Introductory Applied Biostatistics, Preliminary Edition,9780534406899

Introductory Applied Biostatistics, Preliminary Edition

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Edition: 1st
ISBN13: 9780534406899
ISBN10: 0534406890
Format: Paperback
Pub. Date: 2003-07-10
Publisher(s): Brooks Cole
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Summary

INTRODUCTORY APPLIED BIOSTATISTICS provides a solid and engaging background for students learning to apply and appropriately interpret statistical applications in the medical and public health fields. The many examples drawn directly from the authors' remarkable clinical experiences with applied biostatistics make this text relevant, practical, and interesting for students. This flexible textbook encourages students to master application techniques by hand before moving on to computer applications, with SAS programming code and output for each technique covered in every chapter. The majority of the textbook addresses methods for statistical inference, including one- and two-sample tests for means and proportions, analysis of variance techniques, correlation, and regression analysis. For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results.

Table of Contents

1 Introduction 1(2)
2 Motivation 3(12)
2.1 Introduction
3(1)
2.2 Vocabulary
3(3)
2.3 Population Parameters
6(3)
2.4 Sampling and Sample Statistics
9(3)
2.5 Statistical Inference
12(3)
3 Summarizing Data 15(77)
3.1 Introduction
15(1)
3.2 Background
16(2)
3.2.1 Vocabulary
16(1)
3.2.2 Classification of Variables
17(1)
3.2.3 Notation
17(1)
3.3 Descriptive Statistics and Graphical Methods
18(43)
3.3.1 Numerical Summaries for Continuous Variables
19(21)
3.3.2 Graphical Summaries for Continuous Variables
40(5)
3.3.3 Numerical Summaries for Discrete Variables
45(9)
3.3.4 Graphical Summaries for Discrete Variables
54(7)
3.4 Key Formulas
61(4)
3.5 Statistical Computing
65(10)
3.6 Problems
75(17)
4 Probability 92(69)
4.1 Introduction
92(1)
4.2 Background
93(2)
4.2.1 Vocabulary
93(2)
4.3 First Principles
95(7)
4.4 Combinations and Permutations
102(6)
4.5 The Binomial Distribution
108(5)
4.6 The Normal Distribution
113(21)
4.6.1 Percentiles of the Normal Distribution
127(2)
4.6.2 Normal Approximation to the Binomial
129(5)
4.7 Key Formulas
134(2)
4.8 Applications Using SAS
136(11)
4.9 Problems
147(14)
5 Sampling Distributions 161(29)
5.1 Introduction
161(1)
5.2 Background
161(3)
5.3 The Central Limit Theorem
164(13)
5.2 Key Formulas
177(1)
5.3 Applications Using SAS
178(7)
5.4 Problems
185(5)
6 Statistical Inference: Procedures for p 190(68)
6.1 Introduction
190(1)
6.2 Estimating µ
191(18)
6.2.1 Vocabulary and Notation
191(3)
6.2.2 Confidence Intervals for p
194(9)
6.2.3 Precision and Samples Size Determination
203(6)
6.3 Testing Hypotheses Concerning
209(29)
6.3.1 Vocabulary and Notation
209(8)
6.3.2 Hypothesis Tests Concerning µ
217(9)
Interpreting P-Values from SAS
223(2)
Computing P-Values by Hand
225(1)
6.3.3 Power and Samples Size Determination
226(12)
6.4 Key Formulas
238(1)
6.5 Statistical Computing
239(7)
6.6 Problems
246(12)
7 Statistical Inference: Procedures for (µ1-µ2) 258(69)
7.1 Introduction
258(3)
7.2 Statistical Inference Concerning (µ1-µ2)
261(35)
7.2.1 Case 1: Two Independent Populations- Population Variances Known
261(5)
7.2.2 Case 2: Two Independent Populations- Population Variances Assumed Equal
266(6)
7.2.3 Case 3: Two Independent Populations- Population Variances Possibly Unequal
272(18)
7.2.4 Case 4: Two Dependent Populations-The Data Are Matched or Paired
290(6)
7.3 Power and Samples Size Determination
296(8)
7.4 Key Formulas
304(1)
7.5 Statistical Computing
