No comments about Study Guide to Epidemiology And Biostatistics (Study Guide to Epidemiology and Biostatistics) (Study Guide to Epidemiology and Biostatistics).

5 comments about Essentials of Epidemiology in Public Health, Second Edition.

1. This was a required text for a graduate intro to epidemiology course that I took, and I've held on to it since then. Overall the content is well organized and clearly written. That being said, there were also a few important sections that I found very confusing, and there do appear to be at least a few errors in text and arithmetic. The authors are generally fairly concise in their descriptions of types of studies, sources of error, etc., which makes for good overall readability, however I often wished they would give a few more details and examples. In spite of these criticisms, I've looked through a lot of epidemiology books, and they all seem to have limitations. It's probably impossible to identify one introductory text that will be the best choice for everyone. No matter which one you pick up, you will likely benefit from having another one on hand for comparison when a passage or problem is unclear, confusing or underemphasized. In my opinion this book is an excellent choice for those with a general interest in epidemiology for public health practice and who are looking for good readability. I've found that it also serves as a good basic reference on epidemiological studies.



2. This is a great text for anyone studying epidemiology.
   
   Each chapter on the various aspects of Epi (ie, Confounding, Effect Modification, Random Error, Bias, Causation, etc) is readable, relatively short chapters (no more then 20 pages) and very clearly explains the necessary information. Each chapter then has a concise (less then one page) summary, perfect for test studying or board review. In addition, each chapter has test questions with answers posted at the back of the book. This book even explains the underlying mathmetical principles better then most statistic texts I've used.
   
   While you could probably get through Epidemialogy just reading the lecture notes, this book will guarantee you understand it (with out spending too much time) and get a 4.0.



3. It is a good book for beginners. A little outdated but overall does the job effectively explaining the basic concepts.



4. I am totally disappointed with this purchase. I was expecting the latest version that came out in this year. But I received a previous version. Till then I was deperately trying to reach the vendor (Scholasticbooks) to return/ exchange it. But even after e mails and phone calls I am yet to hear from them. I do not recommend this vendor to any one.



5. What a great read. No, really... I'm actually enjoying reading it! The authors do a great job of presenting existing research and breaking down complicated theoretical concepts in a fresh and interesting way that's a quick, substantive read. I bought mine on clearance - what a great investment! definitely what I was looking for as a beginner to the field of public health/epidemiology.

5 comments about Reading and Understanding Multivariate Statistics.

1. "Reading and Understanding Multivariate Statistics" achieves exactly what its title implies. Geared toward non-statisticians in behavioral and social science fields, this book provides clear and reasonably simple explanations of some of the most common multivariate analyses. Each chapter focuses on a different analysis and presents its conceptual underpinnings, underlying assumptions, and basic procedures with a minimum of equations and many concrete examples. It does not teach you how to perform the analyses but does provide references for those who wish to get more detailed information. As a research scientist who doesn't always remember everything I learned in graduate statistics class, I find this book an invaluable aid keeping up with the current literature in my field and in making the most of statistical consultations. This book is ideal for anyone whose job requires them to be a "consumer" of research; for researchers who wish to further their understanding of data analysis; and as a companion text for graduate statistics classes.



2. In many introductory statistics courses you usually do not cover multivariate statistics. This book and its companion volume are useful for anyone in upper level undergraduate or graduate programs. It is a great reference to have when planning research.

   You can read it all at once to get a general understanding of this area or you can look at it as you need it as a reference. It was much better than the statistics books I have had as required reading in courses. It's a great resource overall!




3. I've long wanted a better explanation of Eigenvectors and Eigenvalues than I recieved in a econometrics or statistics textbook. This book gives me an incredibly clear understanding of what they are. Now when I look back at the mathematical interpretation again it means so much more. This is a fantastic book that would highly recommend to anyone wanting a clear conceptual understanding of these sophisticated topics. 5 stars, no questions about it!



4. A good resource for someone taking a psyc stat class.



5. This book is an excellent high-level overview of multivariate statistics and the techniques for working with multivariate data.
   
   It doesn't go into detail making it a very good read for people wanting to learn multivariate concepts.

5 comments about Health Behavior and Health Education: Theory, Research, and Practice.

1. Chapters are disjoint at times, with no reference to similar concepts between them. Almost as if they were all written separately without any editing to tie them all together.
   
   Information is presented in something less than an interesting manner - it's pretty dry!



2. This book is very useful to anyone involved in the public health field for research or developing interventions to address any health behavior with any group. I'm glad I purchased it. I highly recommend it as a valuable resource.



