Best Biostatistics
This most widely used textbook in the field has been thoroughly revised and updated to reflect changes in the health care industry and the renewed focus on health care information technology initiatives. Frances Wickham Lee , DBA, is professor and director of instructional operations for Healthcare Simulation South Carolina at the Medical University of South Carolina (MUSC).
Reviews
Find Best Price at Amazon"I will say, with the way technology and healthcare are changing so quickly these days, don't take too long too read it or it may become quickly outdated."
"I use this book in an introductory health informatics course."
"I didn't enjoy the class for many reasons but this book helped a lot for understanding of the topic presented!"
"I really enjoyed reading this textbook as well as learning more from this book."
"Good starting reference for a degree in Masters in Health Informatics."
"For those who feel comfortable in reading a hard copy than the online one, this is great asset."
"While the text has some erudite points about the meaning and purpose of medical records, it is out of date and never mentions the VA medical system which has completely automated, integrated medical records for all of its facilities."
Winner of the 2014 Technometrics Ziegel Prize for Outstanding Book Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. "There are a wide variety of books available on predictive analytics and data modeling around the web...we've carefully selected the following 10 books, based on relevance, popularity, online ratings, and their ability to add value to your business. "This monograph presents a very friendly practical course on prediction techniques for regression and classification models...The authors are recognized experts in modeling and forecasting , as well as developers of R packages and statistical methodologies...It is a well-written book very useful to students and practitioners who need an immediate and helpful way to apply complex statistical techniques." However, in my judgment, Applied Predictive Modeling by Max Kuhn and Kjell Johnson (Springer 2013) ought to be at the very top of the reading list ...They come across like coaches who really, really want you to be able to do this stuff.
Reviews
Find Best Price at Amazon"I read "Applied predictive modeling" (which I will shorten to APM) shortly after I read "Introduction to statistical learning" (ISL) by James, Witten, Hastie and Tibshirani, and find that book both closest to APM, and helpful in highlighting APM's strengths. Adopting H&T's terminology choice, I will say that both books combine theory of "statistical learning" with hands-on illustrations and exercises implemented in R; the get-your-hands-dirty, try-it-out element is, in fact, ISL's key difference from the earlier, venerable "Elements of statistical learning"."
"Max Kuhn is a legend in R like Hadley Wickham."
"I read this cover to cover, it's incredibly well written without sacrificing technical explanation."
"Great book for understanding concepts, and the R code can be used right away in your own projects."
"Excellent insights on the strengths and weaknesses of traditional machine learning models."
"This book is really good for those who want doing some data analysis!"
"It addresses very important concepts in predictive modeling (i.e., over-fitting and predictor's reduction) and provides efficient R codes for testing."
"And by using R, a freely accessible language, the writers ensure the reader will be able to immediately apply the information in the real world."
Introduction to Meta-Analysis : Outlines the role of meta-analysis in the research process Shows how to compute effects sizes and treatment effects Explains the fixed-effect and random-effects models for synthesizing data Demonstrates how to assess and interpret variation in effect size across studies Clarifies concepts using text and figures, followed by formulas and examples Explains how to avoid common mistakes in meta-analysis Discusses controversies in meta-analysis Features a web site with additional material and exercises. The reader can comfortably skip the. formulas and still understand their application and underlying motivation. For the more. statistically sophisticated reader, the relevant formulas and worked examples provide a superb. practical guide to performing a meta-analysis.
Reviews
Find Best Price at Amazon"That chapter was very easy to understand, plus it went into adequate depth for me, plus it gave very nice working examples. He shows you theoretical formulae, then he gives you actual examples with numbers to plug into the formulae. I only wish he covered ANOVA and Multiple regression in a dedicated chapter, explain them from ground up, in simple terms, go into depth, and show examples."
"If you know nothing about this topic, this book might not be your best starting point."
"It's a great book."
"This is a textbook I needed for a graduate seminar."
"Introduction to Meta-Analysis is straight forward and easy to read."
"Though I only have a background in applied statistical methodology, I found this book easy to follow and, more importantly, understand."
"The only downside was that at the time I ordered it, Amazon did not have any in stock, so it took more than 5 weeks to be delivered..."
"This book was assigned in the Meta-Analysis class I took and it was really helpful."
Best Biostatistics
Winner of the 2014 Technometrics Ziegel Prize for Outstanding Book Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. "There are a wide variety of books available on predictive analytics and data modeling around the web...we've carefully selected the following 10 books, based on relevance, popularity, online ratings, and their ability to add value to your business. "This monograph presents a very friendly practical course on prediction techniques for regression and classification models...The authors are recognized experts in modeling and forecasting , as well as developers of R packages and statistical methodologies...It is a well-written book very useful to students and practitioners who need an immediate and helpful way to apply complex statistical techniques." However, in my judgment, Applied Predictive Modeling by Max Kuhn and Kjell Johnson (Springer 2013) ought to be at the very top of the reading list ...They come across like coaches who really, really want you to be able to do this stuff.
Reviews
Find Best Price at Amazon"I read "Applied predictive modeling" (which I will shorten to APM) shortly after I read "Introduction to statistical learning" (ISL) by James, Witten, Hastie and Tibshirani, and find that book both closest to APM, and helpful in highlighting APM's strengths. Adopting H&T's terminology choice, I will say that both books combine theory of "statistical learning" with hands-on illustrations and exercises implemented in R; the get-your-hands-dirty, try-it-out element is, in fact, ISL's key difference from the earlier, venerable "Elements of statistical learning"."
"Max Kuhn is a legend in R like Hadley Wickham."
"I read this cover to cover, it's incredibly well written without sacrificing technical explanation."
"Great book for understanding concepts, and the R code can be used right away in your own projects."
"Excellent insights on the strengths and weaknesses of traditional machine learning models."
"This book is really good for those who want doing some data analysis!"
"It addresses very important concepts in predictive modeling (i.e., over-fitting and predictor's reduction) and provides efficient R codes for testing."
"And by using R, a freely accessible language, the writers ensure the reader will be able to immediately apply the information in the real world."
Best Epidemiology
Key Features: - Comprehensive coverage of the ACA and its impact on each aspect of the U.S. health care system woven throughout the book. - New "ACA Takeaway" section in each chapter as well as a new Topical Reference Guide to the ACA at the front of the book. - Updated tables and figures, current research findings, data from the 2010 census, updates on Healthy People 2020, and more. - Detailed coverage of the U.S. health care system in straightforward, reader-friendly language that is appropriate for graduate and undergraduate courses alike.
Reviews
Find Best Price at Amazon"The CD that comes with the book was not updated to work along side the chapters."
"Received in excellent condition."
"exactly what it was supposed to be."
"Great book for not only my course, but very detailed for understanding healthcare in America."
"I didnt want to return this book it was so good."
"Did not expect a brand new book when I was ordering a rental one."