In many community-based studies on the incidence of dementia, a target population is screened and a subsample is clinically evaluated at baseline and follow-up. Incidence rates are affected by missed cases at both exams and this complicates the estimation of these rates. Recent work proposes a regression-based technique for joint estimation of prevalence and incidence and suggests the use of surrogate information obtained on the entire cohort at both times to calculate the expected score equation contribution for individuals missing clinical exams at one or both times. This helps to quantify the impact of missed diagnosis upon the incidence estimates and their confidence intervals. We extend this work to the setting of subtypes of dementia for use in the Honolulu-Asia Aging Study on incidence of dementia. The technique is applied using two separate models for the effect of age on dementia incidence. Subsequently, shrinkage estimation methods are applied to provide more precise estimates of the rates. Published in 2000 by John Wiley & Sons, Ltd.