Abstract
When a 400-m walk test with time constraint (in 15 minutes) is administered, analysis of the associated 400-m gait speed can be challenging because some older adults are unable to complete the distance in time (noncompleters). A simplistic imputation method is to calculate the observed speeds of the noncompleters as the partially completed distance divided by the corresponding amount of elapsed time as an estimate of gait speed over the full 400-m distance. This common practice has not been validated to the best of our knowledge. We propose a Bayesian multiple imputation (MI) method to impute the unobserved 400-m gait speed for noncompleters. Briefly, MI is performed under the assumption that the unobserved 400-m gait speed of noncompleters is left-censored from a normal distribution. We illustrate the application of the Bayesian MI method using longitudinal data collected from the Lifestyle Interventions for Elders (LIFE) study. A simulation study was performed to assess the bias in estimation of the mean 400-m gait speed using both methods. The results indicate that the simplistic imputation method tends to overestimate the population mean, whereas the Bayesian MI method yields minimal bias as the sample size increases.