Effect size statistics are extremely important for interpreting statistical results. The emphasis on reporting them has been a great development over the past decade. [Read more…] about Odds Ratio: Standardized or Unstandardized Effect Size?
Lest you believe that odds ratios are merely the domain of logistic regression, I’m here to tell you it’s not true.
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.
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.
by Audrey Schnell
Odds Ratios and Relative Risks are often confused despite being unique concepts. Why?
Well, both measure association between a binary outcome variable and a continuous or binary predictor variable. [Read more…] about The Difference Between Relative Risk and Odds Ratios
Effect size statistics are expected by many journal editors these days.
If you’re running an ANOVA, t-test, or linear regression model, it’s pretty straightforward which ones to report.
Things get trickier, though, once you venture into other types of models.
[Read more...] about Effect Size Statistics in Logistic Regression
A number of years ago when I was still working in the consulting office at Cornell, someone came in asking for help interpreting their ordinal logistic regression results.
The client was surprised because all the coefficients were backwards from what they expected, and they wanted to make sure they were interpreting them correctly.
It looked like the researcher had done everything correctly, but the results were definitely bizarre. They were using SPSS and the manual wasn’t clarifying anything for me, so I did the logical thing: I ran it in another software program. I wanted to make sure the problem was with interpretation, and not in some strange default or [Read more…] about Opposite Results in Ordinal Logistic Regression—Solving a Statistical Mystery