Using and understanding medical statistics
Since the last edition of this book was published, major developments in computer technology have affected both the practice of medicine and the methods of analyzing medical data. These advances make the focus of this revised edition - understanding many of the statistical methods that are used in modern medical studies-all the more important. Two new chapters have been added by the authors. One provides readers with an introduction to the analysis of longitudinal data. The other augments previous material concerning the design of clinical trials, exploring topics such as the use of surrogate markers, multiple outcomes, equivalence trials, and the planning of efficacy-toxicity studies. In addition to providing new information and fine-tuning the rest of the book, the authors have reorganized the final six chapters so that the topics build, naturally, on each other. This latest edition is highly recommended both as an excellent introduction to medical statistics and as a valuable tool in explaining the more complex statistical methods and techniques used today.
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Tests of Significance ll
Approximate Significance Tests for Contingency Tables
Some Warnings concerning 2 X 2 Tables
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2X2 table analyze approximate assay results assumption back pain blood pressure brain weight censored chapter clinical trial column totals confidence interval contingency table corresponding covariates critical values cumulative probability curve data with respect degrees of freedom discussed disease equal equation estimated survival curve estrogen example expected numbers expected values F-distribution fetal mortality Fisher's test graft rejection Group hemophiliacs histogram hypothesis is true indicates involves Kaplan-Meier estimated linear regression LITSIZ litter log-rank test logistic regression logistic regression model lymphoma marrow cell dose medical research methods normal distribution null hypothesis number of deaths observed value odds ratio outcome p-value patients population possible Pr(T Pr(X Pr(Z presented previous pregnancies probability distribution probability of survival random variable regimen regression analysis regression coefficients regression model relapse rates relative risk represent significance level significance test specified standard error statistician stratified symptoms table of expected test statistic tion treatment difference tumor variance x2 test zero