Amang Sukasih

Amang Sukasih is a senior research statistician in RTI’s International Statistics Program. Dr. Sukasih is an expert in survey sampling design, experimental and quasi-experimental designs, adaptive survey design, weighting calculations, and nonresponse adjustments, including imputation for missing data. He also has experience with complex survey data analysis, variance estimation, small area estimation, statistical disclosure avoidance, statistical process control, and design and analysis of methodological studies.

Dr. Sukasih specializes in survey design and sample selection for surveys relating to military populations and postsecondary graduates. He has designed surveys with areas, housing units, households, educational institutions, and individual persons as the sampling unit. He is experienced with sampling frames based on address, phone number, and traditional list frames. Dr. Sukasih served as the project director and task leader for the NCHS Model-Based Estimation project to review, improve and make recommendations on nowcasting and small area estimation modeling to produce timely and granular estimates based on NCHS data. Dr. Sukasih also served as the project director and task leader for the NCHS NAMCS sampling design. He improved the sampling design for the physician and physician assistant sampling.

Dr Sukasih is a proficient SAS and R programmer and has experience with 20 programming languages. Dr. Sukasih has coauthored many papers about sampling, small area estimation, and nonresponse adjustments. Dr. Sukasih authored a paper on the Cyclical Tree-Based Hot Deck imputation, an RTI proprietary tool for imputing large scale complex survey data that capable to handle imputation for many different types of variables, as well as complex relationship across these variables. Outside of RTI International, he reviews journal manuscripts and papers.