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Biostatistics toolbox for data analysis / Steve Selvin.

By: Publication details: New York : Cambridge University Press, 2015.Description: xvii, 560 p. : illustrations ; 27 cmISBN:
  • 9781107113084
Subject(s): DDC classification:
  • 000SB:610 23 Se469
Contents:
1. Statistical distribution; 2. Confidence intervals; 3. A weighted average; 4. Two discrete probability functions; 5. Correlation; 6. The 2 x 2 table; 7. Linear bivariate regression model; 8. The 2 x k table; 9. The log-linear Poisson regression model; 10. Two-way and three-way tables analysis; 11. Bootstrap analysis; 12. Graphical analysis; 13. The variance; 14. The log-normal distribution; 15. Nonparametric analysis; 16. Rates; 17. Nonparametric survival analysis; 18. The Weibull survival function; 19. Prediction, a natural measure of performance; 20. The attributable risk summary; 21. Time/space analysis; 22. ROC curve and analysis; 23. Selection: a statistical description; 24. Mendelian segregation analysis; 25. Admixed populations; 26. Nonrandom mating; 27. Statistical estimation; Appendix.
Summary: This sophisticated package of statistical methods is for advanced master's (MPH) and PhD students in public health and epidemiology who are involved in the analysis of data. It makes the link from statistical theory to data analysis, focusing on the methods and data types most common in public health and related fields. Like most toolboxes, the statistical tools in this book are organized into sections with similar objectives. Unlike most toolboxes, however, these tools are accompanied by complete instructions, explanations, detailed examples, and advice on relevant issues and potential pitfalls - conveying skills, intuition, and experience.
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Includes index.

1. Statistical distribution;
2. Confidence intervals;
3. A weighted average;
4. Two discrete probability functions;
5. Correlation;
6. The 2 x 2 table;
7. Linear bivariate regression model;
8. The 2 x k table;
9. The log-linear Poisson regression model;
10. Two-way and three-way tables analysis;
11. Bootstrap analysis;
12. Graphical analysis;
13. The variance;
14. The log-normal distribution;
15. Nonparametric analysis;
16. Rates;
17. Nonparametric survival analysis;
18. The Weibull survival function;
19. Prediction, a natural measure of performance;
20. The attributable risk summary;
21. Time/space analysis;
22. ROC curve and analysis;
23. Selection: a statistical description;
24. Mendelian segregation analysis;
25. Admixed populations;
26. Nonrandom mating;
27. Statistical estimation;
Appendix.

This sophisticated package of statistical methods is for advanced master's (MPH) and PhD students in public health and epidemiology who are involved in the analysis of data. It makes the link from statistical theory to data analysis, focusing on the methods and data types most common in public health and related fields. Like most toolboxes, the statistical tools in this book are organized into sections with similar objectives. Unlike most toolboxes, however, these tools are accompanied by complete instructions, explanations, detailed examples, and advice on relevant issues and potential pitfalls - conveying skills, intuition, and experience.

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