PDQ Epidemiology
PDQ Epidemiology Books
Product Description
PDQ Epidemiology is an exceptionally clear and highly irreverent review of the vital concepts of medical statistics and their impact on broadcast health policy. As the authors note in their preface: “…the role of Epidemiology these days fills the gaping chasm between the scientific wisdom of the wet laboratory and the clinical wisdom of the ward.” By translating the language of epidemiology into simple to know language, the common sense of the methods emerges and makes sense to students. Featuring unique examples, titled Intricate Reasoning or Anti-intellectual Pomposity Detectors (CRAP Detectors), the text helps the reader identify studies with basic flaws in design or research.
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A very cursory overview of the field of epidemiology. One skim through it and you felt like you read the beginning chapter of a different, real book on the topic. Where PDQ statistics gets into detail enough so that you can converse intelligently with a statistician, after reading this book you’ll sound like a freshman in undergrad. Don’t waste your time or money on this title.
Rating: 1 / 5
This is the best introduction and explanation available for epidemiology. It’s a very concise, illustrative but comprehensive huge picture(and the trees also) of this theme. Nearly everything is clarified with an example, and you can read as a novel. All the others books of epidemiology are complementary to this, but if you have this and the Epidemiology: An Introduction by Kenneth J. Rothman
OR
Epidemiology by Leon Gordis
OR
Clinical Epidemiology: The Essentials by Robert H Fletcher and Suzanne W Fletcher
you have all you need to know what is epidemiology about. Thanks to the authors to share his enthusiasm and sense of humor.
Rating: 5 / 5
If you like to know where each part of statistics fit in with other parts, start with this book. This is a Macro view of statistical analysis, not a nuts and bolts one. Nevertheless, one needs to know the major distinctions of the categories and subcategories of statistical analysis, and this book does a wonderful job at it. Urge it for anyone who cares about the judgment of statistics.
Rating: 5 / 5
In four small chapters, the authors cover a lot of ground, including: research methodology, measurement, and causation. The third chapter covering measurement is especially rich in imparting knowledge. It clarifies clearly many concepts such as sensitivity, specificity, and Bayes’ theorem. The authors do an brilliant job of explaining complex materials such as the ROC curves. This latter concept is challenging, and they make it pretty accessible.
One of the reviewers plotting this was a poor guide to epidemiology because it did not cover enough technical ground. I’d argue that all this book is proposed to do is give you a quick overview of the field. After all, that’s what the PDQ run is all about. In this perspective, the authors have done an outstanding job. They even describe some of the underlying judgment pretty well. They also do a fantastic job at demonstrating all the traps that laypersons and even scientists fall into when interpreting epidemiological studies.
But, to supplement this high-level knowledge you have to study a more extensive textbook on the theme. Other reviewers urge several excellent ones. And, you also got to buy an brilliant foundation in statistics. In this regard, I urge three books you may possibly study in sequential orders. The first one that serves as a excellent refresher is Forgotten Statistics. The second one that covers extensively all the statistics correlated to biostatistics and epidemiology is Intuitive Biostatistics. And the last one is Nonparametric Statistics: An Introduction (Quantitative Applications in the Social Sciences). With this bought statistical background, you will be properly equipped to go forward in your studies in epidemiology or biostatistics.
Rating: 5 / 5