MARC details
| 000 -LEADER |
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05314nam a2200313 a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
17102994 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20210317120525.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
120103s2012 flua b 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
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| LC control number |
2011050403 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781584888345 (hbk. : alk. paper) |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
DLC |
| Transcribing agency |
DLC |
| Modifying agency |
DLC |
| -- |
EG-CaNU |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
570.15195 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Anderson, Stewart, |
| Dates associated with a name |
1955- |
| 245 10 - TITLE STATEMENT |
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| Title |
Biostatistics : |
| Remainder of title |
a computing approach / |
| Statement of responsibility, etc. |
Stewart Anderson. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Boca Raton : |
| Name of publisher, distributor, etc. |
CRC Press, |
| Date of publication, distribution, etc. |
2012. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xx, 306 p. : |
| Other physical details |
ill. ; |
| Dimensions |
25 cm. |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Chapman & Hall/CRC biostatistics series |
| 9 (RLIN) |
450 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographical references (p. 293-301) and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Review of Topics in Probability and Statistics<br/>Introduction to Probability<br/>Conditional Probability<br/>Random Variables<br/>The Uniform distribution<br/>The Normal distribution<br/>The Binomial Distribution<br/>The Poisson Distribution<br/>The Chi–Squared Distribution<br/>Student’s t–distribution<br/>The F-distribution<br/>The Hypergeometric Distribution<br/>The Exponential Distribution<br/>Exercises<br/><br/>Use of Simulation Techniques<br/>Introduction<br/>What can we accomplish with simulations?<br/>How to employ a simple simulation strategy<br/>Generation of Pseudorandom Numbers<br/>Generating Discrete and Continuous random variables<br/>Testing Random Number Generators<br/>A Brief Note on the Efficiency of Simulation Algorithms<br/>Exercises<br/><br/>The Central Limit Theorem<br/>Introduction<br/>The Strong Law of Large Numbers<br/>The Central Limit Theorem<br/>Summary of the Inferential Properties of the Sample Mean<br/>Appendix: Program Listings<br/>Exercises<br/><br/>Correlation and Regression<br/>Introduction<br/>Pearson’s Correlation Coefficient<br/>Simple Linear Regression<br/>Multiple Regression<br/>Visualization of Data<br/>Model Assessment and Related Topics<br/>Polynomial Regression<br/>Smoothing Techniques<br/>Appendix: A Short Tutorial in Matrix Algebra<br/>Exercises<br/><br/>Analysis of Variance<br/>Introduction<br/>One–Way Analysis of Variance<br/>General Contrast<br/>Multiple Comparisons Procedures<br/>Gabriel’s method<br/>Dunnett’s Procedure<br/>Two-Way Analysis of Variance: Factorial Design<br/>Two-Way Analysis of Variance: Randomized Complete Blocks<br/>Analysis of Covariance<br/>Exercises<br/><br/>DiscreteMeasures of Risk<br/>Introduction<br/>Odds Ratio (OR) and Relative Risk (RR)<br/>Calculating risk in the presence of confounding<br/>Logistic Regression<br/>Using SAS and R for Logistic Regression<br/>Comparison of Proportions for Paired Data<br/>Exercises<br/><br/>Multivariate Analysis<br/>The Multivariate Normal Distribution<br/>One and Two Sample Multivariate Inference<br/>Multivariate Analysis of Variance<br/>Multivariate Regression Analysis<br/>Classification Methods<br/>Exercises<br/><br/>Analysis of Repeated Measures Data<br/>Introduction<br/>Plotting Repeated Measures Data<br/>Univariate Approaches for the Analysis of Repeated Measures Data<br/>Covariance Pattern Models<br/>Multivariate Approaches<br/>Modern Approaches for the Analysis of Repeated Measures Data<br/>Analysis of Incomplete Repeated Measures Data<br/>Exercises<br/><br/>NonparametricMethods<br/>Introduction<br/>Comparing Paired Distributions<br/>Comparing Two Independent Distributions<br/>Kruskal–Wallis Test<br/>Spearman’s rho<br/>The Bootstrap<br/>Exercises<br/><br/>Analysis of Time to Event Data<br/>Incidence Density (ID)<br/>Introduction to Survival Analysis<br/>Estimation of the Survival Curve<br/>Estimating the Hazard Function<br/>Comparing Survival in Two Groups<br/>Cox Proportional Hazards Model<br/>Cumulative Incidence<br/>Exercises<br/><br/>Sample size and power calculations<br/>Sample sizes and power for tests of normally distributed data<br/>Sample size and power for Repeated Measures Data<br/>Sample size and power for survival analysis<br/>Constructing Power Curves<br/>Exercises |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25 years, broadening the landscape of available tools in statistical investigations of complex data. Biostatistics: A Computing Approach focuses on visualization and computational approaches associated with both modern and classical techniques. Furthermore, it promotes computing as a tool for performing both analyses and simulations that can facilitate such understanding.<br/><br/>As a practical matter, programs in R and SAS are presented throughout the text. In addition to these programs, appendices describing the basic use of SAS and R are provided. Teaching by example, this book emphasizes the importance of simulation and numerical exploration in a modern-day statistical investigation. A few statistical methods that can be implemented with simple calculations are also worked into the text to build insight about how the methods really work.<br/><br/>Suitable for students who have an interest in the application of statistical methods but do not necessarily intend to become statisticians, this book has been developed from Introduction to Biostatistics II, which the author taught for more than a decade at the University of Pittsburgh. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Biometry |
| General subdivision |
Computer simulation. |
| 9 (RLIN) |
451 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Biostatistics |
| 9 (RLIN) |
428 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Biometry |
| General subdivision |
Statistical methods. |
| 9 (RLIN) |
452 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Biometry |
| General subdivision |
Methodology. |
| 9 (RLIN) |
453 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Biomathematics. |
| 9 (RLIN) |
454 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| Link text |
https://www.routledge.com/Biostatistics-A-Computing-Approach/Anderson/p/book/9781584888345 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |