Ronaldo Iachan, PhD
ICF International, Calverton, Maryland
Dr. Iachan, a senior statistician, has 30 years of experience in statistical methods and applications, particularly in the areas of survey sampling design and analysis. For ICF, Dr. Iachan provides statistical expertise across divisions in projects in the areas of health, education, and social studies. He was a professor at Iowa State University and at the University of Wisconsin–Madison. He has served on ICF’s IRB for 12 years, and has been a statistical editor for the Journal of the American Medical Association for the past 15 years. He has extensive experience in statistical design and analysis, with more than 30 refereed articles published in statistical methods,. Dr. Iachan has extensive experience providing sampling and survey design support for many cancer-related projects for the Centers for Disease Control and Prevention (CDC) and other agencies, including cancer registry studies and heart disease prevention.![IconGems-Print](images/IconGems-Print.png)
502 – Innovative Statistical Methods for Complex Survey Data
Model-Based Evaluation of Local Alcohol Prevention Programs for Under-Age Drinking
Ronaldo Iachan, PhD
ICF International, Calverton, Maryland
Richard Harding, MS
ICF
Shelley N. Osborn
ICF
Underage drinking is a persistent threat to the health and well-being of young people with substantial societal costs. The paper evaluates the impact of grantees' environmental impact strategies to reduce underage drinking and associated misconduct. We built databases that included performance measures submitted by grantees and outcome measures, such as campus liquor law violations and traffic accidents. We then geographically mapped these data to the grantee's intervention catchment area using the first three digits of the zip codes or the section center facility code (SCF). We tested specific hypotheses about the relationship between the intervention activities and youth outcomes. We then included state-level alcohol policies to the dataset to created multilevel models examining the effects of state-level alcohol policies as a measure of alcohol control.