Item Response Theory Modeling of the Philadelphia Naming Test

Author:

Fergadiotis Gerasimos1,Kellough Stacey2,Hula William D.23

Affiliation:

1. Portland State University, OR

2. Geriatric Research Education and Clinical Center, VA Pittsburgh Healthcare System, PA

3. University of Pittsburgh, PA

Abstract

Purpose In this study, we investigated the fit of the Philadelphia Naming Test (PNT; Roach, Schwartz, Martin, Grewal, & Brecher, 1996) to an item-response-theory measurement model, estimated the precision of the resulting scores and item parameters, and provided a theoretical rationale for the interpretation of PNT overall scores by relating explanatory variables to item difficulty. This article describes the statistical model underlying the computer adaptive PNT presented in a companion article (Hula, Kellough, & Fergadiotis, 2015). Method Using archival data, we evaluated the fit of the PNT to 1- and 2-parameter logistic models and examined the precision of the resulting parameter estimates. We regressed the item difficulty estimates on three predictor variables: word length, age of acquisition, and contextual diversity. Results The 2-parameter logistic model demonstrated marginally better fit, but the fit of the 1-parameter logistic model was adequate. Precision was excellent for both person ability and item difficulty estimates. Word length, age of acquisition, and contextual diversity all independently contributed to variance in item difficulty. Conclusions Item-response-theory methods can be productively used to analyze and quantify anomia severity in aphasia. Regression of item difficulty on lexical variables supported the validity of the PNT and interpretation of anomia severity scores in the context of current word-finding models. Supplemental Material https://doi.org/10.23641/asha.6170306

Publisher

American Speech Language Hearing Association

Subject

Speech and Hearing,Linguistics and Language,Language and Linguistics

Reference71 articles.

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5. Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences (2nd ed.). Mahwah, NJ: Erlbaum.

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