One of the tricky parts about dummy coded (0/1) variables is keeping track of what’s a 0 and what’s a 1.
This is made particularly tricky because sometimes your software switches them on you.
Here’s one example in a question I received recently. The context was a Linear Mixed Model, but this can happen in other procedures as well.
I dummy code my categorical variables “0” or “1” but for some reason in the (more…)
Model Building–choosing predictors–is one of those skills in statistics that is difficult to teach. It’s hard to lay out the steps, because at each step, you have to evaluate the situation and make decisions on the next step.
If you’re running purely predictive models, and the relationships among the variables aren’t the focus, it’s much easier. Go ahead and run a stepwise regression model. Let the data give you the best prediction.
But if the point is to answer a research question that describes relationships, you’re going to have to get your hands dirty.
It’s easy to say “use theory” or “test your research question” but that ignores a lot of practical issues. Like the fact that you may have 10 different variables that all measure the same theoretical construct, and it’s not clear which one to use. (more…)
Q: Do most high impact journals require authors to state which method has been used on missing data?
I don’t usually get far enough in the publishing process to read journal requirements.
But based on my conversations with researchers who both review articles for journals and who deal with reviewers’ comments, I can offer this response.
I would be shocked if journal editors at top journals didn’t want information about the missing data technique. If you leave it out, they’ll either assume you didn’t have missing data or are using defaults like listwise deletion. (more…)
Here’s a little SPSS tip.
When you create new variables, whether it’s through the Recode, Compute, or some other command, you need to check that it worked the way you think it did.
(As an aside, I hope this goes without saying, but never, never, never, never use Recode into Same Variable. Always Recode into Different Variable so you don’t overwrite your data and then discover you made a mistake. Or worse, not discover. It happens).
And the easiest way to do that is to simply look at the data. (more…)
You have probably noticed I’m not much into R (though I’m slowly coming around to it). It goes back to when I was in my graduate statistics program, where we were required to use SPlus (R’s parent language—as far as I can tell, it’s the same thing, but with customer support).
We were given a half hour tutorial and an incomprehensible text, and sent off to figure it out how to use SPlus on graduate level stats.
Not fun.
And since I was already fluent in SAS, SPSS, and BMDP (may it rest in peace), I resisted SPlus. A lot.
I actually wish R had been around, (more…)
by Annette Gerritsen, Ph.D.
In an earlier article I discussed how to do a cross-tabulation in SPSS. But what if you do not have a data set with the values of the two variables of interest?
For example, if you do a critical appraisal of a published study and only have proportions and denominators.
In this article it will be demonstrated how SPSS can come up with a cross table and do a Chi-square test in both situations. And you will see that the results are exactly the same.
If you want to test if there is an association between two nominal variables, you do a Chi-square test.
In SPSS you just indicate that one variable (the independent one) should come in the row, (more…)