Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)

Book Description

This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes.

Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.

The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided. For many students and researchers learning to use these methods, this one book may be all they need to conduct and interpret multipredictor regression analyses.

The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992).

From the reviews:

"This book provides a unified introduction to the regression methods listed in the title...The methods are well illustrated by data drawn from medical studies...A real strength of this book is the careful discussion of issues common to all of the multipredictor methods covered." Journal of Biopharmaceutical Statistics, 2005

"This book is not just for biostatisticians. It is, in fact, a very good, and relatively nonmathematical, overview of multipredictor regression models. Although the examples are biologically oriented, they are generally easy to understand and follow...I heartily recommend the book" Technometrics, February 2006

"Overall, the text provides an overview of regression methods that is particularly strong in its breadth of coverage and emphasis on insight in place of mathematical detail. As intended, this well-unified approach should appeal to students who learn conceptually and verbally." Journal of the American Statistical Association, March 2006

Customer Reviews:

very good book, compact but comprehensive.......2007-05-12

This book covers a wide range of topics in Biostatistics, in a comprehensive, but not overwhelming way. In my opinion this book has the potential of being useful to a broad audience, from Statisticians to other professionals who do health related research.

Excellent book ..........2007-01-09

A very specific book, with a lot of details for a statistitian

Average customer rating:

Deceptive
An original approach. An excellent book on the subject.
Hey, I got an A in Biostats I
YES! I could speak and ask questions at journal club without looking like a fool.
Excellent Statistics Book

Intuitive Biostatistics
Harvey Motulsky
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Paperback

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Basic & Clinical Biostatistics (LANGE Basic Science)
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ASIN: 0195086074

Book Description

Designed to provide a nonmathematical introduction to biostatistics for medical and health science students, graduate students in the biological sciences, physicians, and researchers, this text explains statistical principles in non-technical language and focuses on explaining the proper scientific interpretation of statistical tests rather than on the mathematical logic of the tests themselves. Intuitive Biostatistics covers all the topics typically found in an introductory statistics text, but with the emphasis on confidence intervals rather than P values, making it easier for students to understand both. Additionally, it introduces a broad range of topics left out of most other introductory texts but used frequently in biomedical publications, including survival curves. multiple comparisons, sensitivity and specificity of lab tests, Bayesian thinking, lod scores, and logistic, proportional hazards and nonlinear regression. By emphasizing interpretation rather than calculation, this text provides a clear and virtually painless introduction to statistical principles for those students who will need to use statistics constantly in their work. In addition, its practical approach enables readers to understand the statistical results published in biological and medical journals.

Customer Reviews:

Deceptive.......2007-08-10

If you think you can learn Statistics intuitively and without mathematics or in otherwords the easy way, I have an intuitive Brain Surgery book for sale.

An original approach. An excellent book on the subject........2007-06-13

The majority of reviewers really liked this book. I can see why, I did too. The author uses a unique approach to teaching statistics that is focused on calculating and explaining Confidence Intervals (the minimum and maximum value you expect an outcome to be given a confidence level typically 95%) rather than P values (probability outcome is due to chance). He also uses common sense and clearly distinguishes between what is statistically significant and what is "significant." Thus, he translates well statistical mumbo jumbo into plain English. He tells you what you should care about and look for.

He shares with you all the statistical flaws that clinical studies may have including testing multiple hypothesis to come up with just a single statistically meaningful one, using large samples to prove something trivial, using small samples that raises uncertainty level, etc...

His section on Bayesian Logic is excellent. His table on what test or methodology to use given the shape of the data and objective you have is worth the price of the book alone. That's one of the clearest taxonomy of statistical methods I have seen anywhere.

Some knowledgeable reviewers have picked up a few errors the author made. I stumbled upon a couple while attempting to replicate the calculation of a few examples. I emailed the author and each time within an hour he either clarified the calculation or corrected the typo that was present in the book. Given his prompt answers, I can't ding him for the couple of typos I caught.

Although the author presents this book as an introductory one, I recommend the reader acquires a good foundation in basic statistics before studying this book. Forgotten Statistics would fit that bill. Indeed, `Intuitive Biostatistics' covers a huge amount of ground. It is far more than an introductory text. It covers material that is pretty advanced including nonparametric hypothesis tests, non linear regression, logistic regression, Bayesian analysis, etc... If it is the first time you come across that stuff you'd be well served having a solid stats foundation. Given that, this book has a lot to offer. I'll keep it as a great reference for years.

