'Log odds ratio' presentation slideshows

CSE 5290: Algorithms for Bioinformatics Fall 2011

CSE 5290: Algorithms for Bioinformatics Fall 2011. Suprakash D at ta datta@cse.yorku.ca Office: CSEB 3043 Phone: 416-736-2100 ext 77875 Course page: http://www.cse.yorku.ca/course/5290. Next. Markov chains and hidden Markov models

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CSE 5290: Algorithms for Bioinformatics Fall 2009

CSE 5290: Algorithms for Bioinformatics Fall 2009. Suprakash D at ta datta@cs.yorku.ca Office: CSEB 3043 Phone: 416-736-2100 ext 77875 Course page: http://www.cs.yorku.ca/course/5290. Next. Markov chains and hidden Markov models

475 views • 47 slides

Final Review

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Final Review

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Chapter 13

Chapter 13. Design and Analysis Techniques for Epidemiologic Studies. Learning Objectives. Define study designs Measures of effects for categorical data Confounders and effects modifications Stratified analysis (Mantel Haenszel statistic, multiple logistic regression)

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AS 737 Categorical Data Analysis For Multivariate

AS 737 Categorical Data Analysis For Multivariate. Week 2. The Data (var00002). Binomial Test. The Result. Using SPSS. But how is it calculated?. How To Calculate the P-value. Binomial Table Made in Excel with n=20 and p=0.70.

469 views • 28 slides

EVAL 6970: Meta-Analysis Effect Sizes and Precision: Part II

EVAL 6970: Meta-Analysis Effect Sizes and Precision: Part II. Dr. Chris L. S. Coryn Kristin A. Hobson Fall 2013. Agenda. Effect sizes based on binary data Effect sizes based on correlations Converting among effect sizes Precision Review questions In-class activity. Risk Ratios.

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0.5

Funnel plot of effect size versus odds ratio (log scale). The dotted lines represent pseudo 95% confidence limits. 0. 0.5. Standard error of log odds ratio. 1.0. 1.5. 1. 2. 3. 4. 5. 10. 20. 30. 40. 5 0. Odds ratio.

134 views • 1 slides