Kim: Biostatistics for Oral Healthcare ~ Dental and Dentist

Like many projects, this project started out to meet a need: we were teaching classes of dental hygiene, dental and post graduate dentists and could not ﬁnd a textbook in statistics designed with the dental health professional in mind. So, we started to write a brief syllabus. We realized that most dentists will not become researchers, however, all will become consumers of research and will need to understand the inferential statistical principles behind the professional journals they read.

The goal of Biostatistics for Oral Healthcare is to give the reader a conceptual understanding of the basic statistical procedures used in the health sciences. Emphasis is given to the rationales, applications, and interpretations of the most commonly used statistical techniques rather than on their mathematical, computational, and theoretical aspects.

Achieving an effective level of communication in a technical book is always a difﬁcult challenge. If written at too low a level, a book will not really explain many important points and risks insulting intelligent readers as well as boring them. However, if written at too advanced a level, then a book may have difﬁculty ﬁnding an audience.

We have tried to write at a fairly elementary level, but have not hesitated to discuss certain advanced ideas. And we have gone rather deeply into a number of important concepts and methods.

DESCRIPTIVE STATISTICS

The content of Chapters 1 through 5 includes the basic concepts of statistics and covers descriptive statistics. Included are discussions of the rationale for learning and using statistics, mathematical concepts and guidelines for studying statistical concepts (Chapter 1); organizing and graphing data (Chapter 2); describing distributions, measures of central tendency, and measures of variation (Chapter 3); random variables including both discrete and continuous (Chapter 4); and the three most useful distributions in the health sciences: binomial distribution, Poisson distribution and normal distribution.

INFERENTIAL STATISTICS

The discussion of inferential statistics begins in Chapter 6 where the recurring question of sufﬁcient sample size is addressed. Chapters 7 through 9 covers how to determine appropriate sample size for a population and compute conﬁdence intervals as well as hypothesis testing and estimation for one-sample and two-sample cases for the mean and other statistics. Chapter 10 describes hypothesis testing for categorical data.

ADVANCED TOPICS

We began the text with a review of basic mathematical and statistical concepts and we end the text with some of the more sophisticated statistical concepts and procedures. We include discussions of one-way and two-way analysis of variance as well as a description of parametric statistical methods used for data analysis. And ﬁnally, we discuss non-parametric statistics and survival analysis that are particularly useful in dental and medical clinical trials.

It is our sincere hope that the conceptual approach of this book will prove to be a valuable guide for dental health professionals in basic introductory courses as well as more advanced graduate level courses. We hope that we have been successful in providing an integrated overview of the most useful analytical techniques that students and practitioners are bound to encounter in their future studies, research activities and most importantly, as consumers of evidence based dentistry.

We are grateful to Mr. J. Tanzman for his assistance in preparing the probability tables included in the Appendix. Thanks are also due to the students who took statistics courses in which the original manuscript was used as a textbook; their contributions to shaping this book can not be overstressed. Finally, it is a great pleasure to acknowledge Dr. Martha Nunn for her support and encouragement. Table H in the Appendix is her idea.

- The Authors -

Key Features

Comprehensive guide to biostatistics.
Draws on examples from dentistry and oral healthcare research.
Encourages intuitive understanding of statistical concepts.
Includes glossary of definitions and notation.

Contents

Chapter 1. Introduction.

1. What Is Biostatistics?.
2. Why Do I Need Statistics?.
3. How Much Mathematics Do I Need?.
4. How to Study Statistics?.
5. Reference.

Chapter 2. Summarizing Data.

1. Raw Data and Basic Terminology.
2. The Levels of Measurements.
3. Frequency Distributions.

Frequency Tables.
Relative Frequency.

4. Graphs.

Bar Graphs.
Pie Charts.
Line Graphs.
Histograms.
Stem and Leaf Plots.

5. Clinical Trials.
6. Confounding Variables.
7. Exercises.
8. References.

Chapter 3. Measures of Central Tendency, Dispersion, and Skewness.

1. Introduction.
2. Mean.
3. Weighted Mean.
4. Median.
5. Mode.
6. Geometric Mean.
7. Harmonic Mean.
8. Mean and Median of Grouped Data.
9. Mean of Two or More Means.
10. Range.
11. Percentiles and Interquartile Range.
12. Box-whisker Plot.
13. Variance and Standard Deviation.
14. Coefficient of Variation.
15. Variance of the Grouped Data.
16. Skewness.
17. Exercises.
18. References.

Chapter 4. Probability.

1. Introduction.
2. Sample Space and Events.
3. Basic Properties of Probability.
4. Independence and Mutually Exclusive Events.
5. Conditional Probability.
6. Bayes Theorem.
7. Rates and Proportions.

Prevalence and Incidence.
Sensitivity and Specificity.
Relative Risk and Odds Ratio.

8. Exercises.
9. References.

Chapter 5. Probability Distributions.

1. Introduction.
2. Binomial Distribution.
3. Poisson Distribution.
4. Poisson Approximation to Binomial Distribution.
5. Normal Distribution.

