aikenV: Compute the Aiken's V index of content validity

In spheredata: Students' Performance Dataset in Physics Education Research (SPHERE)

Compute the Aiken's V index of content validity

Description

Aiken's V is a statistical measure of content validity index on a single item (Aiken, 1980). This measure could be defined as follow.

\displaystyle V=\frac{\bar{X}-l}{k}

where \bar{X} represents the sample mean of the judges’ ratings, l represents the lowest possible rating, and k represents the range of possible values of the rating scale used (e.g., a scale having possible values extending from 1 to 5 has l=1 and k = 5-1 = 4). Then, Penfield and Giacobbi (2004) suggest a method to compute the confidence interval of Aiken's V index using the formula below.

\displaystyle L=\frac{2nkV+z^2-z\sqrt{4nkV(1-V)+z^2}}{2(nk+z^2)}

\displaystyle U=\frac{2nkV+z^2+z\sqrt{4nkV(1-V)+z^2}}{2(nk+z^2)}

where L and U are the lower and upper limit of Aiken's V index within a C\% confidence interval, and the z is a critical value of a standard normal distribution such that C\% of the area of the distribution lies between -z and z (e.g., for a 95% confidence interval z = 1.96).

Usage

aikenV(data, max_cat = 4, min_cat = 1, CI = 0.95)

Arguments

data	a dataframe of categorical value from expert judgment to the item content validity.
max_cat	a maximum category point of used rating scale (the default value is 4).
min_cat	a minimum category point of used rating scale (the default value is 1).
CI	the default value of confidence interval is 0.95. It can be set to preferred confidence interval.

Value

a dataframe of content validity index of each item as calculated using the Aiken's formula

References

Aiken, L.R. Content Validity and Reliability of Single Items or Questionnaires. Educational and Psychological Measurement 40, 955-959 (1980).

Penfield, R.D. & Giacobbi, P.R. Applying a Score Confidence Interval to Aiken’s Item Content-Relevance Index. Measurement in Physical Education and Exercise Science 8, 4, 213-225 (2004).

Examples

# In this example, we define a dataframe describing the rating of ten
# imaginary items as assessed by seven artificial experts. The minimum point
# of the rating scale is 1, and the maximum point that could be given by
# those experts is 4.

df <- data.frame(item1 = c(3,3,3,4,4,4,3),
                 item2 = c(2,4,3,2,4,4,4),
                 item3 = c(4,3,3,2,4,4,3),
                 item4 = c(3,2,3,3,4,3,3),
                 item5 = c(4,4,4,3,3,3,3),
                 item6 = c(3,3,3,4,3,3,4),
                 item7 = c(4,4,4,3,4,4,4),
                 item8 = c(3,3,4,4,4,4,4),
                 item9 = c(4,4,4,3,4,4,4),
                 item10 = c(4,3,4,4,3,3,4))

# Compute the Aiken's V
aikenV(df)

spheredata documentation built on April 4, 2025, 2:29 a.m.