This textbook is designed to address the specific needs and challenges of all health professionals. It begins with a comprehensive introduction to the field of epidemiology, outlining its history and fundamental goals. It discusses statistical and valid statistical associations, including discussion of chance, bias, and confounding, as well as criteria for judging causality based on the totality of the evidence.
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Panagiota Kitsantas, Ph.D. is Professor of Biostatistics/Epidemiology at the Department of Health Administration and Policy, George Mason University. She is formerly Professor and Chair of the Department of Population Health at the Schmidt College of Medicine (COM), Florida Atlantic University (FAU).
Maria Carmenza Mejia, M.D., M.P.H., FACPM, FASAM is Professor of Population Health at the COM at FAU and is double board certified in preventive and addiction medicine. She is formerly Professor of Family and Community Medicine at the Baylor College of Medicine.
Charles H. Hennekens, M.D., FACPM, FACC is the first Sir Richard Doll Professor of Medicine and Preventive Medicine at the COM, FAU. He is formerly the first John Snow as well as first Eugene Braunwald Professor of Medicine at the Harvard Medical School and first Chief of Preventive Medicine at Brigham and Women’s Hospital.
Gina Seits, BS is Assistant Director of Population Health Administration and Grant Support at the COM, FAU.
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Paperback. Condición: New. This textbook is designed to address the specific needs and challenges of all health professionals. It begins with a comprehensive introduction to the field of epidemiology, outlining its history and fundamental goals. It discusses statistical and valid statistical associations, including discussion of chance, bias, and confounding, as well as criteria for judging causality based on the totality of the evidence. Nº de ref. del artículo: LU-9798823361286
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Paperback. Condición: new. Paperback. This textbook is designed to address the specific needs and challenges of all health professionals. It begins with a comprehensive introduction to the field of epidemiology, outlining its history and fundamental goals. It discusses statistical and valid statistical associations, including discussion of chance, bias, and confounding, as well as criteria for judging causality based on the totality of the evidence. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9798823361286
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