Hey, I got an A in Biostats I.......2007-01-04

I am not a high faltuin' math person, the calculus I went through in undergrad was a struggle and I remember very little. I am a chemist by training, currently seeking my PhD in Public Health while working full time. What that came down to was little to no time to doof around with a muddled textbook or an equally muddled professor or a non-English speaking Teacher's Assistant.

I have no intention of becoming a biostatistician or an epidemiologist, I am interested in policy.

So coming from that perspective, as a student, this book was an absolute God-send.

Not only did I get an A in the class, but I feel like I have a sturdy foundation for my future coursework and career. I will not be intimidated by numbers or jargon because Dr. Motulsky made it all as straightforward and clear as possible, and I recall even laughing a few times.

Overall, if you are in school, facing a biostatics class with extreme trepidation, buy this book as a supplement. Look up the topics in the index as you go and you will have more than the $40 worth of "eureka" moments.

YES! I could speak and ask questions at journal club without looking like a fool........2006-09-25

Helped me from looking a fool during residency. Thank you Harvey!

Excellent Statistics Book.......2006-03-13

Intuitive Biostatistics takes a confidence interval approach that should be required reading for all persons interested in statistics. His discussion of basic statistical concepts in the context of interpreting lab test results is clear and informative and introduces the reader to Bayesian concepts that are presented very simply.

Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine

Average customer rating:

Best guide for analysis
An excellent introductory text
clearest yet description this topic

Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis: Methods for Quantitative Synthesis in Medicine
Diana B. Petitti
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Hardcover

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Designing and Conducting Cost-Effectiveness Analyses in Medicine and Health Care (Jossey-Bass Health Care Series)
Methods for the Economic Evaluation of Health Care Programmes
Cost-Effectiveness in Health and Medicine
Statistical Analysis of Cost-Effectiveness Data (Statistics in Practice)
Decision Modelling for Health Economic Evaluation (Handbooks for Health Economic Evaluation)

ASIN: 0195133641

Book Description

Meta-analysis, decision analysis, and cost-effectiveness analysis are the cornerstones of evidence-based medicine. These related quantitative methods have become essential tools in the formulation of clinical and public policy based on the synthesis of evidence. All three methods are taught with increasing frequency in medical schools and schools of public health and in health policy courses at the undergraduate and graduate level. This book is a lucid introduction, and will serve the needs of students taking introductory courses that cover these topics. It will also be useful to clinicians and policymakers who need to understand the quantitative underpinnings of the methods in order to best apply the information that derives from them. The second edition of this popular book adds new material on cumulative meta-analysis as a method to explore heterogeneity. The coverage of cost-effectiveness analysis has been brought into close alignment with recommendations of the U.S. Public Health Panel on Cost-Effectiveness Analysis in Health and Medicine. Many of the examples have been replaced with more current examples, and all of the material has been updated to reflect recent advances in the methods and the emergence of consensus about some previously controversial issues. analysis. These three closely related methods have become even more important for synthesizing research since the first edition was published in 1994. And they have gained legitimacy as tools for guiding health policy.

Customer Reviews:

Best guide for analysis.......2006-12-20

There are several ways to do analysis of the health care industry but this book covers the big three. Cost Effectiveness is the most useful from a business standpoint. This book covers the math and theory behind each of these methods and gives strong arguments for how to write in each of them. As a health and pharmaceutical economist I found this book to be invaluable. It is written very clearly and helps sort through many of the issues especially meta analysis. If you are starting out in the health analyst field this is a must read and a book you will want to have handy at all times.

An excellent introductory text.......2002-02-05

Meta-analysis, as both an applied and theoretical science, continues to develop from its rather humble beginnings. Since most physicians lack a strong background in quantitative science, rigorous statistical approaches to clinical decision making have been slow to gain widespread support. Despite its limitations, meta-analysis is proving to be an important vehicle for making sense of the increasingly overwhelming amount of published data in the biomedical sciences. Petitti's book goes a long way in demystifying meta-analysis for the rank and file and also serves as an excellent introduction to the field for the more statistically literate.

Most of my own work is in meta-analysis and I bought the book exclusively for this content and not information on decision analysis and cost-effectiveness analysis. I do not mean to minimize the importance of the latter but rather point out my own narrow interest in the Petitti text.

The book is well written and concise. Petitti "cuts to the chase" explaining the theory underlying meta-analytic methods and provides many useful examples from the medical literature. The text is easy to follow, understandable and well balanced. A thorough reading should leave the reader well prepared for further exploration of applied meta-analysis as well as capable of articulating its strengths, weaknesses and future direction.

