Theoretical concepts and computational methods using SAS applications

The following individuals were responsible for the production of this textbook.

Principal Author:
William J. Montelpare, Ph.D., Professor, and the Margaret and Wallace McCain Chair in Human Development and Health,
Department of Applied Human Sciences, Faculty of Science/Faculty of Nursing,
Rm 122, Health Sciences Building, University of Prince Edward Island,
550 Charlottetown, PE, Canada, C1A 4P3


Emily A. Read, Ph.D., RN, University of New Brunswick (

Teri McComber, Ph.D.(c), University of Prince Edward Island (

Alyson Mahar, Ph.D., University of Manitoba (

Krista Ritchie, Ph.D., Mount Saint Vincent University (


Together we achieved the main premise of this textbook, which was to present the basic concepts of statistical methods while using SAS coding methods to evaluate data and to develop a conceptual understanding of what the results are telling us about the data. While each chapter introduces the essential theoretical foundation of statistical concepts, each concept is presented through the unpacking of relevant examples using SAS programming code, and in some cases the use of Webulators© — web-based calculators written in JavaScript and HTML.

From a pedagogical perspective, this textbook will introduce the essential elements of statistical methods applied to research questions in health using applications at an intermediate level while providing examples for the reader to relate applications of these methods to health data. The methods include but are not limited to examples from health related disciplines — healthcare, health services delivery, and health promotion with a view to understanding and implementing research design and statistical applications that researchers may use as a basis for the development of research hypotheses and a theoretical foundation for program planning, policy changes, and program modifications.

The textbook is arranged intentionally for instructors and students to work through a logical approach to statistical applications that progress from basic concepts to more complex applications of statistical methodology.


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Applied Statistics in Healthcare Research Copyright © 2020 by William J. Montelpare, Ph.D., Emily Read, Ph.D., Teri McComber, Alyson Mahar, Ph.D., and Krista Ritchie, Ph.D. is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, except where otherwise noted.

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