Binary logistic regression is one of the most useful regression models. It allows you to predict, classify, or understand explanatory relationships between a set of predictors and a binary outcome.
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Member Training: Introduction to Binary Logistic Regression
December 3rd, 2024 by TAF Support
When to Report Separate Group or a Pooled Mean
November 12th, 2024 by guest contributer
Have you ever wondered whether you should report separate means for different groups or a pooled mean from the entire sample? This is a common scenario that comes up, for instance in deciding whether to separate by sex, region, observed treatment, et cetera.
Member Training: Types of Longitudinal, Repeated Measures, and Time Series
October 2nd, 2024 by TAF Support
How do you know when to use a time series and when to use a linear mixed model for longitudinal data?
What’s the difference between repeated measures data and longitudinal?
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Getting Started with Stata Tutorial #6: How Stata Code Works
July 18th, 2024 by guest contributer
If you’ve tried coding in Stata, you may have found it strange. The syntax rules are straightforward, but different from what I’d expect.
I had experience coding in Java and R before I ever used Stata. Because of this, I expected commands to be followed by parentheses, and for this to make it easy to read the code’s structure.
Stata does not work this way.
An Example of how Stata Code Works
To see the way Stata handles a linear regression, go to the command line and type
h reg or help regress
You will see a help page pop up, with this Syntax line near the top.
(If you need a refresher on getting help in Stata, watch this video by Jeff Meyer.)
This is typical of how Stata code looks. (more…)
The Difference between Standard Deviation and Standard Error
November 10th, 2023 by Karen Grace-Martin
Standard deviation and standard error are statistical concepts you probably learned well enough in Intro Stats to pass the test. Conceptually, you understand them, yet the difference doesn’t make a whole lot of intuitive sense.
So in this article, let’s explore the difference between the two. We will look at an example, in the hopes of making these concepts more intuitive. You’ll also see why sample size has a big effect on standard error. (more…)
Issues in Coding Missing Values
October 11th, 2023 by guest contributer
There’s no mincing words here. Missing values can cause problems for every statistician. That’s true for a lot of reasons, but it can start with simple issues of choices 
made when coding missing values in a data set. Here are a few examples.
Example 1: The Null License Plate
Researcher Joseph Tartaro thought it would be funny to get the following California vanity license plate: (more…)