SMART Series - Evaluating Psychological Measures

Psychological items often reflect multiple sources of variance, and modern psychometric models can help us understand that complexity. This talk introduces contemporary approaches to validity evidence using exploratory structural equation modeling (ESEM) and bifactor models, contrasted with traditional exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). We show how ESEM incorporates theoretical subdomain structures while allowing realistic cross-loadings, and how bifactor models extend naturally to multitrait–multimethod contexts to separate general, specific, and method variance. Attendees will learn how these models provide clearer insights into dimensionality, item functioning, and score meaning, ultimately strengthening the validity arguments behind psychological measures.

Location: Gillham Hall, Carver Resource Center and also on Teams at https://teams.microsoft.com/dl/launcher/launcher.html?url=%2F_%23%2Fl%2Fmeetup-join%2F19%3Ameeting_MTVjNzFjZTItNTBhNC00ZDQ5LTlkMjgtNTc2NjAzYTIxMmY5%40thread.v2%2F0%3Fcontext%3D%257b%2522Tid%2522%253a%25221d6b1707-baa9-4a3d-a8f8-deabfb3d467b%2522%252c%2522Oid%2522%253a%2522f54e735a-826d-4a78-9857-73fddf116af7%2522%257d%26anon%3Dtrue&type=meetup-join&deeplinkId=513c20e5-4aa9-45d6-98eb-4226ad01fa06&directDl=true&msLaunch=true&enableMobilePage=true&suppressPrompt=true

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