3. I purchased this book to use as a reference for a Graduate Project on Health Promotion. I was particularly interested in Planning Models so most of my research focused on Part 5 in the book
   Excellent Book-I highly recommend it
   Judy W.



4. Good book for a class on Health Behavior and Health Education Theories. Good for graduate level work. Theories broken into chapters. Each chapter has the theory history, significant time line for the theory, chart and descriptions of the constructs, and examples where research has used the theory effectively. Examples in book make use of the theory more understandable.



5. This was a good deal and I saved $30. it was new and exactly as described. thanks.

5 comments about Basic & Clinical Biostatistics (LANGE Basic Science).

1. I bought this book in 1990 (an older version) and have never had a statistics course. I have found it to be an extremely helpful starting point for the application of statistical tests to biomedical problems. From this I have gone on and used more sophisticated tools for computation and have only rarely needed to seek out the advice of experts.
   
   The book is packed full of information and covers the broad range of problems most often encountered in biomedical science. It emphasizes an understanding of the choice an appropriate test for a given problem. Flow charts also help guide the user to the right test and the correct chapter. For this reason I have come back to it repeatedly over the years and it has become well worn. It is sparse on explanation of the statistical or mathematical proofs of methods so it is more of a cookbook than as a theoretical treatise.



2. I have very little background in biostats, and need to learn it for medical research and research design.
   
   This book is difficult to read, has far too much emphasis on mathematics and far too little empahisis on concept. After a whole quarter in Biostats using this book, I can tell you very little about how and when to employ certain basis statistics tests or interpret them with confidence. The answers in the back are ofter erroneous, as is some of the text (according to my professor).
   
   The only thing I can seay that is good about this test is that the NCSS software that comes with it I think may be helpful at some point.
   
   I am back in the market for a better book!



3. The book is very detailed and an excellent read and resource for anyone who is in the field of science and someone who reads scientific peer-reviewed journal articles. Though there were some errors in some calculations in the book, overall, it is very helpful and a great way to learn biostatistics and applications in the clinical setting and research settings.



4. I had to purchase this book for a class I am taking. This is a fourth edition book and I have to correct errors before reading each chapter. I give publishers some leeway on a first edition, but by the fourth the kinks should be worked out. Also, there is some crucial information missing when making the calculations and sometimes it does not give enough detail on how to work through the problems.



5. As a grad student required to take a Biostats class, this book sucks. I like that real examples from the literature are used, but one cannot learn what is needed for real life from this book. And no one uses NCSS in real life when analyzing data.

5 comments about Intuitive Biostatistics.

1. A really nifty book for anyone--and that's most of us--interested in what basic statistical tests mean and how to use them. Even someone with a pretty advanced knowledge of statistics may not understand all of the intuitive concepts described in this book. Consistent with its title, it is probably best suited for those in the biosciences, rather than engineers, for example, but I'd say that people in those more technical fields may very well benefit greatly from reading it. It's written in a conversational manner that is easy to digest. I'd say a lot of thinking by the author went into creating it, because he seems to guess what the reader may be thinking and then answers those questions. He's big on the confidence interval, too. Readers who need more specialized, detailed info on a particular topic, such as two-way ANOVA, probably need to consult an additional text. Overall, a great introduction to fundamental statistical concepts and tests, that will be of interest to biological scientists and many other folks, too. Author of Adjust Your Brain: A Practical Theory for Maximizing Mental Health.



2. Dr. Motulsky is an MD who is also a Professor of Pharmacology and President of his own software company. The book's title suggests that he can make biostatistics intuitive for non-statisticians (e.g. physicians, clinicians and nurses). After reading through it he has made a believer out of me! He introduces concepts through examples and touches on most of the important statistical methods that are used in the medical literature. While the book could be used as a classroom text, it seems to me to be more suited as a reference source for medical researchers who want to understand the statistics described in research papers. Although not a statistician by training, Dr. Motulsky has a good understanding of statistical methods and principles and exhibits his wisdom and experience throughout the book. He is deliberate at keeping things simple and to the point. He points out that he intentionally uses fake examples and modifies real examples for simplification of exposition. He avoids mathematics as much as possible. the preface and the introduction are very well written and the reader should read both before reading the rest of the text.
   My usual concern with such books is that concepts are oversimplified and the presentation is too cook-bookish. Amazingly that is not the case here. Professor Motulsky carefully explains concepts such as confidence intervals, p-values, multiple comparison issues, Bayesian thinking and Bayesian controversy in a way that should be understandable to his intended audience.
   
