Addressing Ceiling Effects in Health Status Measures: A Comparison of Techniques Applied to Measures for People with HIV Disease

Objectives

To compare different approaches to address ceiling effects when predicting EQ‐5D index scores from the 10 subscales of the MOS‐HIV Health Survey.

Study Design

Data were collected from an HIV treatment trial. Statistical methods included ordinary least squares (OLS) regression, the censored least absolute deviations (CLAD) approach, a standard two‐part model (TPM), a TPM with a log‐transformed EQ‐5D index, and a latent class model (LCM). Predictive accuracy was evaluated using percentage of absolute error () and squared error () predicted by statistical methods.

Findings

A TPM with a log‐transformed EQ‐5D index performed best on ; a LCM performed best on . In contrast, the CLAD was worst. Performance of the OLS and a standard TPM were intermediate. Values for ranged from 0.33 (CLAD) to 0.42 (TPM‐L); ranged from 0.37 (CLAD) to 0.53 (LCM).

Conclusions

The LCM and TPM with a log‐transformed dependent variable are superior to other approaches in handling data with ceiling effects.