Biostatistics : a computing approach /: a computing approach. (2011)
- Record Type:
- Book
- Title:
- Biostatistics : a computing approach /: a computing approach. (2011)
- Main Title:
- Biostatistics : a computing approach
- Further Information:
- Note: Stewart Anderson.
- Other Names:
- Anderson, Stewart, 1955-
- Contents:
- Preface; ; Review of Topics in Probability and Statistics; Introduction to Probability; Conditional Probability; Random Variables; The Uniform distribution; The Normal distribution; The Binomial Distribution; The Poisson Distribution; The Chi–Squared Distribution; Student’s t –distribution; The F-distribution; The Hypergeometric Distribution; The Exponential Distribution; Exercises; ; Use of Simulation Techniques; Introduction; What can we accomplish with simulations?; How to employ a simple simulation strategy; Generation of Pseudorandom Numbers; Generating Discrete and Continuous random variables; Testing Random Number Generators; A Brief Note on the Efficiency of Simulation Algorithms; Exercises; ; The Central Limit Theorem; Introduction; The Strong Law of Large Numbers; The Central Limit Theorem; Summary of the Inferential Properties of the Sample Mean; Appendix: Program Listings; Exercises; ; Correlation and Regression; Introduction; Pearson’s Correlation Coefficient; Simple Linear Regression; Multiple Regression; Visualization of Data; Model Assessment and Related Topics; Polynomial Regression; Smoothing Techniques; Appendix: A Short Tutorial in Matrix Algebra; Exercises; ; Analysis of Variance; Introduction; One–Way Analysis of Variance; General Contrast; Multiple Comparisons Procedures; Gabriel’s method; Dunnett’s Procedure; Two-Way Analysis of Variance: Factorial Design; Two-Way Analysis of Variance: Randomized Complete Blocks; Analysis of Covariance; Exercises; ;Preface; ; Review of Topics in Probability and Statistics; Introduction to Probability; Conditional Probability; Random Variables; The Uniform distribution; The Normal distribution; The Binomial Distribution; The Poisson Distribution; The Chi–Squared Distribution; Student’s t –distribution; The F-distribution; The Hypergeometric Distribution; The Exponential Distribution; Exercises; ; Use of Simulation Techniques; Introduction; What can we accomplish with simulations?; How to employ a simple simulation strategy; Generation of Pseudorandom Numbers; Generating Discrete and Continuous random variables; Testing Random Number Generators; A Brief Note on the Efficiency of Simulation Algorithms; Exercises; ; The Central Limit Theorem; Introduction; The Strong Law of Large Numbers; The Central Limit Theorem; Summary of the Inferential Properties of the Sample Mean; Appendix: Program Listings; Exercises; ; Correlation and Regression; Introduction; Pearson’s Correlation Coefficient; Simple Linear Regression; Multiple Regression; Visualization of Data; Model Assessment and Related Topics; Polynomial Regression; Smoothing Techniques; Appendix: A Short Tutorial in Matrix Algebra; Exercises; ; Analysis of Variance; Introduction; One–Way Analysis of Variance; General Contrast; Multiple Comparisons Procedures; Gabriel’s method; Dunnett’s Procedure; Two-Way Analysis of Variance: Factorial Design; Two-Way Analysis of Variance: Randomized Complete Blocks; Analysis of Covariance; Exercises; ; DiscreteMeasures of Risk; Introduction; Odds Ratio (OR) and Relative Risk (RR); Calculating risk in the presence of confounding; Logistic Regression; Using SAS and R for Logistic Regression; Comparison of Proportions for Paired Data; Exercises; ; Multivariate Analysis; The Multivariate Normal Distribution; One and Two Sample Multivariate Inference; Multivariate Analysis of Variance; Multivariate Regression Analysis; Classification Methods; Exercises; ; Analysis of Repeated Measures Data; Introduction; Plotting Repeated Measures Data; Univariate Approaches for the Analysis of Repeated Measures Data; Covariance Pattern Models; Multivariate Approaches; Modern Approaches for the Analysis of Repeated Measures Data; Analysis of Incomplete Repeated Measures Data; Exercises; ; NonparametricMethods; Introduction; Comparing Paired Distributions; Comparing Two Independent Distributions; Kruskal–Wallis Test; Spearman’s rho; The Bootstrap; Exercises; ; Analysis of Time to Event Data; Incidence Density (ID); Introduction to Survival Analysis; Estimation of the Survival Curve; Estimating the Hazard Function; Comparing Survival in Two Groups; Cox Proportional Hazards Model; Cumulative Incidence; Exercises; ; Sample size and power calculations; Sample sizes and power for tests of normally distributed data; Sample size and power for Repeated Measures Data; Sample size and power for survival analysis; Constructing Power Curves; Exercises; ; Appendix A: Using SAS; Introduction; Data input in SAS; Some Graphical Procdures: PROC PLOT and PROC CHART; Some Simple Data Analysis Procedures; Diagnosing errors in SAS programs; Exercises; ; Appendix B: Using R; Introduction; Getting started; Input/Output; Some Simple Data Analysis Procedures; Using R for plots; Comparing an R–session to a SAS session; Diagnosing problems in R programs; Exercises; ; References; ; Index ; … (more)
- Publisher Details:
- Place of publication not identified : Chapman and Hall/CRC
- Publication Date:
- 2011
- Extent:
- 1 online resource, illustrations
- Subjects:
- 570.15195
Biometry -- Computer simulation
Biometry -- Statistical methods
Biometry -- Methodology
Biomathematics - Languages:
- English
- ISBNs:
- 9781439897904
1439897905 - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.143410
- Ingest File:
- 02_029.xml