Assessing health status and health preference through different measures has become increasingly important. Recent research has provided a cross-translation algorithm from SF-36 to the Health Utility Index. OBJECTIVE: The present research substantiates the previous cross-translating procedures by estimating algorithms specific to chronic diseases. METHOD: Data were obtained from Southern California Kaiser-Permanente patients during 1992-95. Health status and health preferences were collected longitudinally over three different time periods by the SF-36 and the linear analogue instruments. Only patients with chronic diseases (n=5,000) were included in the present study. A moving average time series model was made using the SF-36 components as explanatory variables and the linear analogue scale as the dependent variable. Patient’s age, gender, comorbidities, and health behavior were used as covariates. As chronic disease severity may affect perceived health status and health preference, two different cross-sections were obtained on basis of high or low chronic disease score. A random coefficient panel data model was then used to capture heterogeneity. Model heteroscedasticity was corrected by GARCH modification. RESULTS: Domains of the SF-36 explained almost 49% variation in the linear analogue scale (Yule Walker estimate R2=0.5055). All of the domains except ‘role limitation due to emotional problem’ showed high statistical significance level (p<0.05) in determining variation in the LAS. Patient comorbidity also showed statistical significance at the same level. Random coefficient model could not find any statistically significant differences in estimation procedure between patients with high and low numbers of chronic diseases. However, education and marital status were significant predictors. CONCLUSION: This study extends previous research to derive a preference based index from the SF-36. This evidence suggests that the SF-36 domains, education, and marital status are better predictors of the LAS than is severity of chronic disease.