From the proportional odds (PO) model, we obtain general equations to compute multiple cut scores on a test score. This analytical procedure is based on the relationship between a test score (X) and an ordinal outcome variable (Y) with more than two categories. Cut scores are established at the test scores corresponding to the intersection of adjacent category distributions. The application of this procedure is illustrated by an example with data from an actual study on eating disorders (EDs). In this example, two cut scores on the Eating Attitudes Test (EAT-26) are established in order to differentiate between three ordered categories: (1) asymptomatic, (2) symptomatic, and (3) eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalizes DSM-IV criteria for EDs. Alternatives to the PO model, when the PO assumption is rejected, are discussed.
Obtaining Equations from the Proportional Odds Model to Set Multiple Cut Scores on a Test
BERROCAL MONTIEL, CARMEN
2009-01-01
Abstract
From the proportional odds (PO) model, we obtain general equations to compute multiple cut scores on a test score. This analytical procedure is based on the relationship between a test score (X) and an ordinal outcome variable (Y) with more than two categories. Cut scores are established at the test scores corresponding to the intersection of adjacent category distributions. The application of this procedure is illustrated by an example with data from an actual study on eating disorders (EDs). In this example, two cut scores on the Eating Attitudes Test (EAT-26) are established in order to differentiate between three ordered categories: (1) asymptomatic, (2) symptomatic, and (3) eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalizes DSM-IV criteria for EDs. Alternatives to the PO model, when the PO assumption is rejected, are discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
