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

Name: Making Sense of Data A Self-Instruction Manual on the Interpretation of Epidemiological Data
Price: 4.6 USD
Availability: InStock
ISBN: 9780195145250

ISBN-10: 0195145259

ISBN-13: 9780195145250

Edition: 3rd 2001 (Revised)

Authors: J. H. Abramson, Z. H. Abramson

List price: $81.00

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This is a self-instructional manual on the interpretation and use of epidemiologic data that deals with the basic concepts and skills needed for appraising published reports or study findings. Applications in clinical medicine, public health, community medicine, and research are presented. The numerous changes in this edition include the addition of a section on questions to be asked before deciding to apply study results in practice, discussions of new topics (Cox proportionalhazards regression, qualitative studies, ROC curves), and fresh examples.

Book details

List price: $81.00
Edition: 3rd
Copyright year: 2001
Publisher: Oxford University Press, Incorporated
Publication date: 9/6/2001
Binding: Paperback
Pages: 384
Size: 8.90" wide x 5.79" long x 0.71" tall
Weight: 1.188



Introduction


The aim of this book


How to use this book



Basic Concepts And Procedures



Introduction



Determining what the facts are


Summarizing the facts



Absolute and relative differences



Diagrams



Seeking explanations for the facts


Testing explanations



The basic scientific process


Rates



Rates (continued)


Inspecting a two-dimensional table



Inspecting a two-dimensional table (continued)



Inspecting a two-dimensional table (continued)


Associations



Associations (continued)


Confounding



Confounding (continued)


Effect modification



Refinement


Skeleton tables


Elaborating an association



Modifying and confounding effects



Elaborating an association (continued)



The use of rates


Causal explanations


Testing causal explanations



Testing causal explanations (continued)


Basic procedure for appraisal of data


What are the facts?


What are the possible explanations?


What additional information is required?



Uses of epidemiological data



Test Yourself (A)



Rates And Other Measures



Introduction


What is a rate?


Prevalence rates



Prevalence rates (continued)


Questions about a rate


What kind of rate is it?


Of what is it a rate?


To what population or group does the rate refer?


How was the information obtained?



Sources of bias


Confidence interval


Validity


Qualitative studies



Use of prevalence data


Incidence rates



Incidence rates (continued)



Bias in incidence studies



Uses of incidence rates



Estimating the individual's chances


Time to event (survival time)



Estimating the individual's chances (continued)


Other rates


What are the odds?



Other rates (continued)


Odds ratio



Other measures



Indirect standardization



Indirect standardization (continued)


Direct Standardization



The use of standardized rates



Test Yourself (B)



How Good Are The Measures?



Introduction



Validity of a measure


Sensitivity and specificity



Misclassification



Differential misclassification



Effects of misclassification



Effects of misclassification (continued)



Other ways of appraising validity


Reliability



Appraisal of reliability



Appraisal of reliability (continued)


Regression toward the mean


Taking account of validity and reliability


Screening tests



Appraisal of a screening test



Appraisal of a screening test (continued)



Appraisal of diagnostic tests


ROC curves


The meaning of ""normal""



Test Yourself (C)



Making Sense Of Associations



Introduction



Explanations for an association



Effects of misclassification


Statistical significance



Statistical significance (continued)



Confounding effects



Confounding effects (continued)



Multivariate analysis



Explanations for the findings


Risk factors and risk markers


Appraising a risk marker


Uses of the findings



Risk factors and risk markers (continued)


Measures of the strength of an association



Measures of strength



Measures of strength (continued)


Matched samples



Synergism



Appraising stratified data


Making sense of a multivariate analysis



Multiple logistic regression



Multiple logistic regression (continued)



Proportional hazards regression



Multiple linear regression



Test Yourself (D)



Causes And Effects



Introduction


Kinds of study



Appraising the results of a cross-sectional study



Appraising the results of a case-control study



Appraising the results of a cohort study



Appraising the results of a group-based study



Appraising the results of an experiment



Appraising the results of a quasi-experiment



Artifact, confound or cause?



Coping with confounding


Delving into causes



Evidence for a causal relationship



Evidence for a causal relationship (continued)



mpact of a causal factor



The attributable fraction



Prevented and preventable fractions



Test Yourself (E)



Meta-Analysis: Putting It All Together



Introduction



The scope of meta-analysis



Measures used in meta-analysis



Measures used in meta-analysis (continued)


Basic information



Finding the studies



Selecting studies



The quality of the studies


Extracting the findings


Apples and oranges



Appraising combinability


Explaining heterogeneity



Explaining heterogeneity (continued)



Effect modification



Using the results


Evaluating a meta-analysis


F12



Putting Study Findings To Use



Introduction



Are the results accurately known?



Validity of the findings



Relevance of the findings



Expected effects



Feasibility and cost



Test Yourself (G)


References


Index