OBJECTIVES: Advancements in the econometric modeling of discrete choice experiment (DCE) data allow for the quantification of individual-specific utility. With a view to improve the precision and face validity of DCE-derived willingness to pay (WTP) estimates, we investigate incorporating a ‘choice certainty’ question into the elicitation and estimation of DCE data.  METHODS: The DCE elicited parents’ preferences surrounding drug treatment for juvenile idiopathic arthritis.  Two alternatives in each question differed on six attributes: drug administration, child reported pain, participation in activities, side-effects, school days missed, and cost. Respondents rated the certainty for each of their choices on a Likert scale. The mixed logit model allowed estimating individual-specific utility values. Respondents’ choice certainty was incorporated into the model by re-weighting the simulated likelihood function. The D-error metric was used to investigate improvements in precision. Monte Carlo simulation techniques were used to generate individual-level population WTP estimates to investigate face validity. RESULTS: 105 parents of children with juvenile idiopathic arthritis at The Hospital for Sick Children, Toronto, Canada completed 16 choice and choice-certainty questions. The D-error statistic demonstrated a 53% gain in efficiency under the choice certainty approach. Under the standard approach, the mean WTP for a child who moved from responding inadequately to methotrexate and adequately to etanercept was $2,105 per month; 95% of the simulated individual-level population WTP estimates fell between $360 and $12,743 per month. When choice certainty was accounted for, mean willingness to pay was $2,167 and 95% of the simulated individual-level population estimates were between $405 and $11,866.  CONCLUSIONS: The stated preferences of parents’ of children with juvenile idiopathic arthritis suggest that this population is, on average, willing to pay $2,167 per month to improve children’s well being.  The choice certainty approach improved the precision of the parameter estimates and the range of willingness to pay values.