A QUANTITATIVE APPROACH TO CONTENT VALIDITY

By C. H. Lawshe. 1975

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Metrics for Explainable AI: Challenges and Prospects (2018, methodology): “Participants were asked to evaluate the scale using the Content Validity Ratio (CVR) method (Lawshe, 1975).”
Structural Equation Modeling in Information Systems Research Using Partial Least Squares (2010, background): “For example, Lawshe (1975) suggests that experts should rate the alternative indicators and that a quantitative metric (content validity ratio, CVR) should be calculated and tested for significance in order to determine the most appropriate indicators.”
Religiosity among Muslims: A Scale Development and Validation Study (2016, methodology): “Both content validity ratio (CVR) and content validity index (CVI) (Lawshe, 1975) were calculated for each item.”
Development of a Measure for the Organizational Learning Construct (2002, methodology): “The content validity of the measurement instrument was then directly investigated by executing a variation on the procedure developed by Lawshe [79] for quantitatively assessing content validity.”
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies (2021, background): “is intended to measure) [31] and content validity (is the test fully representative of what it aims to measure) [84].”
Re-conceptualizing Information System Success: The IS-Impact Measurement Model (2008, methodology): “In this fourth step, a quantitative assessment was made, establishing the Content Validity Ratio (CVR) for each item/question based on the formula of Lawshe (1975).”