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Essentials of Biostatistics In Public Health,9781449623944
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Essentials of Biostatistics In Public Health



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This is the 2nd edition with a publication date of 3/1/2011.

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Essentials of Biostatistics in Public Health, Second Edition provides a fundamental and engaging background for students learning to apply and appropriately interpret biostatistics applications in the field of public health.Many examples are drawn directly from the author's remarkable clinical experiences with the renowned Framingham Heart Study, making this text practical, interesting, and accessible for those with little mathematical background. The examples are real, relevant, and manageable in size so that students can easily focus on applications rather than become overwhelmed by computations. The text is accompanied by an online workbook: Statistical Computing Using Microsoft Excel (for Mac or PC).New Features of the Second Edition:" Learning objectives and more practice problems for every chapter" A new chapter on survival analysis " A new chapter on nonparametric statistics " Coverage of sensitivity, specificity, and performance of screening tests connecting probability to real and important applications" An expansion of the chapter on multivariable methods with more emphasis on interpretation of multivariable regression " A bank of questions for the audience response system ( ;clickers ;) for instructors

Table of Contents

Acknowledgmentsp. vii
Prefacep. ix
Prologuep. xi
About the Authorp. xiii
Introductionp. 1
What Is Biostatistics?p. 2
What Are the Issues?p. 2
Summaryp. 4
Study Designsp. 7
Vocabularyp. 8
Observational Study Designsp. 8
Randomized Study Designsp. 13
The Framingham Heart Studyp. 17
More on Clinical Trialsp. 17
Sample Size Implicationsp. 20
Summaryp. 20
Practice Problemsp. 20
Quantifying the Extent of Diseasep. 23
Prevalencep. 23
Incidencep. 24
Relationships Between Prevalence and Incidencep. 26
Comparing the Extent of Disease Between Groupsp. 27
Summaryp. 30
Practice Problemsp. 30
Summarizing Data Collected in the Samplep. 35
Dichotomous Variablesp. 36
Ordinal and Categorical Variablesp. 40
Continuous Variablesp. 49
Summaryp. 60
Practice Problemsp. 62
The Role of Probabilityp. 67
Samplingp. 67
Basic Conceptsp. 69
Conditional Probabilityp. 70
Independencep. 73
Bayes' Theoremp. 74
Probability Modelsp. 75
Summaryp. 96
Practice Problemsp. 96
Confidence Interval Estimatesp. 101
Introduction to Estimationp. 101
Confidence Intervals for One Sample, Continuous Outcomep. 103
Confidence Intervals for One Sample, Dichotomous Outcomep. 104
Confidence Intervals for Two Independent Samples, Continuous Outcomep. 106
Confidence Intervals for Matched Samples, Continuous Outcomep. 110
Confidence Intervals for Two Independent Samples, Dichotomous Outcomep. 113
Summaryp. 117
Practice Problemsp. 118
Hypothesis Testing Proceduresp. 123
Introduction to Hypothesis Testingp. 123
Tests with One Sample, Continuous Outcomep. 130
Tests with One Sample, Dichotomous Outcomep. 133
Tests with One Sample, Categorical and Ordinal Outcomesp. 134
Tests with Two Independent Samples, Continuous Outcomep. 138
Tests with Matched Samples, Continuous Outcomep. 141
Tests with Two Independent Samples, Dichotomous Outcomep. 144
Tests with More Than Two Independent Samples, Continuous Outcomep. 147
Tests for Two or More Independent Samples, Categorical and Ordinal Outcomesp. 156
Summaryp. 160
Practice Problemsp. 162
Power and Sample Size Determinationp. 169
Issues in Estimating Sample Size for Confidence Intervals Estimatesp. 170
Issues in Estimating Sample Size for Hypothesis Testingp. 176
Summaryp. 185
Practice Problemsp. 185
Multivariable Methodsp. 189
Confounding and Effect Modificationp. 190
The Cochran-Mantel-Haenszel Methodp. 197
Introduction to Correlation and Regression Analysisp. 198
Multiple Linear Regression Analysisp. 206
Multiple Logistic Regression Analysisp. 210
Summaryp. 213
Practice Problemsp. 214
Nonparametric Testsp. 219
Introduction to Nonparametric Testingp. 221
Tests with Two Independent Samplesp. 223
Tests with Matched Samplesp. 229
Tests with More Than Two Independent Samplesp. 236
Summaryp. 240
Practice Problemsp. 241
Survival Analysisp. 243
Introduction to Survival Datap. 245
Estimating the Survival Functionp. 247
Comparing Survival Curvesp. 252
Cox Proportional Hazards Regression Analysisp. 260
Extensionsp. 264
Summaryp. 265
Practice Problemsp. 267
Appendixp. 271
Glossaryp. 289
Indexp. 299
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