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While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. This text presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression model for continuous outcomes, the logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The author emphasizes adequate use, correct interpretation of results, appropriate presentation of results, and avoidance of potential pitfalls.
The author reviews the essentials of logistic regression and discusses the variety of mechanisms which might cause missing values while the rest of the book covers the methods which may be used to deal with missing values and their effectiveness.
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