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Fundamentals of Biostatistics

ISBN: 9780534370688 | 0534370683
Edition: 5th
Format: Paperback
Publisher: Duxbury Press
Pub. Date: 12/17/1999

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SummaryTable of Contents
Bernard Rosner's FUNDAMENTALS OF BIOSTATISTICS is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through... MORE
General Overview
1(6)
Reference
5(2)
Descriptive Statistics
... MORE(38)
Introduction
7(2)
Measures of Location
9(7)
Some Properties of the Arithmetic Mean
16(2)
Measures of Spread
18(4)
Some Properties of the Variance and Standard Deviation
22(2)
The Coefficient of Variation
24(1)
Grouped Data
25(3)
Graphic Methods
28(7)
Case Study 1: Effects of Lead Exposure on Neurological and Psychological Function in Children
35(1)
Case Study 2: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
36(1)
Summary
37(8)
Problems
39(5)
References
44(1)
Probability
45(34)
Introduction
45(1)
Definition of Probability
46(1)
Some Useful Probabilistic Notation
47(2)
The Multiplication Law of Probability
49(3)
The Addition Law of Probability
52(2)
Conditional Probability
54(4)
Bayes' Rule and Screening Tests
58(7)
Prevalence and Incidence
65(1)
Summary
66(13)
Problems
66(10)
References
76(3)
Discrete Probability Distributions
79(38)
Introduction
79(1)
Random Variables
80(1)
The Probability Mass Function for a Discrete Random Variable
81(2)
The Expected Value of a Discrete Random Variable
83(2)
The Variance of a Discrete Random Variable
85(1)
The Cumulative-Distribution Function of a Discrete Random Variable
86(1)
Permutations and Combinations
87(4)
The Binomial Distribution
91(6)
Expected Value and Variance of the Binomial Distribution
97(1)
The Poisson Distribution
98(4)
Computation of Poisson Probabilities
102(1)
Expected Value and Variance of the Poisson Distribution
103(2)
Poisson Approximation to the Binomial Distribution
105(3)
Summary
108(9)
Problems
108(7)
References
115(2)
Continuous Probability Distributions
117(40)
Introduction
117(1)
General Concepts
117(3)
The Normal Distribution
120(4)
Properties of the Standard Normal Distribution
124(6)
Conversion from an N(μ, σ2) Distribution to an N(0, 1) Distribution
130(3)
Linear Combinations of Random Variables
133(5)
Normal Approximation to the Binomial Distribution
138(7)
Normal Approximation to the Poisson Distribution
145(1)
Summary
146(11)
Problems
147(9)
References
156(1)
Estimation
157(54)
Introduction
157(1)
The Relationship Between Population and Sample
158(2)
Random-Number Tables
160(4)
Randomized Clinical Trials
164(4)
Estimation of the Mean of a Distribution
168(16)
Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
184(1)
Estimation of the Variance of a Distribution
185(6)
Estimation for the Binomial Distribution
191(5)
Estimation for the Poisson Distribution
196(3)
One-Sided Confidence Intervals
199(3)
Summary
202(9)
Problems
202(7)
References
209(2)
Hypothesis Testing: One-Sample Inference
211(62)
Introduction
211(1)
General Concepts
212(3)
One-Sample Test for the Mean of a Normal Distribution: One-Sided Alternatives
215(8)
One-Sample Test for the Mean of a Normal Distribution: Two-Sided Alternatives
223(6)
The Power of a Test
229(7)
Sample-Size Determination
236(7)
The Relationship Between Hypothesis Testing and Confidence Intervals
243(2)
One-Sample χ2 Test for the Variance of a Normal Distribution
245(4)
One-Sample Test for a Binomial Proportion
249(6)
One-Sample Inference for the Poisson Distribution
255(5)
Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
260(1)
Summary
261(12)
Problems
263(7)
References
270(3)
Hypothesis Testing: Two-Sample Inference
273(58)
Introduction
273(2)
The Paired t Test
275(4)
Interval Estimation for the Comparison of Means from Two Paired Samples
279(1)
Two-Sample t Test for Independent Samples with Equal Variances
280(4)
Interval Estimation for the Comparison of Means from Two Independent Samples (Equal Variance Case)
284(2)
Testing for the Equality of Two Variances
286(7)
Two-Sample t Test for Independent Samples with Unequal Variances
293(6)
Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
299(1)
The Treatment of Outliers
300(7)
Estimation of Sample Size and Power for Comparing Two Means
307(2)
Sample-Size Estimation for Longitudinal Studies
309(3)
Summary
312(19)
Problems
314(14)
References
328(3)
Nonparametric Methods
331(24)
