Stage 3

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.

The Difference Between an Odds Ratio and a Predicted Odds

by Karen Grace-Martin Leave a Comment

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

by TAF Support

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

by Karen Grace-Martin 3 Comments

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

Odds Ratio: Standardized or Unstandardized Effect Size?

by Karen Grace-Martin Leave a Comment

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?

Member Training: Matrix Algebra for Data Analysts: A Primer

by Karen Grace-Martin 4 Comments

If you’ve been doing data analysis for very long, you’ve certainly come across terms, concepts, and processes of matrix algebra. Not just matrices, but:

Matrix addition and multiplication
Traces and determinants
Eigenvalues and Eigenvectors
Inverting and transposing
Positive and negative definite