   Proportions and the binomial distribution are introduced early. Advanced topics such as sequential methods, survival curves and logistic regression are tackled. These subjects are important in medical research but are often avoided in elementary books. To his credit he also does a very good job of introducing the concepts of sensitivity and specificity. Hypothesis testing is introduced at the same time which makes a lot of sense since for a particularly hypothesis test the specificity and the sensitivity are related to the type I and type II errors. It is a good way for those familiar with medical applications where specificity and sensitivity may be intuitive concepts, to become comfortable with the less familiar null and alternative hypotheses and their associated error probabilities.
   
   Professor Motulsky writes eloquently and this appears to be appreciated by the readers, judging from the other reviews that I have seen on Amazon. Having said all this you might wonder why I didn't give it 5 stars. I found a few things that could have been done better.
   
   I am not completely happy with the way probability is introduced through the binomial distribution and here the wording could be improved. He writes "Mathematicians have developed equations, known as the binomial distribution, to calculate the likelihood of observing any particular outcome when you know the proportion in the overall population." Actually the binomial distribution is a probability distribution (which he has not yet defined as he first uses the term distribution). The equation is a statement that the probability of an event (e.g. exact 7 heads in 10 coin flips) is given by equation (2.2) on page 19 with N=10 and R=7 and p=1/2 (assuming a fair coin).
   
   Another area that could be omitted or else improved is the discussion of Bayesian ideas. Bayes theorem is presented in a limited context related to the example of sensitivity and specificity. While I do think that some Bayesian ideas are well brought out the breadth of applications is missing. Some comparison of the frequentist and Bayesian approaches and philosophy are correctly described but the discussion is too brief to provide good insight. The p-value is strictly a frequentist concept. Motulsky relates it to the Bayesian idea of posterior odds for the null hypothesis to be true. While there is such a formal mathematical relationship, they are conceptually quite different. This is just like relating likelihood to posterior probability. Mathematically the likelihood and posterior probability are related through Bayes theorem as posterior = likelihood x prior but although likelihood is an acceptible frequentist concept posterior probability is not. A real understanding requires some knowledge of the sample space for a frequentist and the treatment of parameters as random quantities by Bayesians. I think this may be something that requires a little more mathematical sophistication than is intended for this readership.
   
   There are a few topics that get little or no treatment but deserve more in a biostatistics texts. These include missing data, resampling methods, hierarchical Bayesian models and longitudinal - repeated measures data. Perhaps we will see intuitive descriptions of some of these topics in the second edition.



3. This book goes straight to the point, assisting you in making the proper decisions with the statistical tests you need to use. Well written, well organized. A really good book coming from the same person who brought us a really good software (Prism).



4. One of the best handbooks I have ever seen in any subject. Since statistics or generaly mathematics is pretty hard for biologists to lern, it require special teching aproach designed to demonstrate logics behind statistical concepts. This book is uniquely doing exectly that. I have used several books in statistics for biologists, including small intorductory material and heavyweight Biometry, as well as numerous online stat dedicated sites. This is the book I strongly recommend for the bigginers interested in lerning statistics.



5. This text is by far the most readable book on statistics I've ever read. In addition, the software written by this author (GraphPad Prism) is also the most user-friendly and intuitive package available. In my opinion, the major benefit of this book is that it gets the reader to understand the conceptual basis of various experimental designs and statistical analyses, rather than blindly dumping data into a statistical package and hitting "go".

5 comments about Epidemiology, Updated Edition: With STUDENT CONSULT Online Access.

1. this book is required for our class. However, it is such a well-written book, that anyone interested in the basics of epidemiology would be able to understand the concepts and gain a deeper understanding of public health.



2. The most complete introductory book on market. For a more detailed textbook I would suggest looking at The Trichopoulos, Mac Mahon textbook.



3. This book explains everything very clearly. It has good concrete real examples of diff studies and the things that are wrong with them. There are very few review questions, however, and sometimes the book rambles on and gets repetitive.



4. This book is a wonderful concise reference in Epidemiology in relation also to health administration . It is extremely basic , straight forward from a leader in the field .
   I enjoyed the simplicity of examples.
   Asaad A. Abduljawad



5. This was a required text for my introductory epidemiology course. I have had an interest in epi for a number of years and approached the book with a fair amount of skepticism, especially given its relatively small size. After reading the first few chapters I found Gordis's writing style to be dry and too convoluted for otherwise simple topics. Saying this, halfway through the semester I really warmed up to the book and the author's subtle humor. The sections on odds ratios and matched/unmatched case-control studies were explained so well that I had a eureka moment that I had hoped for prior to taking my first USMLE step. For an introductory book, it covers with perfect detail the basic methods and principles of epidemiology and provides elegant descriptions of the applications to both clinical medicine and public health. The illustrations offer great clarity to the theory and I have already referenced them on many occasions during other courses and while reading journal articles. It will remain on my shelf until the next edition is released.

