Dissertations, Theses, and Capstone Projects
Date of Degree
5-2018
Document Type
Dissertation
Degree Name
Ph.D.
Program
Educational Psychology
Advisor
Jay Verkuilen
Committee Members
Irvin Schonfeld
Renzo Bianchi
Howard Everson
Claire Wladis
Subject Categories
Applied Statistics | Occupational Health and Industrial Hygiene | Quantitative Psychology | Social Statistics | Statistical Methodology | Statistical Models
Keywords
ordinality, monotonicity, clinical assessment, item response theory, PHQ-9, depression
Abstract
Improper scale usage in psychological and clinical assessment is an important problem. If respondents do not use the scales in a consistent manner, the reliability of a composite is likely to be attenuated. This is particularly problematic when particular items are singled out for special treatment or when subscales are of interest, not just a total score. This study used both non-parametric and parametric item response theory (IRT) methods to gain further insight into the validity of the PHQ-9, a dual purpose instrument that assesses the severity of depressive symptoms using nine Likert-scale items and allows the investigator to establish provisional diagnoses of depressive disorders. The data was collected by Bianchi et al. (2015) across three separate cross-cultural samples of teachers. The analysis indicated that scale monotonicity was preserved, violations to ordinality occurred among a subset of items resulting in inconsistent scale usage within the different samples, and that language differences in the test administration primarily accounted for the differences in scale usage.
Recommended Citation
Singhroy, Venessa N., "Assessing the Ordinality of Response Bias with Item Response Models: A Case Study Using the PHQ-9" (2018). CUNY Academic Works.
https://academicworks.cuny.edu/gc_etds/2583
Included in
Applied Statistics Commons, Occupational Health and Industrial Hygiene Commons, Quantitative Psychology Commons, Social Statistics Commons, Statistical Methodology Commons, Statistical Models Commons