Overall, Petitti's text is an excellent place to start for those interested in learning the fundamentals of "research synthesis". The book is also an extremely handy references for the more experienced practitioner. I highly recommend it.

clearest yet description this topic.......1997-07-08

In a forest of mirky and arcane descriptions of a field that has come to dominate medical research and policy making, this book stands out for its clarity. Dr. Petitti speaks a language that normal people can understand. She avoids jargon and frequently uses quantitative examples that make it easy to plug in your own problems and directly apply her lessons to your tasks. This is easily the best book in print on this topic

History: Fiction or Science? (Chronology, No. 1)

Average customer rating:

Calculations are only as good as your numbers
Pants on fire?
Accepted History & Chronology Must Be Changed.
Very Interesting
History as Science Fiction

History: Fiction or Science? (Chronology, No. 1)
Anatoly Fomenko
Manufacturer: Mithec
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Binding: Paperback

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Similar Items:

History: Fiction or Science? Chronology 2 (Chronology)
History: Fiction or Science? Astronomical methods as applied to chronology. Ptolemy's Almagest. Chronology III
Discovering the Mysteries of Ancient America: Lost History And Legends, Unearthed And Explored
Before the Pharaohs: Egypt's Mysterious Prehistory
They Cast No Shadows: A Collection of Essays on the Illuminati, Revisionist History, and Suppressed Technologies

ASIN: 2913621058

Book Description

Recorded history is a finely-woven magic fabric of intricate lies about events predating the sixteenth century. There is not a single piece of evidence that can be reliably and independently traced back earlier than the eleventh century. This book details events that are substantiated by hard facts and logic, and validated by new astronomical research and statistical analysis of ancient sources.

Customer Reviews:

Calculations are only as good as your numbers.......2007-08-03

Yes, we can all agree that mainstream history is nearly 100% BS due to politics, economics, ego, problems with dating techniques, and various conspiracies. Agreed. But, I've been researching the distinct possibility that human history (in terms of civilizations) are much more ancient than we've been told, so coming across this book was very interesting to me. I wondered how Fomenko could be wrong (if at all) because he is very persuasive in his presentations. Then it dawned on me. If at previous times in prehistory, due to the various catastrophies that are well documented (comets, asteroids, planetary disruptions, plasma discharge, pole reversals, etc) the Earth was in a different position in relation to the sun, different tilt on its axis, different orbit, different rotation (in terms of velocity and DIRECTION), and the continents were in different positions, then would this not cause the ancients to see the sky (constellations) differently? In other words, is Fomenko making erronious assumptions about the physics of the Earth in pre-history, which then corrupt his data with regards to dating the relevant astrology? The last event to seriously disrupt our planet occured roughly 3500 years ago, according to other good researchers, so is it possible Fomenko has been confused by this? The vastly different physics of our planet in the not so distant past may explain this confusion, which is not to say the "mainstream" version of history is correct; on the contrary. I am not an expert in these fields, but wanted to see if this idea could spark discussion.

Pants on fire?.......2007-07-19

Will people ever read before spamming? Yes, Jesuits could not rewrite world history alone, they had help. Anyway, Dr Prof Acad A.Fomenko does not point to jesuits as the driving force of world wide history manipulation in published volumes 1,2,3;, actually he barely mentions the poor devils. Check it with 'Search inside' feature, please. China is rarely mentioned either, in fact, Dr Fomenko is completely eurocentric. Right, his theory contradicts all mainstream schools of history, because in their actual state they are all built on blatantly erroneus chronology. You don't need a mysterious cabal (conspiracy) to falsify history, the falsification is its modus operandi. It is inherent to history(ians) to falsify (distort) events, as it is inherent to humans to boast as it is inherent to power (authority) to legimize itself by referrring to glorious past made to its own order. Dr Prof Fomenko and team have identified scores of instances of such manipulation in Russian, European, etc.. history, and delivered valid statistical proof thereof. His own 'reconstruction' is completely another story. Forget c14 as a valid method of dating. W.Libby has initially discovered a brilliant method of INDEPENDENT dating. Too bad, c14 method has become a joke after a forced marrige with dendrochronology with consensual chronological scale inbuilt. Radiocarbon method can't stand blind tests, but is so very productive as a rubberstamp.

