Buy An Introduction to Medical Statistics (Oxford Medical Publications)

An Introduction to Medical Statistics (Oxford Medical Publications) by Oxford University Press, USA




Now in its Third Edition, An Introduction to Medical Statistics continues to be and invaluable textbook for medical students, doctors, medical researchers, nurses, members of professionals allied to medicine as well as those concerned with medical data. The material covered includes all the statistical work that would be required for a course in medicine and for the examinations of most of the Royal Colleges. It includes the design of clinical trials and epidemiological studies, data collection, summarizing and presenting data, probability, standard error, confidence intervals and significance tests, techniques of data analysis including multifactorial methods and the choice of statistical method, problems of medical measurement and diagnosis, vital statistics, and calculation of sample size. The new edition describes the design and analysis of medical research studies in a clear and user friendly manner. The third edition includes new topics such as consent in clinical trials, design and analysis of cluster-randomized trials, ecological studies, conditional probability, repeated testing, random effects models, intraclass correlation and conditional odds ratios. Material which is encountered only at the postgraduate level has been indicated clearly in the text to facilitate ease or use. The book is firmly grounded in medical data, particularly in medical research, and includes real illustrative examples. There are 100 multiple choice questions and 17 long questions involving calculations to which fully explained solutions are provided. A new companion volume, Statisitical questions in evidence based medicine (Bland & Peacock, 2000) refers directly to this new edition. This new book of questions and answers includes no calculations and is complementary to the exercises given here.Read more An Introduction to Medical Statistics (Oxford Medical Publications)

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Presenting Medical Statistics from Proposal to Publication: A Step-by-step Guide (Oxford Medical Publications)

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As many medical and healthcare researchers have a love-hate relationship with statistics, this practical reference book may make all the difference. It takes examples, mainly from the authors' own research, to explain how to make sense of statistics, turn statistical computer results into coherent information, and help decide which pieces of information to report and how to present them. Presenting Medical Statistics includes a wide range of statistical analyses, and all the statistical methods are illustrated using real data. Labelled figures show the Stata and SPSS commands needed to obtain the analyses, with indications of which information should be extracted from the output for reporting. The relevant results are then presented as for a report or journal article, to illustrate the principles of good presentation. The reader is taken through the various stages of the research process, from the initial research proposal, ethical approval and data analysis, to reporting on and publishing the findings. There are even extensive references for those who wish to find out more about the statistical methods. This is a must for anyone working with statistics in the medical profession.

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This book deals with infectious diseases -- viral, bacterial, protozoan and helminth -- in terms of the dynamics of their interaction with host populations. The book combines mathematical models with extensive use of epidemiological and other data. This analytic framework is highly useful for the evaluation of public health strategies aimed at controlling or eradicating particular infections. Such a framework is increasingly important in light of the widespread concern for primary health care programs aimed at such diseases as measles, malaria, river blindness, sleeping sickness, and schistosomiasis, and the advent of AIDS/HIV and other emerging viruses. Throughout the book, the mathematics is used as a tool for thinking clearly about fundamental and applied problems having to do with infectious diseases. The book is divided into two parts, one dealing with microparasites (viruses, bacteria and protozoans) and the other with macroparasites (helminths and parasitic arthropods). Each part begins with simple models, developed in a biologically intuitive way, and then goes on to develop more complicated and realistic models as tools for public health planning. The book synthesizes previous work in this rapidly growing field (much of which is scattered between the ecological and the medical literature) with a good deal of new material.

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This book presents a logical system of critical appraisal, to allow readers to evaluate studies and to carry out their own studies more effectively. This system emphasizes the central importance of cause and effect relationships. Its great strength is that it is applicable to a wide range of issues, and both to intervention trials and observational studies.

This system unifies the often different approaches used in epidemiology, health services research, clinical trials, and evidence-based medicine, starting from a logical consideration of cause and effect. The author's approach to the issues of study design, selection of subjects, bias, confounding, and the place of statistical methods has been praised for its clarity and interest. Systematic reviews, meta-analysis, and the applications of this logic to evidence-based medicine, knowledge-based health care, and health practice and policy are discussed. Current and often controversial examples are used, including screening for prostate cancer, publication bias in psychiatry, public health issues in developing countries, and conflicts between observational studies and randomized trials. Statistical issues are explained clearly without complex mathematics, and the most useful methods are summarized in the appendix.

The final chapters give six applications of the critical appraisal of major studies; randomized trials of medical treatment and prevention, a prospective and a retrospective cohort study, a small matched case-control study, and a large case-control study. In these chapters, sections of the original papers are reproduced and the original studies places in context by a summary of current developments.

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To practice evidence-based medicine, doctors need to understand how research is conducted and be able to critically appraise research evidence. A sound understanding of medical statistics is essential for the correct evaluation of medical research and the appropriate implementation of findings in clinical practice.
Written in an easily accessible style, the Oxford Handbook of Medical Statistics provides doctors and medical students with a concise and thorough account of this often difficult subject. It promotes understanding and interpretation of statistical methods across a wide range of topics, from study design and sample size considerations, through t- and chi-squared tests, to complex multifactor analyses, using examples from published research. References for further reading are given for more information on specific topics.
Helping readers to conduct their own research or critically appraise other's work, this volume provides all the information readers need to understand and interpret medical statistics.