When interpreting the results of a regression model, the first step is to look at the regression coefficients. Each term in the model has one. And each one describes the average difference in the value of Y for a one-unit difference in the value of the predictor variable, X, that makes up that term. It’s the effect size statistic for that term in the model.
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odds ratio
The Difference Between an Odds Ratio and a Predicted Odds
May 20th, 2022 by Karen Grace-MartinLogistic Regression Analysis: Understanding Odds and Probability
November 22nd, 2021 by Karen Grace-MartinUpdated 11/22/2021
Probability and odds measure the same thing: the likelihood or propensity or possibility of a specific outcome.
People use the terms odds and probability interchangeably in casual usage, but that is unfortunate. It just creates confusion because they are not equivalent.
How Odds and Probability Differ
They measure the same thing on different scales. Imagine how confusing it would be if people used degrees Celsius and degrees Fahrenheit interchangeably. “It’s going to be 35 degrees today” could really make you dress the wrong way.
In measuring the likelihood of any outcome, we need to know (more…)
Odds Ratio: Standardized or Unstandardized Effect Size?
September 7th, 2021 by Karen Grace-MartinEffect size statistics are extremely important for interpreting statistical results. The emphasis on reporting them has been a great development over the past decade. (more…)
Effect Size Statistics: How to Calculate the Odds Ratio from a Chi-Square Cross-tabulation Table
August 12th, 2020 by Karen Grace-MartinLest you believe that odds ratios are merely the domain of logistic regression, I’m here to tell you it’s not true.
One of the simplest ways to calculate an odds ratio is from a cross tabulation table.
We usually analyze these tables with a categorical statistical test. There are a few options, depending on the sample size and the design, but common ones are Chi-Square test of independence or homogeneity, or a Fisher’s exact test.
Member Training: Those Darn Ratios!
December 1st, 2018 by TAF SupportRatios are everywhere in statistics—coefficient of variation, hazard ratio, odds ratio, the list goes on. You see them reported in the literature and in your output.
You comment on them in your reports. You even (kinda) understand them. Or, maybe, not quite?
Please join Elaine Eisenbeisz as she presents an overview of the how and why of various ratios we use often in statistical practice.
The Difference Between Relative Risk and Odds Ratios
July 11th, 2016 by Audrey SchnellRelative Risk and Odds Ratios are often confused despite being unique concepts. Why?
Well, both measure association between a binary outcome variable and a continuous or binary predictor variable. (more…)