Each topic starts with an explanation of the theoretical background necessary to allow full understanding of the technique and to facilitate future learning of more advanced or new methods and software
Explanations are designed to assume as little background in mathematics and statistical theory as possible, except that some knowledge of calculus is necessary for certain parts.
SAS commands are provided for applying the methods. (PROC REG, PROC MIXED, and PROC GENMOD)
All sections contain real life examples, mostly from epidemiologic research
First chapter includes a SAS refresher
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MARI PALTA, PHD, is a professor in the Department of Population Health Sciences and Biostatistics and Medical Information at the University of Wisconsin-Madison
A user’s guide to advanced statistical techniques for nonstatisticians
The study of population health often involves the use of observational data from existing data sets, complex survey designs and longitudinal follow-up. Ordinary regression analysis, familiar to most researchers and practitioners is inadequate for analyzing such data and answering important questions about the relationship of risk factors to health. Nonstatisticians such as epidemiologists and health services researchers require a working knowledge of the sophisticated modeling techniques used by professional statisticians. Quantitative Methods in Population Health provides an accessible guide for students in an applied statistics sequence as well as for practicing researchers and professionals.
Mari Palta’s timely text assumes some background in mathematics and in applied statistics and regression analysis, but little knowledge of statistical theory. The Statistical Analysis System® (SAS) is an ubiquitous tool in the field, and some basic knowledge of its structure is assumed. Each topic starts with an explanation of the theoretical background that is necessary for understanding the technique as well as for establishing a basis to adopt more advanced methods or software in the future. The author endeavors to keep the material immediately applicable by providing detailed instructions for how to run and interpret procedures in SAS. Topics covered include:
SAS commands for applying the methods–including PROC REG, PROC MIXED, and PROC GENMOD–are provided, and each section includes real-life examples. Quantitative Methods in Population Health proves a seamless meshing of the theoretical and practical in this vital field.
A user’s guide to advanced statistical techniques for nonstatisticians
The study of population health often involves the use of observational data from existing data sets, complex survey designs and longitudinal follow-up. Ordinary regression analysis, familiar to most researchers and practitioners is inadequate for analyzing such data and answering important questions about the relationship of risk factors to health. Nonstatisticians such as epidemiologists and health services researchers require a working knowledge of the sophisticated modeling techniques used by professional statisticians. Quantitative Methods in Population Health provides an accessible guide for students in an applied statistics sequence as well as for practicing researchers and professionals.
Mari Palta’s timely text assumes some background in mathematics and in applied statistics and regression analysis, but little knowledge of statistical theory. The Statistical Analysis System® (SAS) is an ubiquitous tool in the field, and some basic knowledge of its structure is assumed. Each topic starts with an explanation of the theoretical background that is necessary for understanding the technique as well as for establishing a basis to adopt more advanced methods or software in the future. The author endeavors to keep the material immediately applicable by providing detailed instructions for how to run and interpret procedures in SAS. Topics covered include:
SAS commands for applying the methods–including PROC REG, PROC MIXED, and PROC GENMOD–are provided, and each section includes real-life examples. Quantitative Methods in Population Health proves a seamless meshing of the theoretical and practical in this vital field.
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