SAS

Specifying Fixed and Random Factors in Mixed Models

January 10th, 2022 by

One of the difficult decisions in mixed modeling is deciding which factors are fixed and which are random. And as difficult as it is, it’s also very important. Correctly specifying the fixed and random factors of the model is vital to obtain accurate analyses.

Now, you may be thinking of the fixed and random effects in the model, rather than the factors themselves, as fixed or random. If so, remember that each term in the model (factor, covariate, interaction or other multiplicative term) has an effect. We’ll come back to how the model measures the effects for fixed and random factors.

Sadly, the definitions in many texts don’t help much with decisions to specify factors as fixed or random. Textbook examples are often artificial and hard to apply to the real, messy data you’re working with.

Here’s the real kicker. The same factor can often be fixed or random, depending on the researcher’s objective. (more…)


Multiple Imputation in a Nutshell

September 20th, 2021 by

Imputation as an approach to missing data has been around for decades.

You probably learned about mean imputation in methods classes, only to be told to never do it for a variety of very good reasons. Mean imputation, in which each missing value is replaced, or imputed, with the mean of observed values of that variable, is not the only type of imputation, however. (more…)


Statistical Software Access From Home

March 30th, 2020 by

Of all the stressors you’ve got right now, accessing your statistical software from home shouldn’t be one of them. (You know, the one on your office computer).

We’ve gotten some updates from some statistical software companies on how they’re making it easier to access the software you have a license to or to extend a free trial while you’re working from home.

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Member Training: What’s the Best Statistical Package for You?

February 1st, 2019 by

Choosing statistical software is part of The Fundamentals of Statistical Skill and is necessary to learning a second software (something we recommend to anyone progressing from Stage 2 to Stage 3 and beyond).

You have many choices for software to analyze your data: R, SAS, SPSS, and Stata, among others. They are all quite good, but each has its own unique strengths and weaknesses.

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The Secret to Importing Excel Spreadsheets into SAS

January 21st, 2019 by

My poor colleague was pulling her hair out in frustration today.

You know when you’re trying to do something quickly, and it’s supposed to be easy, only it’s not? And you try every solution you can think of and it still doesn’t work?

And even in the great age of the Internet, which is supposed to know all the things you don’t, you still can’t find the answer anywhere?

Cue hair-pulling.

Here’s what happened: She was trying to import an Excel spreadsheet into SAS, and it didn’t work.

Instead she got:

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Tricks for Using Word to Make Statistical Syntax Easier

March 13th, 2017 by

We’ve talked a lot around here about the reasons to use syntax — not only menus — in your statistical analyses.

Regardless of which software you use, the syntax file is pretty much always a text file. This is true for R, SPSS, SAS, Stata — just about all of them.

This is important because it means you can use an unlikely tool to help you code: Microsoft Word.

I know what you’re thinking. Word? Really?

Yep, it’s true. Essentially it’s because Word has much better Search-and-Replace options than your stat software’s editor.

Here are a couple features of Word’s search-and-replace that I use to help me code faster:

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