Mean and SD of scale scores

Computes the mean and standard deviation of respondent scale scores. When divisor is NULL the scale score is the row mean across items. When divisor is supplied the scale score is the row sum divided by divisor, which is useful when scores need to be expressed on a custom metric (e.g. dividing a sum score by the maximum possible score to obtain a proportion).

Usage

compute_mean_sd_alpha(df, divisor = NULL)

Arguments

df

A data frame whose columns are the items of a single scale. All columns must be numeric.

divisor

Numeric scalar used to divide the row sum before computing the mean and SD. When NULL (default) row means are used instead.

Value

A one-row data frame with columns MEAN and SD containing the mean and standard deviation of the scale scores across respondents.

Examples

set.seed(12345)
df <- data.frame(matrix(.5, ncol = 6, nrow = 6))
correlation_martix <- as.matrix(df)
diag(correlation_martix) <- 1
df <- round(generate_correlation_matrix(correlation_martix, nrows = 1000), 0) + 5
compute_mean_sd_alpha(df)
#>       MEAN        SD
#> 1 5.006833 0.7683419
compute_mean_sd_alpha(df, divisor = 100)
#>      Mean         SD
#> 1 0.30041 0.04610051