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 (R1) and squared error (R2) predicted by statistical methods.
Findings. A TPM with a log-transformed EQ-5D index performed best on R1; a LCM performed best on R2. In contrast, the CLAD was worst. Performance of the OLS and a standard TPM were intermediate. Values for R1 ranged from 0.33 (CLAD) to 0.42 (TPM-L); R2 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.