Ronaldo Iachan, PhD
ICF, 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.
647 – Current Federal Research on Improving Measurement of LGBT Populations
Methods for Calculating State and National Prevalence Estimates: An Application of Estimates of Sexual Orientation and Gender Identity
Ronaldo Iachan, PhD
ICF, Calverton, Maryland
Yangyang Deng
ICF
Carol Pierannunzi
Centers for Disease Control and Prevention
This research focuses on the methods for modeling estimates at the state level when data are available from a subset of states. We used the Sexual Orientation and Gender Identity (SOGI) optional module questions from the Behavioral Risk Factor Surveillance System (BRFSS) for 2014 to 2016 to develop models and provide estimates for all states. Models are validated against direct estimates where available. SOGI questions represent the most vigorous test of such a model in that limited proportion of the sample who identify as transgender, bisexual and/or gay/lesbian. The process presented also provides a mechanism for imputation of responses where non-substantive answers are given (i.e. "do not know" or refusal to answer). The methodology is adaptable to other BRFSS optional models used by subsets of the states annually.