'Odds' presentation slideshows

Categorical Data Analysis

1.81k views • 151 slides

MORE UPWARD AND ALSO MORE DOWNWARD MOBILITY?

MORE UPWARD AND ALSO MORE DOWNWARD MOBILITY? COMPULSORY SCHOOLING IN THE NETHERLANDS DURING THE 20TH CENTURY. Wout Ultee - Radboud Universiteit Nijmegen Presentation in the Department of Sociology, Tel Aviv University February 24, 2005.

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Presenting results from statistical models

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Multinomial Logistic Regression

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Overview

Overview. Odds Pot Odds Outs Probability to Hit an Out Odds Against Hitting Your Hand Implied Odds Reverse Implied Odds Putting It Together. Odds. The odds represent the probability that an event does not occur.

638 views • 42 slides

Logistic Regression III: Advanced topics

Logistic Regression III: Advanced topics. Conditional Logistic Regression for Matched Data. Recall: Matching. Matching can control for extraneous sources of variability and increase the power of a statistical test.

532 views • 40 slides

Logistic regression for binary response variables

Logistic regression for binary response variables. Space shuttle example. n = 24 space shuttle launches prior to Challenger disaster on January 27, 1986 Response y is an indicator variable y = 1 if O-ring failures during launch y = 0 if no O-ring failures during launch

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Logistic Regression

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PH6415 Review Questions

PH6415 Review Questions. Question 1. A journal article reports a 95%CI for the relative risk (RR) of an event (treatment versus control as (0.55, 0.97). What can be said of the p-value associated with testing Ho: RR=1 vs. Ha: RR not equal 1? The p-value is < 0.01. The p-value is < 0.05.

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Please turn off cell phones, pagers, etc. The lecture will begin shortly.

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Sociology 601 Class 13: October 13, 2009

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Pre-Algebra HOMEWORK

Pre-Algebra HOMEWORK. Page 480 #1-12 Turn in for Credit!. Pre-Algebra HOMEWORK. Page 484 #1-6 Due on MONDAY!. 9-8. Odds. Warm Up. Problem of the Day. Lesson Presentation. Pre-Algebra. 9-8. Odds. 5. 87. 7. 29. Pre-Algebra. Warm Up

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Logistic Regression

Logistic Regression. Biostatistics 510 March 15, 2007 Vanessa Perez. Logistic regression. Most important model for categorical response (y i ) data Categorical response with 2 levels ( binary : 0 and 1) Categorical response with ? 3 levels (nominal or ordinal)

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April 6

April 6. Logistic Regression Estimating probability based on logistic model Testing differences among multiple groups Assumptions for model. Logistic regression equation. Model log odds of outcome as a linear function of one or more variables X i = predictors, independent variables

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A Meta-Analysis Primer

Rick Chappell - 641, 12/15/2010. A Meta-Analysis Primer. Outline. I. Definition II. Example 1 - Cervical Carcinoma at UW III. How to Numerically Summarize Evidence IV. Examples of Presentation V. Reasons for Meta-Analysis VI. Problems with Meta-Analysis. I. Definition.

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Analysis of Case Control Studies

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STAT 3120 Statistical Methods I

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Ratios vs Odds

Ratios vs Odds. A Ratio is a fraction. Odds are a type of ratio. Fractions. Ratios 1/4. Odds 1:3. For example, if you go fishing and you catch 3 largemouth bass and 1 trout, The probability (or risk ) of catching a trout is the ratio below:

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Review

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Odds vs. Probabilities

Odds vs. Probabilities. Odds ratio in SPSS (Exp(B)) is an odds rather than a probability Odds = success/failure Probability = Likelihood of success for any one person. Null model Odds Ratio = 26/24 = 1.0833. Specified Model Odds Ratio = 1.7313 (e .549 where e = 2.718).

227 views • 3 slides