Interactions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions and they become even more difficult to understand. (more…)
Stage 3
Member Training: Interactions in Poisson and Logistic Regression
May 1st, 2023 by TAF SupportThe Difference Between the Bernoulli and Binomial Distributions
February 8th, 2023 by Kim Love
You might already be familiar with the binomial distribution. It describes the scenario where the result of an observation is binary—it can be one of two outcomes. You might label the outcomes as “success” and “failure” (or not!). (more…)
Member Training: Translating Between Multilevel and Mixed Models
October 31st, 2022 by TAF SupportMultilevel and Mixed models are essentially the same analysis. But they use different vocabulary, different notation, and approach the analysis considerations in different ways.
(more…)
Member Training: Analyzing Likert Scale Data
August 31st, 2022 by TAF SupportIs it really ok to treat Likert items as continuous? 
And can you just decide to combine Likert items to make a scale? Likert-type data is extremely common—and so are questions like these about how to analyze it appropriately. (more…)
Member Training: A Gentle Introduction to Bootstrapping
July 28th, 2022 by TAF SupportBootstrapping is a methodology derived by Bradley Efron in the 1980s that provides a reasonable approximation to the sampling distribution of various “difficult” statistics. Difficult statistics are those where there is no mathematical theory to establish a distribution.
When Linear Models Don’t Fit Your Data, Now What?
June 20th, 2022 by Karen Grace-MartinWhen your dependent variable is not continuous, unbounded, and measured on an interval or ratio scale, linear models don’t fit. The data just will not meet the assumptions of linear models. But there’s good news, other models exist for many types of dependent variables.
Today I’m going to go into more detail about 6 common types of dependent variables that are either discrete, bounded, or measured on a nominal or ordinal scale and the tests that work for them instead. Some are all of these.