Accepted History & Chronology Must Be Changed. .......2007-04-09

There is no doubt that history as most know it is a sham, & institution's version of History both University & Church is fradulent & inaccurate. Everything was established with an agenda, The real "Dark Ages" are now when we have access to incredible amounts of information past authorities & more important 'common folk' didn't have but our institutions & educators are slow to evolve because of what has ignorantly & arrogantly been taught for too long. This is on many subjects not just Chronology.

For anyone to question "Why would a Mathematician have anything credible to say of History?" The answer is from Dr. Fomenko's preface in the book: "It would be worthwhile to remind the reader that in the XVI-XVII century Chronology was considered to be a subdivision of Mathematics." These volumes could possibly be some of the most important works to date & should be read by everyone with an interest in History, especially professors & educators who have a duty to the public. I have read both books & must say that 'Chronology 1' has some very eye opening & revolutionary information. Even if these volumes are part true the implications are profound & opens the doors to further investigations & questions which must be done. I speak several different lanquages & must say the logic Dr. Fomenko uses with "inflection" of words & words being read from left to right in one region & right to left in another then written backwards, the removal of vowels & get down to basics of words, or different cities & locations having the same name etc. is correct. Vowel usage has always been optional & varied, actually complicating linquistics & study. The first thing one has to understand is that words never had a fixed spelling in history like we do now, the spelling of words was mutable & regional, as well as names & titles of people were vast, varied & changed, NOTHING WAS FIXED or understood linear. Matters of Life & Death as well as financial profiteering yesterday & today were & are made with ignorant, illogical & conspiratorial views of history & reality, it's time people get closer to the Truth & society collectively grow up.

Very Interesting.......2007-03-07

It is a good proposal and I believe it will mature into something even better in the future. I think it deserves to be read.

History as Science Fiction.......2007-01-10

Anatoly Fomenko has written a very intriguing book, full of pictures, charts, and computer 'proof' of his thesis: backwards of AD900 we don't really know what happened or when. Between AD900 and AD1600 there is more certainty, but there is still a lot of fuzzy ground, and things don't get reliable until we get past the 1600's where the printing press made it very difficult for the perpetrators of this timeline manipulation to change anything that had been committed to print. The Dark Ages did not happen. Books were burned for a reason. One organization has doubled the actual length of its existence by expanding the real chronology. Read why.

I had always wondered why Christ died about AD33 and yet men waited until the 11th century to form the Knights Templar, the Cathars, etc and go after the Holy Land by force. Why the 1000 year gap? Turns out there wasn't more than a 10-12 year gap and he proves it using astronomy. This also implies that the planet is not as old as we have been told, and current Christian and other creationist scientists are already championing that idea without being aware of Fomenko's book. The two groups, creationist scientists and the Russian mathematical analysts corroborate each other. Fascinating.

Of course, all this flies in the face of what we have been told traditionally is the 'proper' chronology of western civilization, and most readers will experience 'cognitive dissonance' in reading this book. It means that our history going backwards from AD1600 becomes progressively more incorrect and unreliable until it cannot be trusted at all... in the space of 700-800 years.

Naturally, the curious, open-minded reader will want to know WHO did this, WHY, and did any of the events we think of as really ancient ever happen?
Dr. Fomenko is a respected scientist/mathematician at Moscow State University who has already answered these questions to the satisfaction of his initially skeptical colleagues. Most of them are now believers, a few still refuse to believe (the usual diehards), and of course the western press has ignored Fomenko's work -- for obvious reasons when you read the book. The ones who perpetrated this chronology ruse have a lot to answer for. They are still with us. That's why this book is a well-kept secret.

I gave the book a 4-star rating because I was unable to check out some of his claims; those I checked were as he said. But if even 1/3 of his claims are true, this punches a big hole in what we think is our history, the meaning of western civilization, our educational process (for repeating the ruse as gospel), and the trustworthiness of the organization that perpetrated this ruse, well-intentioned or not.

This book relates to current research into a Young Earth paradigm, to John Keel's discoveries about our planet, and Fr Malachi Martin's insights (in his now out-of-print books). We are indeed sheep who are manipulated and kept ignorant -- for a reason. While knowing what these men have to say may be the "booby prize" (as in: 'what can you do with this knowledge?'), it will provide interesting reading. Didn't someone say: "...and the Truth will set you free."?? For you to judge if this book contains the truth.

