This comprehensive, graduate-level text for advanced practice nurses and other health care professionals provides state-of-the-art tools that facilitate the reading and interpretation of clinical research articles that use increasingly complex statistical techniques. It addresses clinically relevant topics in biostatistics beyond the usual introduction to linear models, such as survival analysis and evaluation of screening tests. The text emphasizes the importance of understanding the underlying logic of statistical inference and statistical models to support correct interpretation and effective translation into practice. It promotes appropriate statistical method selection for conducting translational research.
With a focus on disseminating information in easily understandable language, the text addresses basic statistical reasoning and four different classes of statistical models. The appendix provides refreshers on the algebraic underpinnings of statistics. More complex algebraic derivations are highlighted in boxes throughout the text chapters. The text explains how to work with the exponential expressions and logarithms necessary for the interpretation of logistic and hazard regression models and features clear explanations of more sophisticated statistical models, inference, and analyses. Chapters include examples from current research and multiple exercises designed to reinforce learning.
Key Features:- End-of-chapter exercises include both problems of interpretation and numerical problems that can be solved via hand calculations.
- For instructors and students interested in practical data analysis, data sets and practice problems are available from Springer Publishing Company's website with instructions in SPSS, STATA, and SAS formats.
- At the end of each chapter is a "Literature Application" text box with interpretation questions about a recent research article that highlights the statistical model discussed in the chapter.
- Throughout the book, text boxes highlight the most important algebraic formulas useful in interpreting statistical methods.
- A chapter on data management practices and ethical issues of privacy maintenance is included.
- Nine appendices provide tables of major probability distributions, for example, normal, t- and F-distributions, and algebraic derivations of some of the most important results in statistics.
Contents
Preface
Acknowledgments
PART I: FOUNDATIONS FOR STATISTICAL THINKING
1. Introduction: The Role of Statistics in Research and Clinical Practice
2. Properties of Variables: Levels of Measurement
3. Descriptive Univariate Statistics
4. Probabilities
5. Logic of Statistical Inference: The Sampling Distribution and Significance Tests
6. Standard Errors, Confidence Intervals, and the Power of Statistical Tests
7. Research Designs and Statistical Analysis
PART II: MODELS FOR CONTINUOUS/INTERVAL-LEVEL OUTCOME MEASURES
8. t-Test
9. One-Way Analysis of Variance
10. Linear Regression and Pearson’s r Correlation
11. Factorial Analysis of Variance and Analysis of Covariance
12. Multiple Linear Regression
13. Repeated-Measures Analysis of Variance
14. Introduction to Mixed-Effects Regression Models
PART III: MODELS FOR CATEGORICAL OUTCOME MEASURES
15. Nonparametric/Ordinal Statistics
16. Frequency Cross-Tabulations: 2 Ëš 2 Tables
17. Logistic Regression With One Independent Variable
18. Logistic Regression Models With Multiple Predictors
PART IV: MODELS FOR TIME-TO-EVENT DATA/SURVIVAL ANALYSIS
19. Incidence Rates, Life Tables, and Survival Function
20. Comparing Survival Functions in Different Groups and Hazard Regression
PART V: MEASUREMENT MODELS
21. Reliability Coefficients and Medical Test Evaluation
22. Factor Analysis
PART VI: ISSUES IN DATA MANAGEMENT
23. Data Management and Privacy Concerns
APPENDICES
A. Estimating Population Variance From Sample Variance
B. One-Sided Probabilities for z-Scores of the Standard Normal Distribution
C. Table of Critical t-Values for Several Significance Levels of t-Distributions With Different Degrees of Freedom (df)
D. Normalizing a Nonnormal Distribution
E. Table of Critical f-Values at the Significance Level of a = 0.05 of f-Distributions With Different Degrees of Freedom (df)
F. Proof That Phi = Pearson’s r
G. Table of Critical Chi-Square Values for Several Significance Levels of Chi-Square Distributions With Different Degrees of Freedom (df)
H. Refresher on Exponential and Logarithmic Transformations
I. Standardization of Interval-Level Variables
J. Answers to Selected Exercises
Index
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- Release Date: June 9, 2014
- Paperback / softback
- 350 Pages
- Trim Size: 7in x 10in
- ISBN: 9780826198242
- eBook ISBN: 9780826198259
