Introductory Applied Biostatistics, Preliminary Edition

by D’Agostino, Sr., Ralph; Sullivan, Lisa; Beiser, Alexa

• ISBN13: 9780534406899
• ISBN10: 0534406890
• Edition: 1st
• Format: Paperback
• Copyright: 2003-07-10
• Publisher: Brooks Cole

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