Making Sense of Data: A Self-Instruction Manual on the Interpretation of Epidemiological Data

This self-instructional manual on the interpretation and use of epidemiologic data deals with the basic concepts and skills needed for the appraisal of published reports or one's own findings. Applications in clinical medicine, public health, community medicine, and research are all taken into consideration. Making Sense of Data is designed as a workbook of short exercises and instructional self-tests that introduce fundamental approaches and procedures in data interpretation and develop competency in working with epidemiologic tools. Basic concepts are presented in the first section, which also demonstrates the step-by-step assessment of data. The next section discusses rates and other simple measures, and the third shows how to judge their accuracy. Section IV and V deal with more complex issues of associations between variables and the appraisal of cause-effect relationships. Section VI deals with meta-analysis (the critical review and integration of the findings from separate studies) and section VII with the questions to be asked before deciding to apply study results in practice. Numerous changes have been made in this edition, including the addition of a section on the practical application of epidemiological findings, discussions of new topics (Cox proportional hazards regression, qualitative studies, ROC curves), and fresh examples.