Methods for Meta-Analysis in Medical Research (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section)

Average customer rating:

A personal review

Methods for Meta-Analysis in Medical Research (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section)
Alexander J Sutton , Keith R. Abrams , David R Jones , Trevor A. Sheldon , and Fujian Song
Manufacturer: Wiley
ProductGroup: Book
Binding: Hardcover

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Meta-Analysis in Medical Research

ASIN: 0471490660

Book Description

With meta-analysis methods playing a crucial role in health research in recent years, this important and clearly-written book provides a much-needed survey of the field.
Meta-analysis provides a framework for combining the results of several clinical trials and drawing inferences about the effectiveness of medical treatments. The move towards evidence-based health care and practice is underpinned by the use of meta-analysis. This book:
* Provides a thorough criticism and an up-to-date survey of meta-analysis methods
* Emphasises the practical approach, and illustrates the methods by numerous examples
* Describes the use of Bayesian methods in meta-analysis
* Includes discussion of appropriate software for each analysis
* Includes numerous references to more advanced treatment of specialist topics
* Refers to software code used in the examples available on the authors' Web site
Practising statisticians, statistically-minded clinicians and health research professionals will benefit greatly from the clear presentation and numerous examples. Medical researchers will grasp the basic principles of meta-analysis, and learn how to apply the various methods.

Customer Reviews:

A personal review.......2007-05-13

This book has two big advantages: In my personal view it is written well for someone who has at least some basic statistical understanding and for me there are quite enough practical examples and illustrations of the chosen methodology. The second advantage in my opinion is its wealth of references at the end of every chapter.

Overall it covers almost all of the relevant methods and thus can be considered as a reference for the experienced statistician and as an easily comprehensible introduction to the beginner.

I think to recommend this book warmly to any reader who does not need the theoretical foundations of probability in meta-analysis.

Applied Survival Analysis: Regression Modeling of Time to Event Data

Average customer rating:

A Good Read, but Read it Carefully!
nice introduction
Great conceptual Introduction to Cox regression analysis
A clear, simple introduction to survival models
Excellent Nontechnical Coverage of Survival Analysis

Applied Survival Analysis: Regression Modeling of Time to Event Data
David W. Hosmer Jr. , and Stanley Lemeshow
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

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Applied logistic regression (Wiley Series in probability and statistics)
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Modeling Survival Data: Extending the Cox Model (Statistics for Biology and Health)

Accessories:

Solutions Manual to Accompany Applied Survival Analysis: Regression Modeling of Time to Event Data

ASIN: 0471154105

Book Description

A Practical, Up-To-Date Guide To Modern Methods In The Analysis Of Time To Event Data.
The rapid proliferation of powerful and affordable statistical software packages over the past decade has inspired the development of an array of valuable new methods for analyzing survival time data. Yet there continues to be a paucity of statistical modeling guides geared to the concerns of health-related researchers who study time to event data. This book helps bridge this important gap in the literature.
Applied Survival Analysis is a comprehensive introduction to regression modeling for time to event data used in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies. While the authors emphasize the proportional hazards model, descriptive methods and parametric models are also considered in some detail. Key topics covered in depth include:
* Variable selection.
* Identification of the scale of continuous covariates.
* The role of interactions in the model.
* Interpretation of a fitted model.
* Assessment of fit and model assumptions.
* Regression diagnostics.
* Recurrent event models, frailty models, and additive models.
* Commercially available statistical software and getting the most out of it.
Applied Survival Analysis is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health-related fields.

Customer Reviews:

A Good Read, but Read it Carefully!.......2005-05-05

The authors provide a really nice, non-technical survey of the landscape for Cox Proportional Hazards models. A nice aspect of their treatment is the care they take to reference all highly technical texts and journal articles. For example, if you'd like to find out more about goodness-of-fit tests for survival models, the authors provide ample references to the Counting Process Theory of Martingale Residuals.

The first chapter discusses the basic characteristics of survival data, including the notion of censoring (in all of its various forms). Examples of the principle types of censoring are included. The chapter also includes introductory material on the general survival model, including a nice description of the log likelihood function. Curiously, the rigorous definition of the hazard function has been omitted, probably to avoid intimidating readers who are not familiar with formal limits.

Chapter 2 continues to build up the general survival model and introduces the relationship between the survivor function and the cumulative hazard. Pointwise estimators for the survivor function are discussed, including the Kaplan-Meier estimator along with the various variance estimators. Test statistics for comparing two survival populations are introduced, including the Log-Rank and General Wilcoxon statistics. The reader is encouraged to read the counting process treatments of these statistics to see why they produced defensible hypothesis tests.

Chapter 3 is devoted to the Cox Model and Cox's partial likelihood function. Tests for significance of the coefficients are introduced, included the Wald test, log likelihood ratio test and the score test. These are used heavily in the later chapters as the basis of a model-building methodology.

