Biostatistics for Population Health: A Primer 1st Edition by Lisa M. Sullivan, ISBN-13: 978-1284194265

Description

Biostatistics for Population Health: A Primer 1st Edition by Lisa M. Sullivan, ISBN-13: 978-1284194265

[PDF eBook eTextbook]

• Publisher: ‎ Jones & Bartlett Learning; 1st edition (April 16, 2020)
• Language: ‎ English
• ISBN-10: ‎ 1284194264
• ISBN-13: ‎ 978-1284194265

Written for undergraduate and graduate students with little or no mathematical background, Biostatistics for Population Health: A Primer offers current and future health professionals a clear, and accessible approach to learning the basic tools and techniques necessary to conduct biostatistical analyses and the professional confidence to critically evaluate and interpret biostatistical findings. Each unit begins with a contemporary population health issue (e.g., the opioid crisis, physical inactivity among children, diabetes) and raises questions that require the use of techniques discussed in that unit. Each technique, in turn, is illustrated with realistic, contemporary examples (e.g. vaping) to pique student interest. By the end of the unit, students are encouraged to apply the techniques to address the questions that were raised.

Key Features:

• Contemporary, realistic examples and straightforward approach makes material accessible to students with minimal background.

• Statistical and mathematical notation is kept to a minimum with focus on application and interpretation.

• Key points summarized at the end of each unit and a comprehensive glossary provide helpful references for students

• Concise length makes this text an easy and affordable supplement for a variety of courses.

• The instructor guide offers helpful suggestions and resources to engage students and encourage active learning.

Table of Contents:

Cover

Title Page

Copyright Page

Contents

Acknowledgment

Introduction

Unit 1 Summarizing Data for Decision Making

A Population Health Issue—The Opioid Crisis in the United States

Populations and Samples

1.1 Data, Measurement, and Variables

Dichotomous Variables

Categorical Variables

Ordinal Variables

Continuous Variables

1.2 Descriptive Statistics

Descriptive Statistics for Dichotomous Variables

Descriptive Statistics for Categorical and Ordinal Variables

Descriptive Statistics for Continuous or Measurement Variables

1.3 Risks, Rates, and Ratios and Their Use in Population Health

Risks

Rates

Ratios

1.4 Graphical Displays of Data

Distributions

Comparing Groups

Summarizing Associations

Trends over Time

1.5 Summary

Key Points

References

Unit 2 Associations Between Two Variables

A Population Health Issue—Physical Inactivity Among Children Worldwide Is Raising Concerns

2.1 Concepts and Applications of Probability

2.2 Screening and Diagnostic Tests

Performance Measures of Screening Tests

Bayes’ Rule

2.3 Probability Models

The Normal Distribution

The Standard Normal Distribution

Using z Scores for Comparisons

2.4 Estimation

The Central Limit Theorem

Confidence Interval Estimates

Confidence Interval Estimates for a Population Mean or a Population Proportion

Confidence Intervals Comparing Means in Two Independent Groups

Confidence Intervals Comparing Means in Two Matched or Paired Groups

Confidence Intervals Comparing Proportions, Risks, and Rates in Two Independent Groups

Confidence Intervals Comparing Proportions and Risks in Two Matched or Paired Groups

2.5 Tests of Hypothesis for Means and Proportions

Errors in Statistical Tests

Hypothesis Tests for a Population Mean or a Population Proportion

Hypothesis Tests Comparing Means in Two Independent Groups

Hypothesis Tests Comparing Means in Two Matched or Paired Groups

Hypothesis Tests Comparing Means in More than Two Groups

Hypothesis Tests Comparing Proportions in Two or More Independent Groups

Hypothesis Tests Comparing Proportions in Two Matched or Paired Groups

2.6 Correlation Analysis

Estimating a Correlation

Confidence Interval Estimate for a Population Correlation

Hypothesis Test for a Population Correlation

2.7 Summary

Key Points

References

Unit 3 Multivariable Analysis

A Population Health Issue—Diabetes Prevalence Increasing Worldwide

3.1 Bias, Confounding, and Effect Modification

3.2 Approaches to Address Confounding

3.3 Data Considerations for Multivariable Modelling

3.4 Multivariable Linear Regression Analysis

Crude, Unadjusted Linear Regression Models

Multivariable, Adjusted Linear Regression Models

3.5 Multivariable Logistic Regression Analysis

Crude, Unadjusted Logistic Regression Models

Multivariable, Adjusted Logistic Regression Models

3.6 Survival Analysis

Estimating a Survival Function

Comparing Survival in Two or More Independent Groups

Cox Proportional Hazards Regression Analysis

3.7 Summary

Key Points

References

Glossary

Index

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