data <- as.data.frame(
matrix(rbinom(200 * 10, 1, 0.6), nrow = 200)
)
# Calculate weighted mean scores
mean_scores <- weighted_mean_score(my_data, threshold = 1)
# View the first few mean scores
cat("--- Weighted Mean Scores (Head) ---\n")
print(head(mean_scores))
# Compare with simple unweighted mean scores
unweighted_means <- rowMeans(my_data)
cat("\n--- Unweighted Mean Scores (Head) ---\n")
print(head(unweighted_means))
[Package WeightMyItems version 0.1.4 Index]