Confirmatory Factor Analysis and Measurement Invariance Testing with Ordinal Data: An Application in Revising the Flirting Styles Inventory

Abstract

Factor analysis (FA) is becoming a common practice in communication research for measurement validation, yet issues associated with FA for ordinal items have not been adequately addressed. As many attitudinal and behavioral measures in communication research consist of ordered-categorical items, this article provides an accessible introduction for applied researchers on categorical confirmatory factor analysis (cat-CFA) and measurement invariance (MI) testing for ordinal data. First, this paper presents conceptual discussions on the classical and the categorical FA models and conditions under which applications of the classical FA can lead to estimation biases. Second, model identification and specification issues with MI for ordinal data are discussed. Third, to demonstrate the techniques, cat-CFA and MI with ordinal data are applied to the revision of an existing self-report Likert-type measure, the Flirting Styles Inventory.