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 | | Introductory Applied Biostatistics (with CD-ROM) by Sr., Ralph D'Agostino, Lisa Sullivan, Alexa Beiser ISBN-10: 9780534423995 ISBN-10: 0-534-42399-X ISBN-13: 9780534423995 ISBN-13: 978-0-534-42399-5 Hardcover 2005-03-16 Brooks Cole Find Lowest Price |
Editorials | ||
Product Description INTRODUCTORY APPLIED BIOSTATISTICS (WITH CD-ROM) explores statistical applications in the medical and public health fields. Examples drawn directly from the authors' clinical experiences with applied biostatistics make this text both practical and applicable. You'll master application techniques by hand before moving on to computer applications, with SAS programming code and output for each technique covered in every chapter. For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results. This book is a must-have for every student preparing for a statistical career in a healthcare field! | ||
Reviews | ||
Introductory Applied Biostatistics This is the "required" textbook for my biostatistics course and after reading most of the chapters, I can see why. Being someone with a weak mathematical background, I find this book to be extremely clear and helpful, taking a step by step approach which is very easy to follow. All the examples are relevant to what is being explained, all the formulas are numbered so when they refer to them later in the text it's easy to find them, and at the end of each chapter is a table summarizing all the formulas and when to use them. As for the answers to the problems, there is a Students Solution Manual available, although I don't see the need for it because as it has been mentioned before, there are plenty of practice examples within the text, and I also have an instructor that can help me go through the problems if I don't understand, instead of simply giving me the answer. | ||
Introductory Apploied Biostatistics w CD ROM Found the information to be well organized. Good examples of testing, clear statements of analysis process. | ||
I know less than when I started! I have found this text book to be one of the most confusing I have ever read. I have trouble understanding the formulas and correlating them to the questions in the back of the chapters. And it is virtually impossible to use a reference book either. There is a lot of text that just runs together. | ||
Introductory Applied Biostatistics This is a great textbook for an introduction to biostatistics. My "required" textbook for my Introduction to Biostatistical Methods was way to technical for me to understand. I got this book to translate and really learn the basics (I have little mathmatics background). Its geared to those who may not have had any statistics backgrounds and easy to read. | ||
great introductory book covering all the key topics In contrast to the first reviewer I loved this book! It should be pointed that I am reviewing this first official edition in hard cover with a CD-ROM while the first reviewer reviewed a preliminary edition in paperback with no CD and published in 2005 whereas this text has a 2006 copyright date. The authors are all statistics professors at Boston University with Ralph D'Agostino Sr. the most well-known. They have a great deal of experience as teachers researchers and consultants and it shows in the material and the clarity of presentation. Also to their credit, they provide numerous worked out examples in the text and plenty of exericises at the end of the chapters that can be given as homework problems. The other reviewer complained about not having any answers given in the back of the book. I question how valuable that would be. The in-text exercises and the clear exposition in the text , along with an instructor, should be enough for the students to gain enough confidence to try the homework problems with some confidence that they are doing them right! Also the instructor should have a solutions manual to work from or should put one together to go over the homework in class and/or in tutorial sections. Sometime students can waste a lot of time trying to force their solution to match the answer in the back of the book. What if there is a error or typo in the book's answer? I like the way the authors present the material and the fact that they illustrate the methodology with real examples and SAS software. Many of the analyses are done using the Framingham Heart Study data which is a well designed cohort study with thus far a long 50 year follow-up on the surviving original cohorts. We benefit from the authors' intimate knowledge of this data snd their ability to illustrate a variety of biostatistical methods using it. There is also an interesting follow-up study that was conducted with the offspring of the original Framington cohorts that is discussed in the book. The book starts with a motivating chapter. I did a similar thing in my introductory book for health science majors. Students in the health sciences are not very interested in math and may have a preconceived notion that statistics is boring mathematics and not relevant to their work. These ideas are very much off base and a good introductory chapter can dispell these notions. The next three chapters are standard to almost any first statistics course starting with ways to summarize data for description. This includes a section on statistical computing snd an introduction to the Framingham study and its data. Next an introductory chapter on probability is given that includes the basics and some important combinatorial ideas needed to understand the binomial distribution. Then the binomial and normal distributions are presented. This chapter and all subsequent chapters have a section on statistical computing using SAS. Appendix A provides the basic components of SAS that are needed to run analyses in SAS along with sample code and sample output. Next Chapter 4, as part of a logical progression, covers sampling distributions and the central limit theorem. Chapter 5 covers inference for a single sample mean and includes discussion of power and precision in the important practical problem of deciding how many subjects are needed to draw proper inferences from the trial. This deserves mention because many elementary statistics books avoid this topic and yet it is always one of the first questions a statistician is faced with when he is designing a clinical trial. Chapter 6 does essentially the same thing as 5 but for two sample problems where the difference of two means is often the key parameter. In the two sample problem there is the added complication of whether or not the two population variances are equal and/or the two sample sizes are equal. Methods are available for all of these situations. Also matched pair designs involve two correlated populations of equal size and can often improve precision over designs that use independent populations to compute the mean difference. Such analyses often come up in clinical trials when baseline and final values are compared for the same subject and for pre-intervention and post-intervention tests in educational trianing studies. Again power and precision the SAS procedures and the analysis of the Framingham Heart Study are given. The remaining chapters are Categorical Data (Chapter 7) Comparing risks in two populations (Chapter 8), Analysis of Variance (Chapter 9), Correlation and Regression (Chapter 10), Logistic Regression (Chapter 11), Nonparametric Tests (Chapter 12), and Introduction to Survival Analysis (Chapter 13). These are important chapters commonly included in introductory biostatistics texts but chapters such as 8, 10 and 12 are often not included in a general introductory statistics course. In addition to Appendix A on SAS, Appendix B provides the traditional statistical tables but also shows why the are no longer really necessary since all these table entries can be generated using software. In this case the authors demonstrate it with SAS. And finally, Appendix C provides additional information and data documentation on the Framingham Heart Study. This text would make a great course text for medical students and health science majors and could even be used as a first biostatistics course for either masters or PhD level statistics students who are interested in biostatistics. It also makes a good reference book for statisticians and biostatisticians. | ||