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Fundamentals of Biostatistics (with CD-ROM)

ISBN: 9780534418205 | 0534418201
Edition: 6th
Format: Hardcover
Publisher: Cengage Learning
Pub. Date: 2/24/2005

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SummaryTable of Contents
FUNDAMENTALS OF BIOSTATISTICS (WITH CD-ROM) leads you through the methods, techniques, and computations necessary for success in the medical field. Every new concept is developed systematically through completely worked out examples from current medical research problems.
Prefacexv
General Overview
1(5)
Descriptive Statistics
6(37)
... MOREIntroduction
6(2)
Measures of Location
8(7)
Some Properties of the Arithmetic Mean
15(2)
Measures of Spread
17(4)
Some Properties of the Variance and Standard Deviation
21(2)
The Coefficient of Variation
23(2)
Grouped Data
25(3)
Graphic Methods
28(5)
Case Study 1: Effects of Lead Exposure on Neurological and Psychological Function in Children
33(1)
Case Study 2: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
34(1)
Obtaining Descriptive Statistics on the Computer
35(1)
Summary
35(8)
Problems
37(6)
Probability
43(38)
Introduction
43(1)
Definition of Probability
44(2)
Some Useful Probabilistic Notation
46(2)
The Multiplication Law of Probability
48(2)
The Addition Law of Probability
50(2)
Conditional Probability
52(5)
Bayes' Rule and Screening Tests
57(6)
Bayesian Inference
63(1)
ROC Curves
64(2)
Prevalence and Incidence
66(1)
Summary
67(14)
Problems
68(13)
Discrete Probability Distributions
81(41)
Introduction
81(1)
Random Variables
82(1)
The Probability-Mass Function for a Discrete Random Variable
83(2)
The Expected Value of a Discrete Random Variable
85(2)
The Variance of a Discrete Random Variable
87(1)
The Cumulative-Distribution Function of a Discrete Random Variable
88(2)
Permutations and Combinations
90(4)
The Binomial Distribution
94(6)
Expected Value and Variance of the Binomial Distribution
100(1)
The Poisson Distribution
101(5)
Computation of Poisson Probabilities
106(1)
Expected Value and Variance of the Poisson Distribution
107(1)
Poisson Approximation to the Binomial Distribution
108(4)
Summary
112(10)
Problems
112(10)
Continuous Probability Distributions
122(44)
Introduction
122(1)
General Concepts
122(3)
The Normal Distribution
125(4)
Properties of the Standard Normal Distribution
129(6)
Conversion from an N(μ,σ2) Distribution to an N(0,1) Distribution
135(5)
Linear Combinations of Random Variables
140(5)
Normal Approximation to the Binomial Distribution
145(5)
Normal Approximation to the Poisson Distribution
150(3)
Summary
153(13)
Problems
154(12)
Estimation
166(60)
Introduction
166(1)
The Relationship Between Population and Sample
167(2)
Random-Number Tables
169(4)
Randomized Clinical Trials
173(4)
Estimation of the Mean of a Distribution
177(18)
Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
195(1)
Estimation of the Variance of a Distribution
195(6)
Estimation for the Binomial Distribution
201(9)
Estimation for the Poisson Distribution
210(4)
One-Sided Confidence Intervals
214(2)
Summary
216(10)
Problems
217(9)
Hypothesis Testing: One-Sample Inference
226(70)
Introduction
226(1)
General Concepts
227(3)
One-Sample Test for the Mean of a Normal Distribution: One-Sided Alternatives
230(8)
One-Sample Test for the Mean of a Normal Distribution: Two-Sided Alternatives
238(7)
The Power of a Test
245(8)
Sample-Size Determination
253(6)
The Relationship Between Hypothesis Testing and Confidence Intervals
259(3)
Bayesian Inference
262(5)
One-Sample Χ2 Test for the Variance of a Normal Distribution
267(3)
One-Sample Test for a Binomial Proportion
270(7)
One-Sample Inference for the Poisson Distribution
277(5)
Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
282(1)
Summary
283(13)
Problems
285(11)
Hypothesis Testing: Two-Sample Inference
296(63)
Introduction
296(2)
The Paired t Test
298(5)
Interval Estimation for the Comparison of Means from Two Paired Samples
303(1)
Two-Sample t Test for Independent Samples with Equal Variances
304(4)
Interval Estimation for the Comparison of Means from Two Independent Samples (Equal Variance Case)
308(2)
Testing for the Equality of Two Variances
310(7)
Two-Sample t Test for Independent Samples with Unequal Variances
317(6)
Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
323(2)
The Treatment of Outliers
325(6)
Estimation of Sample Size and Power for Comparing Two Means
331(3)