Chapter 4 is a very short, but nicely written chapter explaining how to interpret the values of each regression coefficent. It also describes covariate-adjustment techniques for model diagnostics.

Chapter 5 is just a wonderful chapter which outlines classical model building techniques. This is a great chapter for anyone who has ever been thrown a ton of data (with a bushel of possible covariates) and asked to "fit a model to this stuff".
Readers who have done a lot of purposeful fitting of linear regression models won't find the basic techniques new, but use of survival specific residuals and selection criterion will probably be an eye-opener. The section on assessing the functional form for continuous covariates is also nicely written.
However, the section on Best Subsets Selection was a little too "cook-booky" for my taste.

Chapter 6 is another very nice chapter on goodness-of-fit. It discusses analysis of the various residuals and their use for analysis outliers, testing proportional hazards assumptions and overall Goodness-of-Fit.

Chapter 7 discusses the standard extensions of the Cox model, including stratification and time-varying covariates. Chapter 8 discusses parametric survival models, and is a good introduction to the SAS procedure LIFEREG. The generalization of the Cox model to recurring event data (also know as Aalen's multiplicative intensity model) can be found in Chapter 9.

My only complaint is that each chapter was designed to be read in one sitting. Individual ideas, topics and formulas can be buried in a seemingly unbroken chain of paragraphs. The lack of sub-sub section titles,etc, makes using the text as is somewhat cumbersome to use as a desk reference. I've gotten around this limitation by marking key concepts, etc., in the margin in order to give a "quick search" capability enhancement to the index.

nice introduction.......2003-04-03

This book provides a good, clear, concise explanation of Cox's proportional hazards models. For someone seeking a non-mathematical description this is a great guide. The original datasets from the text examples can even be downloaded and you can go through the same process yourself. Because of some mistakes in the text, I would recomend looking at other sources as well.

Great conceptual Introduction to Cox regression analysis.......2000-02-09

I enjoyed the authors' book on logistic regression analysis in 1989, and this book is just as good, or better, with many extremely practical suggestions on building regression models for survival data. Happily, the authors summarize, compare, and contrast several major texts on survival analysis which have appeared in the past 10 years. For example, they discuss different names used by different authors for score residuals. They present a helpful appendix on the counting process approach to survival analysis, which will make more advanced texts accessible to students; thus, anyone who wants to use survival analysis, at any level, should consult this book, even if he has already studied books by Miller, Lee, Collett, Fleming-Harington,Andersen, et al, etc. An unfortunate drawback to this book is that the first printing contains many careless errors, some of which may affect student learning: for example, the definition of a survival function is misstated. I recommend that you insist on the second or third printing when buying this book, and you will be quite satisfied.

A clear, simple introduction to survival models.......2000-01-07

Hosmer and Lemeshow have given us a clear, nontechnical introduction to using survival models. The book strikes a good balance between covering the basics and addressing the most recent, state-of-the-art techniques, including repeated events, frailty models, and others. They also do a good job of addressing practical issues, including estimation details and available software. While most of the examples are drawn from medicine and biostatistics, this book could also serve as a useful starting point for social and behavioral scientists interesting in learning the fundamentals of these models, as well as a useful reference for applied researchers.

Excellent Nontechnical Coverage of Survival Analysis.......1999-12-07

Applied Survival Analysis is an excellent book for someone seeking a non-mathematicial explanation of survival analysis. The book covers the motivation behind the development of survival analysis, estimation of survival curves, the Cox proportionial hazards, and some parametric models. The book also covers the major methods used in variable selection, model building, and diagnostics. Someone with an undergraduate background in statistics and econometrics will understand the book. The book relies on text to discuss the methods and uses mathematical formulas only when absolutely necessary. Numerous examples are used to highlight what the text covers. The math that is used is easily understandable. This book is ideal for someone who needs to learn the tools of survival analysis but not how they were derived.

Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity)

Average customer rating:

Annie Wu -- Book #1
The Emergence of Convergence

Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity)
John H. Miller , and Scott E. Page
Manufacturer: Princeton University Press
ProductGroup: Book
Binding: Paperback

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Similar Items:

Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton Studies in Complexity)
The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies
Social Emergence: Societies As Complex Systems
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
Evolutionary Dynamics: Exploring the Equations of Life

ASIN: 0691127026

Book Description

This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents.

John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

Customer Reviews:

Annie Wu -- Book #1.......2007-08-10

I am a purchasing agent who buys books for my faculty, and as far as I know, this faculty member is very impressed with this particular book.

