Synopses & Reviews
Converting Data into Evidence: A Statistics Primer for the Medical Practitioner provides a thorough introduction to the key statistical techniques that medical practitioners encounter throughout
Synopsis
Statistics and Causality.- Summarizing Data.- Statistical Inference: Testing and Estimation.- Confidence Intervals, Another Test, and Statistical Power.- Bivariate Statistical Techniques.- Linear Regression Models.- Nonlinear Regression Models.- Survival Analysis.- Other Regression Techniques.- Concluding Comments.- Glossary.- References.
Synopsis
Converting Data into Evidence: A Statistics Primer for the Medical Practitioner provides a thorough introduction to the key statistical techniques that medical practitioners encounter throughout
Synopsis
This book provides an introduction to key statistical techniques medical practitioners encounter throughout their careers. It utilizes real data sets from recent clinical trials and observational studies in urology to illustrate data analysis techniques.
About the Author
Alfred DeMaris earned a Ph.D. in sociology from the University of Florida in 1982 and a master's degree in statistics from Virginia Tech in 1987. He is currently professor of sociology and statistician for the Center for Family and Demographic Research at Bowling Green State University in Bowling Green, Ohio. His other statistical monographs are
Logit Modeling: Practical Applications (Sage, 1992) and
Regression with Social Data: Modeling Continuous and Limited Response Variables (Wiley, 2004). He has published another dozen articles and book chapters on statistical techniques as well as approximately 70 journal articles on topics in family social psychology. His work has appeared in
Psychological Bulletin, Sociological Methods & Research, Social Forces, Social Psychology Quarterly, Journal of Marriage and Family, and
Journal of Family Issues, among other venues. He was twice awarded the Hugo Beigel Award for the best empirical article in the
Journal of Sex Research. He has been teaching statistics at the undergraduate and graduate levels for the past thirty years. Through his company, Statistical Insights, he does statistical consulting on a regular basis for individuals in the social and behavioral sciences as well as those in medicine and industry.
Steven Selman received his undergraduate degree in Engineering Physics at the University of Toledo. Following his medical school training at Case Western Reserve University he completed residencies both in General Surgery and Urology at University Hospitals of Cleveland. His research interest has principally been in the arena of urologic oncology and methodologies of urologic resident education. He has over 100 publications in the peer reviewed urologic literature. Currently, Dr. Selman serves both as residency Program Director and Chair of the Department of Urology at University of Toledo Medical Center.
Table of Contents
Statistics and Causality.-