Sample-Size Estimation for Longitudinal Studies
334(3)
Summary
337(22)
Problems
339(20)
Nonparametric Methods
359(26)
Introduction
359(2)
The Sign Test
361(5)
The Wilcoxon Signed-Rank Test
366(6)
The Wilcoxon Rank-Sum Test
372(5)
Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
377(2)
Summary
379(6)
Problems
379(6)
Hypothesis Testing: Categorical Data
385(79)
Introduction
385(1)
Two-Sample Test for Binomial Proportions
386(16)
Fisher's Exact Test
402(6)
Two-Sample Test for Binomial Proportions for Matched-Pair Data (McNemar's Test)
408(8)
Estimation of Sample Size and Power for Comparing Two Binomial Proportions
416(10)
R x C Contingency Tables
426(12)
Chi-Square Goodness-of-Fit Test
438(3)
The Kappa Statistic
441(4)
Summary
445(19)
Problems
446(18)
Regression and Correlation Methods
464(93)
Introduction
464(1)
General Concepts
465(3)
Fitting Regression Lines---The Method of Least Squares
468(5)
Inferences About Parameters from Regression Lines
473(10)
Interval Estimation for Linear Regression
483(4)
Assessing the Goodness of Fit of Regression Lines
487(5)
The Correlation Coefficient
492(4)
Statistical Inference for Correlation Coefficients
496(14)
Multiple Regression
510(21)
Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
531(7)
Partial and Multiple Correlation
538(2)
Rank Correlation
540(6)
Summary
546(11)
Problems
546(11)
Multisample Inference
557(73)
Introduction to the One-Way Analysis of Variance
557(1)
One-Way Analysis of Variance--Fixed-Effects Model
558(1)
Hypothesis Testing in One-Way Anova---Fixed-Effects Model
559(5)
Comparisons of Specific Groups in One-Way ANOVA
564(18)
Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
582(9)
Two-Way Analysis of Variance
591(9)
The Kruskal-Wallis Test
600(6)
One-Way Anova---The Random-Effects Model
606(7)
The Intraclass Correlation Coefficient
613(5)
Summary
618(12)
Problems
619(11)
Design and Analysis Techniques for Epidemiologic Studies
630(114)
Introduction
630(1)
Study Design
631(3)
Measures of Effect for Categorical Data
634(10)
Confounding and Standardization
644(7)
Methods of Inference for Stratified Categorical Data---The Mantel-Haenszel Test
651(14)
Power and Sample-Size Estimation for Stratified Categorical Data
665(3)
Multiple Logistic Regression
668(22)
Meta-Analysis
690(5)
Equivalence Studies
695(4)
The Cross-Over Design
699(9)
Clustered Binary Data
708(8)
Measurement-Error Methods
716(9)
Missing Data
725(6)
Summary
731(13)
Problems
733(11)
Hypothesis Testing: Person-Time Data
744(73)
Measure of Effect for Person-Time Data
744(2)
One-Sample Inference for Incidence-Rate Data
746(4)
Two-Sample Inference for Incidence-Rate Data
750(8)
Power and Sample-Size Estimation for Person-Time Data
758(5)
Inference for Stratified Person-Time Data
763(9)
Power and Sample-Size Estimation for Stratified Person-Time Data
772(5)
Testing for Trend: Incidence-Rate Data
777(4)
Introduction to Survival Analysis
781(2)
Estimation of Survival Curves: The Kaplan-Meier Estimator
783(7)
The Log-Rank Test
790(7)
The Proportional-Hazards Model
797(10)
Power and Sample-Size Estimation under the Proportional-Hazards Model
807(4)
Summary
811(6)
Problems
812(5)
APPENDIX Tables
817(28)
Exact Binomial Probabilities Pr(X = k) =(n/k)pk qn-k
817(5)
Exact Poisson Probabilities Pr(X = k) =e-μμk/k!
822(3)
The Normal Distribution
825(5)
Table of 1000 Random Digits
830(1)
Percentage Points of the t Distribution (t d,u)
831(1)
Percentage Points of the Chi-Square Distribution (Chi;2 d,u)
832(1)
Exact Two-Sided 100% x (1 - α) Confidence Limits for Binomial Proportions (α = .05)
833(1)
Exact Two-Sided 100% x (1 - α) Confidence Limits for Binomial Proportions (α = .01)
834(1)
Confidence Limits for the Expectation of a Poisson Variable (μ)
835(1)
Percentage Points of the F Distribution (F d1,d2,p)
836(2)
Critical Values for the ESD (Extreme Studentized Deviate) Outlier Statistic (ESD n,1-alpha;' α = .05, .01)
838(1)
Two-Tailed Critical Values for the Wilcoxon Signed-Rank Test
839(1)
Two-Tailed Critical Values for the Wilcoxon Rank-Sum Test
840(2)
Fisher's z Transformation
842(1)
Two-Tailed Upper Critical Values for the Spearman Rank-Correlation Coefficient (r s)
843(1)
Critical Values for the Kruskal-Wallis Test Statistic (H) for Selected Sample Sizes for k = 3
844(1)
Answers to Selected Problems845(4)
Flowchart: Methods of Statistical Inference849(6)
Index of Data Sets855(2)
Index857

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