Is 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. [Read more…] about Member Training: Analyzing Likert Scale Data

# Stage 3

## Member Training: A Gentle Introduction to Bootstrapping

Bootstrapping 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.

[Read more…] about Member Training: A Gentle Introduction to Bootstrapping

## When Linear Models Don’t Fit Your Data, Now What?

When 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.

[Read more…] about When Linear Models Don’t Fit Your Data, Now What?

## The Difference Between an Odds Ratio and a Predicted Odds

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. [Read more…] about The Difference Between an Odds Ratio and a Predicted Odds

## Member Training: Heterogeneity in Meta-analysis

Meta-analysis allows us to synthesize the results of separate studies. The goal is to assess the mean effect size and also heterogeneity – how much the effect size varies across studies. [Read more…] about Member Training: Heterogeneity in Meta-analysis

## Logistic Regression Analysis: Understanding Odds and Probability

*Updated 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 [Read more…] about Logistic Regression Analysis: Understanding Odds and Probability