The Emergence of Convergence .......2007-08-04

At the time of writing this review, this book isn't searchable through Amazon, that's too bad because if you're reading the reviews wondering if it's worth buying, just browsing through any page from the intro or appendix B would clearly resolve any remnant hesitation. This book is a must have for anyone even remotely interested in complex adaptive systems. Scott Page and John Miller dress the landscape and state of the art of computational social science, the issues are motivated from the ground up and the existing approaches to resolve them explicitly detailed, yet using clear and jargon free language. For example, descriptions of the many concepts repeatedly used in the scientific method (of CAS et al) such as ergodicity or optimization theory are refreshing and insightful, simply stuff you don't get from textbooks, but rather that one would learn over years of experience doing.

In summary, the authors are handing us an expert summary of literature and developments of a complex field in a concise, fun and delightful read, it would be a shame to miss it.

Statistical Methods for Health Care Research

Average customer rating:

Statistics
fooled me!!
Statistical Methods for Health Care Research
Great book
A very user friendly approach to understanding statistics.

Statistical Methods for Health Care Research
Barbara Hazard Munro
Manufacturer: Lippincott Williams & Wilkins
ProductGroup: Book
Binding: Paperback

Health Care Delivery | Administration & Policy | Medicine | Subjects | Books

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Similar Items:

Nursing Research: Generating and Assessing Evidence for Nursing Practice (Nursing Research (Polit))
Qualitative Research in Nursing: Advancing the Humanistic Imperative (Nursing Research)
Integrating Behavioral Social Sciences with Public Health
Health Care Management: Organization Design and Behavior
The Practice of Nursing Research: Conduct, Critique, & Utilization

ASIN: 0781748402

Book Description

Focusing on the statistical methods most frequently used in the health care literature and featuring numerous charts, graphs, and up-to-date examples from the literature, this text provides a thorough foundation for the statistics portion of nursing and all health care research courses. All Fifth Edition chapters include new examples and new computer printouts using the latest software, SPSS for Windows, Version 12. New material on regression diagnostics has been added. Includes a complete set of powerpoint slides on the Connection website

Customer Reviews:

Statistics.......2007-03-26

This book is written for PhD level students. It is not an easy read, even for someone who has had statistics before. I would not recommend this text to anyone except experienced statistics students.

fooled me!!.......2007-01-18

I believed this was the text book by the exact same name instead it turned out to be the study guide for the text book. I do not have the text book so this book is useless for me. I think I am done doing business with Amazon!!

Statistical Methods for Health Care Research.......2003-06-01

A very well-written and helpful statistics book. It was required reading for a course in Quantitative Nursing Research last semester. Overall, the concepts such as t-tests, correlation and regression were explained in relatively simple terms. Examples with answers were found at the end of each chapter and the book came with a data disk. This was the most user-friendly statistics book that I have used so far!

Great book.......2000-03-14

I had a chance to review this book. I think the authors can make us much better understand, particularly one who is about to learn the concept of statistics. You can apply this book with the SPSS program in order to interpret the results. Anyway, I still like the calculation parts which are removed in this edition (3rd) compared with the last one. I think they can help someone, who is very interested in statistics, to understand better before go ahead to use the computer. It's a great book for the beginner.

A very user friendly approach to understanding statistics........1999-01-04

An excellent beginning reference book for anyone in need of understanding or interpreting univariate and multivariate statistics. Geared toward health care research, with many examples. A data set is provided with the book for students to use with different analyses. Reading audience is upper division undergraduate or graduate student.

Designing Clinical Research: An Epidemiologic Approach

Average customer rating:

Very Good
Needed for Class
IT HAS A REFINED ANALYTICAL APPROACH
excessively convenience-oriented book
THIS IS A MUST HAVE

Designing Clinical Research: An Epidemiologic Approach
Stephen B Hulley , Steven R Cummings , Warren S Browner , Deborah G Grady , and Norman Hearst
Manufacturer: Lippincott Williams & Wilkins
ProductGroup: Book
Binding: Paperback

Public Health | Administration & Policy | Medicine | Subjects | Books

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Basic & Clinical Biostatistics (LANGE Basic Science)
Exploring Research (6th Edition)
Clinical Epidemiology: The Essentials
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Epidemiology, Updated Edition: With STUDENT CONSULT Online Access

ASIN: 0781722187

Book Description

Designing Clinical Research has set the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy to read, uncomplicated presentation. Updated chapters incorporate current research methodology, with an updated syllabus for conducting a clinical research workshop. A Brandon-Hill recommended title.