5 comments about Qualitative Data Analysis: An Expanded Sourcebook(2nd Edition).

1. I am working on my dissertation. This book got me out of my thinking chair and to my writing desk. The philosophical approach to qualitative research is very contemporary and will take us into whole new areas of research to improve and 'polish' humanity. My only objection is the cost. Does a book like this really have to cost over $60? Too much.



2. As a first time qualitative researcher, I found this book indispensible during my data analysis. It clearly explains multiple analytic techniques, providing the researcher with many alternatives to use in developing conclusions. The descriptions are easy to understand and supported by insightful examples. If you are looking for a roadmap to guide you through qualitative research, this is the GPS of qualitative data analysis.



3. Don't let the date published scare you away from this book. The guides are applicable to any person wishing to perform qualitative data analysis.



4. This book assisted me in my graduate classes for Kinesiology.
   
   I recommend it for any graduate students who need to take similar classes to mine.



5. This publication is well organized and covers a large scope of data analysis in qualitative research but did very little, in my opinion, to guide me, as a dissertation author, in the process of coding and thematic analysis. A book entitled Qualitative Data Analysis, I think, should cover the actual analysis of qualitative data more than the type of introduction to design of qualitative research. One finds this information in many, many other titles- and to a more useable extent to boot. Two of the 13 chapters were helpful in meeting my needs (Chapter 4: Early Steps in Analysis and Chapter 10: Making Good Sense: Drawing and Verifying Conclusions) While there is a wealth of information presented in a well-written manner such as information about the display of data, my initial reading of the book was followed by immediate shelving.

1 comments about Modern Epidemiology.

1. Masterly. Rothman and coworkers' 3rd edition of the classic `Modern Epidemiology' is a landmark step in presenting with cohesiveness and clarity traditional + cutting-edge concepts and methods for observational research (and by extension for experimental research on human subjects as well, since problems like unblinding or loss-to-follow-up may reintroduce bias in clinical trials after randomization, with a corresponding need for epidemiological interpretative and analytical tools).
   This highly regarded volume has no equal, as it has been not only an authoritative source of information but `the' reference on epi methods for almost a quarter century. For those looking for an introductory level textbook, Rothman's one by Oxford University Press is highly recommended, since the comprehensive `Modern Epidemiology' requires some previous exposure to the concepts and biostatistical methods presented.
   The 3rd edition is an encyclopedic effort, brings methodological coherence to a whole new level, is highly readable, and confirms itself as the standard reference on epidemiological and clinical research for many more years to come. An outstanding scholarly achievement.
   Definitely a must-have for anyone who needs to learn and apply basic/advanced epidemiological methods rigorously in clinical as well as general population settings.

5 comments about Designing Clinical Research: An Epidemiologic Approach.

1. "Designing Clinical Research: An Epidermiologic Approach" did a thorough analysis of various methodologies, which medical scientists could use in everyday research. It, first of all, outlined all the essential steps (used in epidemiological research), before delving into the analysis of each step. Its information is current and versatile. But, certain important issues like research-funding and statistics received less than expected attention. Despite this flaw, I would still recommend this book to scientists. Its pros did exceed its cons by a mile.



2. This is a really great book. It is well written and seems easy to follow. IT was required for my Intro to Research class. It will be helpful as well in the development of my capstone/research project for graduaiton.



3. This book was good for me, give you the best about clinical research from A to Z, very simple, up to the point



4. I enjoyed the class and this book was pretty helpful, but probably not worth the price.



5. I am a declared fan of this book. I teach on how to do research to med students and this book is very straight forward and practical.
   I believe that this book is a must for physicians that want to do research and have no time to learn everything. It is designed for everyone to pose their research question, select the design (which I believe is the right way to do research)(first 6 chapters) and then read the chapters about the selected design. It has additional chapters about searching funds(seldom included in research books) and ethical issues. My favorite chapters are the first two for beginners with no research experience (research question), the fifth (hypothesis) and the sixth (sample size), and the questionnaire chapter. The questionnaire chapter is a masterpiece, it teaches about difficult subjects in a practical and very easy way for physicians to understand. I have let away most of my books about questionnaires aside with this chapter (for physicians, for research specialties you might go to other books). And in this new edition the data management chapter has included the use of software for data analysis.
   I hope the Spanish version of this 3rd edition will be available soon.