305(9)
7.6 Problems
314(13)
8 Categorical Data 327(68)
8.1 Introduction
327(1)
8.2 Statistical Inference Concerning p
328(6)
8.3 Cross-tabulation Tables
334(3)
8.4 Diagnostic Tests: Sensitivity and Specificity
337(2)
8.5 Statistical Inference Concerning (p1-p2)
339(6)
8.6 Chi-Square Tests
345(19)
8.6.1 Goodness of Fit Test
345(7)
8.6.2 Tests of Independence
352(12)
8.7 Precision, Power and Sample Size Determination
364(6)
8.8 Key Formulas
370(1)
8.9 Statistical Computing
371(13)
8.10 Problems
384(11)
9 Comparing Risks in Two Populations 395(42)
9.1 Introduction
395(1)
9.2 Effect Measures
396(2)
9.3 Confidence Intervals for Effect Measures
398(6)
9.4 The Chi-square Test of Homogeneity
404(7)
9.5 Fisher's Exact Test
411(2)
9.6 Cox-Mantel-Haenel Method
413(5)
9.7 Precision, Power and Sample Size Determination
418(1)
9.8 Key Formulas
419(1)
9.9 Statistical Computing
420(11)
9.10 Problems
431(6)
10 Analysis of Variance 437(67)
10.1 Introduction
437(1)
10.2 Background Logic
438(6)
10.3 Notation and Examples
444(13)
10.4 Fixed vs. Random Effects Models
457(1)
10.5 Evaluating Treatment Effects
458(1)
10.6 Multiple Comparisons
459(13)
10.6.1 The Scheffe Procedure
461(6)
10.6.2 The Tukey Procedure
467(5)
10.7 Repeated Measures Analysis of Variance
472(7)
10.8 Key Formulas
479(1)
10.9 Statistical Computing
480(12)
10.10 Problems
492(12)
11 Correlation and Regression 504(45)
11.1 Introduction
504(1)
11.2 Correlation Analysis
505(13)
11.2.1 The Sample Correlation Coefficient r
508(5)
11.2.2 Statistical Inference Concerning p
513(5)
11.3 Simple Linear Regression
518(9)
11.4 Multiple Regression Analysis
527(3)
11.5 Logistic Regression Analysis
530(4)
11.6 Key Formulas
534(1)
11.7 Statistical Computing
535(8)
11.8 Problems
543(6)
12 Logistic Regression Analysis 549(34)
12.1 Introduction
549(1)
12.2 The Logistic Model
549(2)
12.3 Statistical Inference for Simple Logistic Regression
551(9)
12.4 Multiple Logistic Regression
560(5)
12.5 ROC Area
565(5)
12.6 Key Formulas
570(1)
12.7 Statistical Computing
571(6)
12.8 Problems
577(6)
13 Nonparametric Tests 583(37)
13.1 Introduction
583(1)
13.2 The Sign Test (Two Dependent Samples Test)
584(3)
13.3 The Wilcoxon Signed-Rank Test (Two Dependent Samples)
587(5)
13.4 The Wilcoxon Rank Sum Test (Two Independent Samples )
592(3)
13.5 The Kruskel-Wallis Test (k Independent Samples)
595(2)
13.6 Spearman Correlation (Correlation Between Variables)
597(7)
13.7 Key Formulas
604(1)
13.8 Statistical Computing
605(10)
13.9 Problems
615(5)
14 Introduction to Survival Analysis 620
14.1 Introduction
620(1)
14.2 Incomplete Follow-Up
620(2)
14.3 Time to Event
622(1)
14.4 Survival Analysis Techniques
623(8674289)
Appendix A: Introduction to Statistical Computing Using SAS i
A1. Introduction to SAS
i
A1.1 Components of a SAS Program
i
A1.2 Overview of the SAS System
iii
A1.3 Creating and Executing SAS Programs
v
A2. The Data Step
vi
A2.1 Inputting Data: Types of Data
vii
A2.2 Inputting Data: Types of Input
viii
A2.3 Missing Values
ix
A2.4 Advanced Data Input and Data Manipulation
x
Appendix B: Statistical Tables xix
I. Statistical Tables
xix
Table 1. Probabilities of the Binomial Distribution
xx
Table 2. Probabilities of the Standard Normal Distribution
xxviii
Table 2A. Z Values for Confidence Intervals
xxx
Table 2B. Z Values for Tests of Hypothesis
xxx
Table 3. Critical Values of the t Distribution
xxxi
Table 4. Critical Values of the F Distribution
xxxiii
Table 5. Critical Values of the X2 Distribution
xxxv
Table 6. Critical Values of the Studentized Range Statistic
xxxvi
II. SAS Programs used to generate table entries
xxxvii

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