Customer Reviews:

Very Good .......2007-03-23

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

Needed for Class.......2006-07-01

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.

IT HAS A REFINED ANALYTICAL APPROACH.......2003-01-30

"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.

excessively convenience-oriented book.......2002-05-25

On the whole this book is an excellent work.

But there is some possibility of fostering illusions in many readers' mind that they actually have great power of research in spite of not having good understanding on basic principles such as statistics.

It is not sufficiently equipped for graduate student or researcher above the level.

THIS IS A MUST HAVE.......2001-07-07

This is an amazing textbook that is a must have for all healthcare workers or anyone involved or wanting to be involved in clinical research. The test is organized and extremely well written. I use it to teach clinical research design to my students, residents, and fellows. Hats off to Hulley et al on a job well done. It was worth the 13 year wait for the 2nd edition.

How to Report Statistics in Medicine: Annotated Guidelines for Authors, Editors, and Reviewers (Medical Writing and Communication) (Medical Writing and ... (Medical Writing and Communication)

Average customer rating:

Guidelines valuable to everybody
Fantastic Reference for Preparing for Peer-Reviewed Manuscript Submissions
Incredibly useful
Good for beginners
Understanding biostatistics without becoming a statistican

How to Report Statistics in Medicine: Annotated Guidelines for Authors, Editors, and Reviewers (Medical Writing and Communication) (Medical Writing and ... (Medical Writing and Communication)
Thomas A. Lang , and Michelle Secic
Manufacturer: American College of Physicians
ProductGroup: Book
Binding: Paperback

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AMA Manual of Style: A Guide for Authors and Editors
Guidebook to Better Medical Writing
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Clinician's Guide to Medical Writing

ASIN: 1930513690
Release Date: 2006-12-30

Product Description

How to Report Statistics in Medicine presents a comprehensive and comprehensible set of guidelines for reporting the statistical analyses and research designs and activities commonly used in biomedical research. Containing elements of a reference book, a style manual, a dictionary, an encyclopedia, and a text book, it is the standard guide in the fields of medical writing, scientific publications, and evidence-based medicine throughout the world. Features: Specific, detailed guidelines for reporting and interpreting statistics and research designs and activities in biomedical science. Sample presentations that guide you in reporting statistics correctly and completely. Coverage of current and emerging topics in statistics and trial design. Written by a senior medical writer and a senior biostatistician, the text is both clear and accurate, and the information is complete and pragmatic. Designed for anyone who needs to interpret or report statistics in medicine.

Customer Reviews:

Guidelines valuable to everybody.......2007-07-27

I found this book unexpectedly useful, complete and easy to read. It contains the kind of statistical knowledge that medical people do like to see. It is not another textbook that reviews medical statistics. However it provides the clues to understand and classify all these statistical jargon and processes that cause difficulties to eveybody that loves to handle statistics himself.I fully recommend it

Fantastic Reference for Preparing for Peer-Reviewed Manuscript Submissions.......2007-06-27

This is the best reference book I have found on the topic of how to present data for manuscripts to be submitted to peer-reviewed journals. It is easy to use, super easy to understand, and covers all elements of the manuscript preparation process as far as data representation is concerned. I highly recommend it for anyone looking for a book on the subject. It includes many examples of data tables, figures, and even examples of how to write up titles and data descriptions.

Incredibly useful.......2007-02-11

The material is presented in a way that will help medical writers understand clinical trials more fully, and answer questions that come while writing.

Good for beginners .......2005-09-30

I am glad to read this book before I prepared for my statistical clinical studies. This book could give you basic ideas, but you need to discuss with your collegues or use more advanced books to improve further.

Understanding biostatistics without becoming a statistican.......2000-07-20

As a medical writer and editor at The Cleveland Clinic, Thomas A. Lang found that the lack of clear understanding of statistics by non-statisticians affected the clarity of their writing. Physicians had the same problem while writing up their research papers for publication. Lang perceived a need among medical and science writers to understand just enough of biostatistics to make them better writers and editors without becoming statisticians themselves. He devised workshops that were conducted by the American Medical Writers Association which were enormously successful. The logical next step was to write this book based on the valuable teaching experience and feedback he got at those courses. In other words, this is a book that wasn't written in a vacuum but is the result of a perceived need, and the author's experience in meeting that need. Co-author Michelle Secic has also contributed with her expertise, making it a valuable book for people in this field.

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