Present state bias in transition ratings was accurately estimated in simulated and real data.

Objective: Patient-reported transition ratings are supposed to reflect the change between a previous baseline health state and a present follow-up state, but may reflect the present state to a greater extent. This so-called "present state bias" (PSB) potentially threatens the validity of transition ratings. Several criteria have been proposed to assess PSB. We examined how well these criteria perform and to which extent confirmatory factor analysis (CFA) for categorical data provides an accurate assessment of the degree of PSB.

Study Design And Setting: We simulated multiple samples with baseline and follow-up item responses to a hypothetical questionnaire, and transition ratings. The samples varied with respect to various distributional characteristics and the degree of PSB. The performance of criteria proposed in the literature, and a new CFA-based criterion, were evaluated by the proportion of explained variance in PSB. In addition, four real datasets were analyzed.

Results: The known criteria explained 36-74% of the variance in PSB. A new CFA-based criterion, namely the ratio of the factor loadings of the transition ratings plus one, explained 81-98% of the variance in PSB across the samples.

Conclusion: Present state bias in transition ratings can be estimated accurately using CFA.