Introduction
331(2)
The Sign Test
333(5)
The Wilcoxon Signed-Rank Test
338(5)
The Wilcoxon Rank-Sum Test
343(4)
Case Study: Effects of Lead Exposure on Neurological and Pyschological Function in Children
347(2)
Summary
349(6)
Problems
349(4)
References
353(2)
Hypothesis Testing: Categorical Data
355(70)
Introduction
355(1)
Two-Sample Test for Binomial Proportions
356(15)
Fisher's Exact Test
371(5)
Two-Sample Test for Binomial Proportions for Matched-Pair Data (McNemar's Test)
376(8)
Estimation of Sample Size and Power for Comparing Two Binomial Proportions
384(9)
R x C Contingency Tables
393(10)
Chi-Square Goodness-of-Fit Test
403(4)
The Kappa Statistics
407(4)
Summary
411(14)
Problems
411(12)
References
423(2)
Regression and Correlation Methods
425(86)
Introduction
425(1)
General Concepts
426(3)
Fitting Regression Lines---The Method of Least Squares
429(4)
Inferences about Parameters from Regression Lines
433(10)
Interval Estimation for Linear Regression
443(4)
Assessing the Goodness of Fit of Regression Lines
447(4)
The Correlation Coefficient
451(4)
Statistical Infernece for Correlation Coefficients
455(11)
Multiple Regression
466(21)
Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
487(8)
Partial and Multiple Correlation
495(1)
Rank Correlation
496(5)
Summary
501(10)
Problems
503(5)
References
508(3)
Multisample Inference
511(66)
Introduction to the One-Way Analysis of Variance
511(1)
One-Way Analysis of Variance---Fixed-Effects Model
512(1)
Hypothesis Testing in One-Way ANOVA---Fixed-Effects Model
513(5)
Comparisons of Specific Groups in One-Way ANOVA
518(14)
Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
532(10)
Two-Way Analysis of Variance
542(7)
The Kruskal-Wallis Test
549(6)
One-Way ANOVA---The Random-Effects Model
555(7)
The Intraclass Correlation Coefficient
562(4)
Summary
566(11)
Problems
567(7)
References
574(3)
Design and Analysis Techniques for Epidemiologic Studies
577(100)
Introduction
577(1)
Study Design
577(3)
Measures of Effect for Categorical Data
580(11)
Confounding and Standardization
591(5)
Methods of Inference for Stratified Categorical Data---The Mantel-Haenszel Test
596(13)
Power and Sample-Size Estimation for Stratified Categorical Data
609(3)
Multiple Logistic Regression
612(20)
Meta-Analysis
632(6)
Equivalance Studies
638(3)
The Cross-Over Design
641(8)
Clustered Binary Data
649(8)
Measurement-Error Methods
657(9)
Summary
666(11)
Problems
668(7)
References
675(2)
Hypothesis Testing: Person-Time Data
677(66)
Measure of Effect for Person-Time Data
677(2)
One-Sample Inference for Incidence-Rate Data
679(3)
Two-Sample Inference for Incidence-Rate Data
682(8)
Power and Sample-Size Estimation for Person-Time Data
690(5)
Inference for Stratified Person-Time Data
695(7)
Power and Sample-Size Estimation for Stratified Person-Time Data
702(5)
Testing for Trend: Incidence-Rate Data
707(3)
Introduction to Survival Analysis
710(3)
Estimation of Survival Curves: The Kaplan-Meier Estimator
713(6)
The Log-Rank Test
719(7)
The Proportional-Hazards Model
726(7)
Power and Sample-Size Estimation under the Proportional-Hazards Model
733(4)
Summary
737(6)
Problems
737(4)
References
741(2)
APPENDIX: Tables743(28)
Exact Binomial Probabilities
743(5)
Exact Poisson Probabilities
748(3)
The Normal Distribution
751(5)
Table of 1000 Random Digits
756(1)
Percentage Points of the t Distribution (td,u)
757(1)
Percentage Points of the Chi-Square Distribution
758(1)
Exact Two-Sided 100% x (1 - α) Confidence Limits for Binomial Proportions (α = .05)
759(1)
Exact Two-Sided 100% x (1 - α) Confidence Limits for Binomial Proportions (α = .01)
760(1)
Confidence Limits for the Expectation of a Poisson Variable (μ)
761(1)
Percentage Points of the F Distribution (Fd1,d2,p)
762(2)
Critical Values of the ESD (Extreme Studentized Deviate) Outlier Statistic (ESDn,1-α α = .05, .01)
764(1)
Tow-Tailed Critical Values for the Wilcoxon Signed-Rank Test
765(1)
Two-Tailed Critical Values for the Wilcoxon Rank-Sum Test
766(2)
Fisher's z transformation
768(1)
Two-Tailed Upper Critical Values for the Spearman Rank-Correlation Coefficient (rs)
769(1)
Critical Values for the Kruskal-Wallis Test Statistic (H) for selected sample sizes for k = 3
770(1)
Answers to Selected Problems771(4)
Flowchart: Methods of Statistical Inference775(6)
Index of Data Sets781(2)
Index783

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