WeightMyItems (version 0.1.4)

weighted_mean_score: 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)

Value

A numeric vector containing the weighted mean score for each individual (each row).

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.

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))