Topics in Biostatistics

ISBN-13: 9781617376238 / Angielski / Miękka / 2010 / 528 str.

Walter T. Ambrosius

Opis

Basic Biostatistics presents a multidisciplinary survey of biostatics methods, each illustrated with hands-on examples. Methods range from the elementary, including descriptive statistics, study design, statistical interference, categorical variables, evaluation of diagnostic tests, comparison of means, linear regression, and logistic regression. These introductory methods create a portfolio of biostatistical techniques for both novice and expert researchers. More complicated statistical methods are introduced as well, including those requiring either collaboration with a biostatistician or the use of a statistical package. Specific topics of interest include microarray analysis, missing data techniques, power and sample size, statistical methods in genetics. Expert advice is given on when to seek statistical help, and how to conduct a meeting with the statistical collaborator or consultant. Basic Biostatistics is an essential resource for researchers at every level of their career.

Recenzje

From the reviews:

"It is useful to biologists as well as statisticians. The book describes the use of appropriate statistical methods and offers guidelines on selecting an appropriate test. ... The main strength of the book is the clear exposition of statistical tests. ... As biostatisticians we strongly recommend this book for libraries where research on molecular biology is going on, and students ... in biostatistics. ... helpful in understanding the essence of the statistical techniques to a wide range of researchers and students in biology and medicine." (Mukesh Srivastava and M. Abbas, Journal of Applied Statistics, Vol. 36 (4), April, 2009)

Spis treści

Outline: 1. Study Design-The Basics Hyun Ja Lim and Raymond Hoffmann, Medical College of Wisconsin 1. Introduction 2. Experimental Studies 2.1 Randomized controlled studies 2.2 Historically controlled studies 2.3 Crossover studies 2.4 Factorial designs 2.5 Cluster or group allocation designs 3. Randomization 3.1 Complete or simple randomization 3.2 Block randomization 3.3 Stratified randomization 4. Blinding/Masking 5. Biases 6. Analyses 6.1 Compliance 6.2 Intention-to-treat (ITT) analysis 6.3 As received and per-protocol (PP) analysis 6.4 Subgroup analysis 6.5 Exploratory analyses 7. Study Interpretation 2. Observational Study Design Raymond Hoffmann and Hyun Ja Lim, Medical College of Wisconsin 1. Introduction 2. Cohort Studies 3. Prospective Cohort Studies and Retrospective Cohort Studies 4. Case-Control Studies 4.1 Odds Ratios 4.2 Choice of Controls 4.2 Case-Control Genetic Association Studies 4.3 Matching and Case-Control Studies 4.4 Biases in Case-Control Studies 4.5 Cross-Sectional Studies 5. Outcomes 6. More on Odds Ratios and Relative Risks 6.1 Relative Risks 6.2 Odds Ratios 7. Summary 3. Descriptive Statistics Todd Nick, Cincinnati Children's Hospital 1. Types of Data 2. Measures of location and spread 3. Normal distribution 4. Distribution of a mean 5. Distribution of a variance (including degrees of freedom) 6. Distribution of a proportion 4. Basic Principles of Statistical Inference Wanzhu Tu, Indiana University School of Medicine 1. Introduction 2. Parameter Estimation 2.1 Point Estimation 2.2 Confidence Interval Estimation 2.2.1 Large Sample Confidence Interval for the Mean 2.2.2 Student t-distribution 2.2.3 Small Sample Confidence Interval for the Mean 2.2.4 Simultaneous Inference: Bonferroni's Multiplicity Adjustment 2.2.5 Confidence Interval for the Variance 2.2.6 One-Sided Confidence Intervals 3. Hypothesis Testing 3.1 Understanding Hypothesis Testing 3.2 One sample t test 3.3 An alternaive Decision Rule: P-value 3.4 Errors, Power, and Sample Size 3.5 Statistical Significance and Practical Significance 5. Statistical Inference on Categorical Variables Susan Perkins, Indiana University School of Medicine 1. Introduction 1.1 What is Categorical Data? 1.2 Categorical Data Distributions 1.3 General Notation 1.4 Statistical Analysis Using Categorical Data 2. The Binomial Distribution and the Normal Approximation to the Binomial Distribution 2.1 The Binomial Experiment 2.2 The Binomial Distribution 2.3 The Normal Approximation to the Binomial 3. Estimation and Testing of Single Proportions/Two Proportions 3.1 Estimation of a Single Proportion or the Difference Between Two Proportions 3.2 Hypothesis Testing with a Single Proportion or the Difference Between Two Proportions 3.3 Assumptions 4. Tests of Association 4.1 2x2 Tables 4.2 RxC Tables 4.3 Relationship Between Tests of Independence and Homogeneity 4.4 Fisher's Exact Test 5. McNemar's Test 6. Sample Size Estimation 7. Discussion 6. Development and Evaluation of Classifiers Todd A. Alonzo, University of Southern California, and Margaret Sullivan Pepe, Fred Hutchinson Cancer Research Center and University of Washington 1. Introduction 2. Measures of Classification Accuracy 2.1 True and False Positive Fractions 2.2 Predictive Values 2.3 Diagnostic Likelihood Ratios 2.4 ROC Curves 2.5 Selecting a Measure of Accuracy 3. Basics of Study Design 3.1 Case-control versus Cohort Designs 3.2 Paired versus Unpaired Designs 3.3 Blinding 3.4 Avoiding Bias 3.5 Factors Affecting Test Performance 4. Estimating Performance from Data 4.1 Single binary test 4.2 Comparison of TPF and FPF for two binary tests 4.2.1 Unpaired

Blurb

Biostatistics can be a language nearly indecipherable to those not trained to speak it.  In Topics in Biostatistics, a broad survey of biostatiscal methods, techniques are illustrated by clear, step-by-step instructions able to be performed with paper, a pencil, and a calculator. With subjects as diverse as descriptive statistics, study design, statistical inference, and linear and logistic regression, this volume invites the reader to better understand the language of statistics to aid in collaborations with biostatisticians or the deciphering of software manuals. Following the format of the highly successful Methods in Molecular Biology™ format, each protocol offers readily reproducible results, and, specifically in this case, provides the reader with a concise introduction to complicated statistical methods.

Comprehensive and enlightening, Topics in Biostatistics is the perfect statistical resource for scientists in all disciplines attempting to comprehend this challenging mathematical field.