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Hindi Journal of Applied Bioinformatics & Computational BiologyISSN: 2329-9533
Baojiang Chen Author
Subjects of specialization
Affiliation
Biostatistics, Statistics, Statistical Analyst, Statistics and Actuarial Science
Department of Biostatistics and Data Science, School of Public Health in Austin the University of Texas, Canada
Biography
Dr. Baojiang has received his Ph.D in Statistics from University of Waterloo, Canada and M.S.Statistics from Nankai University, China. Present he is working as associate professor at Department of Biostatistics, School of Public Health in the University of Texas Health Science Center at Houston.
Publications
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Missing Data: A Non-ignorable Issue in Modern Biostatistics
Author(s): Baojiang Chen and Kendra K. Schmid
Missing Data: A Non-ignorable Issue in Modern Biostatistics
Missing data is a common feature in modern biostatistics. For most cases, the easily implemented method such as complete case analysis will yield biased conclusions if data are Missing At Random (MAR) or Missing Not At Random (MNAR). The vast majority of articles in the literature dealing with incomplete data make the unrealistic assumption that data are available for the response but incomplete for the covariates or risk factors, or alternatively, they assume that information on risk factors is complete, but the data on response are incomplete.
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