Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics 2nd Edition

I am not a professional academic in the healthcare/statistics space, but have become increasingly involved in the area through work and wanted a good primer to refer to on construction of health studies. This book is definitely dense -- it's printed in black and green only, with minimal charts/graphs and a TON of text, so be ready to dive into a fairly heavy textbook read. But it is easy to understand and follow, even for my background (which is an MBA with some stats/regression training but no healthcare specific courses). It covers a good breadth of areas around setting up research studies, sample populations, and statistical results. I included a picture below of the table of contents and general format to give a sense of the topics covered. In general, very much recommend this text!

For professors seeking a new introductory-level textbook for their class, this could be an appropriate selection. The text has many of the treasured hallmarks for a beginner class:1.) Key terms are both bolded and italicized. This is not only effective in helping learning students discern which terms are most important, but this also becomes value when studying for exams.2.) Self assessment exercises allow students to be proactive in their studies. (Answers are provided for students).3.) Logical organization of text. Each chapter moves flawlessly into the next. Diligent students will be constantly building their knowledge base.4.) Learning objectives are presented in designated "boxes" at the beginning of each chapter. This allows students to prepare for the information to come as well as help students study for exams.5.) Charts and graphs are clearly presented (though the print is somewhat small).This text is fairly standard. While there is no innovation in the presentation of material, it will easily suffice.Worthy of consideration for the professor looking for a new text for the semester.

Lots of good information. It states what they expect you to know and doesn't waste time/space explaining 'background' type stuff. Intuitive layout for finding what you need, when you need it. Engaging, interesting information. A great textbook for someone interested in this field.

Well structured, (mathematical) concepts explained well, great as additional resource when studying for medical exams

✪ This is a book with very precise definitions and clear language.✪ It is one that geeky science boffins will appreciate.✪ This stuff is far beyond what my tiny brain can understand, but I still found scratching the surface quite interesting 🤓✪ This book is very, very thorough.✪ I found the chapter on Systematic Reviews and Meta-Analysis(Chapter 9) particularly useful.CHAPTER 9========• Introduction and Learning Objectives 385✪ Page 385 has definitions for "systematic review" and "meta-analysis" as indented paragraphs.✪ To assess the validity of various studies, there needs to be a systematic, rigorous approach — a review of all the evidence (published and unpublished)• Increasing Power by Combining Studies 386• Resource Papers 387• 9.1 The Why and How of Systematic Reviews 387• 9.1.1 Why is it Important that Reviews be Systematic? 387• 9.1.2 Method of Systematic Review – Overview and Developing a Protocol 388• 9.1.3 Deciding on the Research Question and Objectives for the Review 389• 9.1.4 Defining Criteria for Inclusion and Exclusion of Studies 390• 9.1.5 Identifying Relevant Studies 391✪ On page 391, I found the discussion of *publication bias* particularly interesting. 🤔✪ A simple literature search of electronic databases is not enough — not all published, peer-reviewed studies are there — and you need to look at unpublished studies, too.✪ Studies reporting statistically significant results are more likely to be published.✪ On page 392, a website that acts as a registry for clinical trials in the UK is mentioned.✪ A caveat of all this is that including data from unpublished studies can itself introduce bias 😩😩✪ You need to use techniques in Section 9.2 (like doing a funnel plot) to investigate.• 9.1.6 Assessment of Methodological Quality 396• 9.1.7 Extracting Data 399• 9.1.8 Describing the Results 399• 9.2 The Methodology of Meta-Analysis 402• 9.2.1 Method of Meta-Analysis – Overview 402• 9.2.2 Assessment of Publication Bias – the Funnel Plot 403• 9.2.3 Heterogeneity 405• 9.2.4 Calculating the Pooled Estimate 407• 9.2.5 Presentation of Results: Forest Plot 408• 9.2.6 Sensitivity Analysis 409• 9.2.7 Statistical Software for the Conduct of Meta-Analysis 410• 9.2.8 Another Example of the Value of Meta-Analysis – Identifying a Dangerous Treatment 411• 9.3 Systematic Reviews and Meta-Analyses of Observational Studies 414• 9.3.1 Introduction 414• 9.3.2 Why Conduct a Systematic Review of Observational Studies? 414• 9.3.3 Approach to Meta-Analysis of Observational Studies 415• 9.3.4 Method of Systematic Review of Observational Studies 416• 9.3.5 Method of Meta-Analysis of Observational Studies 416• 9.4 Reporting and Publishing Systematic Reviews and Meta-Analyses 418• 9.5 The Cochrane Collaboration 419• 9.5.1 Introduction 419• 9.5.2 Cochrane Collaboration Logo 422• Collaborative Review Groups 422• 9.5.3 Cochrane Library 422• 9.6 Answers to Self-Assessment Exercises 423

Well it’s a hefty book, but incredibly well written, and could be used by any discipline collecting observational data. I love authors that make you think about your assumptions and methodology and accept that categorisation involves some falsification or ambiguity (for instance suicide rates when the coroner has returned an open verdict, even though the poor train driver watched someone throw themselves off a railway bridge). There are very clear breakdowns of the derivation of Greek terms. It’s a book that wants to lead you through the scary bits and come out the other end confident of your approach. Not an easy journey, but for once, an excellent textbook.

This book is DENSE. It's been some time since I worked on stats and this will throw you right in. It's not a light read and is meant to be best used alongside self assessments inside and companion website.If you are interested or curious about health stats, are a high level student or keen enthusiast you, have a reasonable grasp of maths, then I can't fault this book. You will need to put the time in and do the assessments to get the most from this book. If you are a casual reader then I wouldn't recommend this, while it does talk about different methods of statistical study, pros and cons, it's not a discussion couched in the social sciences of psychology and sociology - although if you are at degree level, then this would be of use when designing experiments.It is a good book as long as you understand what you are getting. A high level workbook on stats based in the health sector.

This is an excellent text from Wiley. Perfect for students in the healthcare field to support their research methodology for dissertations or doctoral theses, and also for those working in the field - and, really, for anyone conducting an academic or professional research project.. Although it is aimed at health research, much of the content is transferable. It is very comprehensive and detailed, giving not just the nuts and bolts of the mathematical side of it, but the real world practicalities of conducting research - especially research involving people in all their infinite variety. One major focus is on dealing with self-assessment based research, something that is most important due to the limitations normally imposed by researchers - and compounded by the self-awareness, or lack thereof, of the population being researched. And that's just one example of the wide range of the expertise shared within this book. This is a super resource produced by folks who know what they are talking about.