Properties of Normal Distributions.
Standard Normal Distribution.
Using Normal Probability Table.
Further Applications of Normal Probability.
Normal Approximation to the Binomial Distribution.

6. Exercises.
7. References.

Chapter 6. Sampling Distributions.

1. Introduction.
2. Sampling Distribution of the Mean.

Standard Error of the Sample Mean.
Central Limit Theorem.

3. Student's t Distribution.
4. Exercises.
5. References.

Chapter 7. Confidence Intervals and Sample Size.

1. Introduction.
2. Confidence Intervals for the Mean and Sample Size n when Is Known.
3. Confidence Intervals for the Mean when is Not Known.
4. Confidence Intervals for the Binomial Parameter p.
5. Confidence Intervals for the Variances and Standard Deviations.
6. Exercises.
7. References.

Chapter 8. Hypothesis Testing: One Sample Case.

1. Introduction.
2. Concept of Hypothesis Testing.
3. One-tailed Z Test of the Mean of a Normal Distribution When Is Known.
4. Two-tailed Z Test of the Mean of a Normal Distribution When Is Known.
5. t Test of the Mean of a Normal Distribution.
6. The Power of a Test and Sample Size.
7. One-Sample Test for a Binomial Proportion.
8. One-Sample Test for the Variance of a Normal Distribution.
9. Exercises.
10. References.

Chapter 9. Hypothesis Testing: Two-Sample Case.

1. Introduction.
2. Two Sample Z Test for Comparing Two Means.
3. Two Sample t Test for Comparing Two Means with Equal Variances.
4. Two Sample t Test for Comparing Two Means with Unequal Variances.
5. The Paired t Test.
6. Z Test for Comparing Two Binomial Proportions.
7. The Sample Size and Power of a Two Sample Test.

Estimation of a Sample Size.
The Power of a Two Sample Test.

8. The F Test for the Equality of Two Variances.
9. Exercises.
10. References.

Chapter 10. Categorical Data Analysis.

1. Introduction.
2. 2 x 2 Contingency Table.
3. r x c Contingency Table.
4. The Cochran-Mantel-Haenszel Test.
5. The McNemar Test.
6. The Kappa Statistic.
7. Goodness of Fit Test.
8. Exercises.
9. References.

Chapter 11. Regression Analysis and Correlation.

1. Introduction.
2. Simple Linear Regression.

Description of Regression Model.
Estimation of Regression Function.
Aptness of a Model.

3. Correlation Coefficient.

Significance of Correlation Coefficient.

4. Coefficient of Determination.
5. Multiple Regression.
6. Logistic Regression.

The Logistic Regression Model.
Fitting the Logistic Regression Model.

7. Multiple Logistic Regression Model.
8. Exercises.
9. References.

Chapter 12. One-Way Analysis of Variance.

1. Introduction.
2. Factors and Factor Levels.
3. Statement of the Problem and Model Assumptions.
4. Basic Concepts in ANOVA.
5. F-test for Comparison of k Population Means.
6. Multiple Comparisons Procedures.

Least Significant Difference Method.
Bonferroni Approach.
Scheffe's Method.
Tukey's Procedure.

7. One-way ANOVA Random Effects Model.
8. Test for Equality of k Variances.

Bartlett's Test.
Hartley's Test.

9. Exercises.
10. References.

Chapter 13. Two-Way Analysis of Variance.

1. Introduction.
2. General Model.
3. Sum of Squares and Degrees of Freedom.
4. F Test.
5. Exercises.
6. References.

Chapter 14. Non-Parametric Statistics.

1. Introduction.
2. The Sign Test.
3. The Wilcoxon Rank Sum Test.
4. The Wilcoxon Signed Rank Test.
5. The Median Test.
6. The Kruskal-Wallis Test.
7. The Friedman Test.
8. The Permutation Test.
9. The Cochran Test.
10. The Squared Rank Test For Variances.
11. Spearman's Rank Correlation Coefficient.
12. Exercises.
13. References.

Chapter 15. Survival Analysis.

1. Introduction.
2. Person-Time Method and Mortality Rate.
3. Life Table Analysis.
4. Hazard Function.
5. Kaplan-Meier Product Limit Estimator.
6. Comparing Survival Functions.

Gehan's Generalized Wilcoxon Test.
The Logrank Test.
The Mantel and Haenszel Test.

7. Piecewise Exponential Estimator (PEXE).

Small Sample Illustration.
General Description of PEXE.
An Example.
Properties of PEXE and Comparisons with Kaplan-Meier Estimator.

8. References.

Appendix.

Solutions to Selected Exercises.
Table A. Table of Random Numbers.
Table B. Table of Binomial Probabilities.
Table C. Table of Poisson Probabilities.
Table D. Standard Normal Probabilities.
Table E. Percentiles of the t Distribution.
Table F. Percentiles of the Distribution.
Table G. Percentiles of the F Distribution.

Product Details

Hardcover: 344 pages
Publisher: Wiley-Blackwell; 1 edition (January 1, 2008)
Language: English
ISBN-10: 081382818X
ISBN-13: 978-0813828183
Product Dimensions: 10.1 x 7.2 x 1 inches

List Price: $156.99

Tags: Dental Public Health