JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 355
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 11:35 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #313988
Title: Monte Carlo Simulation to Examine the Uncertainty in Autism Spectrum Disorder Prevalence Estimates Derived from Postcensal Population Estimates
Author(s): Lin Tian*+ and Owen Devine
Companies: CDC and CDC
Keywords: Postcensal population estimates ; uncertainty in prevalence estimates ; Monte Carlo simulation
Abstract:

Postcensal population estimates (PPEs) are commonly used with case counts to estimate the prevalence of health outcomes. However, PPEs are subject to error and have an unknown level of uncertainty. We used Monte Carlo (MC) simulation to evaluate how a specified level of uncertainty could affect Autism Spectrum Disorder (ASD) prevalence estimates in 2008. We assumed that the uncertainty in the true population size followed a triangular distribution with a minimum value of the intercensal estimate, a maximum value of the PPE, and a mode of the liner growth population estimate in 2008. Based on 1000 simulated population sizes drawn from this distribution, we calculated 1000 ASD prevalence estimates and their 95% confidence intervals (CIs). The resulting distribution of possible values for the prevalence was summarized using the mean of the 1000 prevalence values. Uncertainty in the CIs was evaluated by defining an overall lower limit as the minimum of the lower CI values across simulations and the upper limit as the maximum of the CI upper limits. The results indicate that uncertainty in PPEs should be taken into account in estimating point and interval estimates of ASD prevalence.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.