Regression is one of the most common analyses in statistics. Most of us learn it in grad school, and we learned it in a specific software. Maybe SPSS, maybe another software package. The thing is, depending on your training and when you did it, there is SO MUCH to know about doing a regression analysis in SPSS.
When you draw a graph- either a bar chart, a scatter plot, or even a pie chart, you have the choice of a broad range of colors that you can use. R, for example, has 657 different colors from aliceblue to yellowgreen. SAS has 13 shades of orange, 33 shades of blue, and 47 shades of green. They even have different shades of black.
You have a wealth of colors, but you can’t use all of them in the same graph. The ideal number of colors is 2.
I recently received a great question in a comment about whether the assumptions of normality, constant variance, and independence in linear models are about the errors, εi, or the response variable, Yi.
The asker had a situation where Y, the response, was not normally distributed, but the residuals were.
Quick Answer: It’s just the errors.
In fact, if you look at any (good) statistics textbook on linear models, you’ll see below the model, stating the assumptions: (more…)
A well-fitting regression model results in predicted values close to the observed data values. The mean model, which uses the mean for every predicted value, generally would be used if there were no useful predictor variables. The fit of a proposed regression model should therefore be better than the fit of the mean model. But how do you measure that model fit?
From our first 2 Getting Started with Stata posts, you should be comfortable navigating the windows and menus of Stata. We can now get into the real meat of programming in Stata: do-files.
A do-file is a Stata file that provides a list of commands to run. You can run an entire do-file at once, or you can highlight and run particular lines from the file.
If you set up your do-file correctly, you can just click “run” after opening it. The do-file will set you to the correct directory, open your dataset, do all analyses, and save any graphs or results you want saved.
I’ll start off by saying this: Any analysis you want to run in Stata can be run without a do-file, just using menus and individual commands in the command window. But you still should make a do-file for the following reason:
Reproducibility (more…)
If you have run mixed models much at all, you have undoubtedly been haunted by some version of this very obtuse warning: “The 
Hessian (or G or D) Matrix is not positive definite. Convergence has stopped.”
Or “The Model has not Converged. Parameter Estimates from the last iteration are displayed.”
Let’s start with some background. If you’ve never taken matrix algebra, (more…)