spheredata (version 0.1.3)

lawsheCVR: Compute the Lawshe's content validity ratio (CVR)

Description

Lawshe (1975) proposed an index to quantify content validity of items as assessed by experts. He coined the index as content validity ratio (\(CVR\)) that can be calculated using the following formula. $$\displaystyle CVR=\frac{n_e - \frac{N}{2}}{\frac{N}{2}}$$ where \(n_e\) is the number of experts identifying an item as essential. In this function, we define a cutoff value using two methods. The first is "max" calculated by searching the maximum value of the used rating scale ("max_cat") and then divide it by two. The second method is "min" by using the minimum value of the used rating scale ("min_cat") as the cutoff criteria.

Usage

lawsheCVR(data, max_cat = 4, min_cat = 1, method = "max")

Value

a dataframe of CVR of each item as calculated using the Lawshe's formula

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).

method

a method to determine cutoff value between essential and non-essential items

References

Gilbert, G.E. & Prion, S. Making Sense of Methods and Measurement: Lawshe's Content Validity Index. Clinical Simulation in Nursing 12, 530-531 (2016).

Lawshe, C.H. A Quantitative Approach of Content Validity. Personnel Psychology 28, 563-575 (1975).

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 Lawshe's CVR
lawsheCVR(df)