Karen Grace-Martin

Do Top Journals Require Reporting on Missing Data Techniques?

June 3rd, 2011 by

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…)


Is Multiple Imputation Possible in the Context of Survival Analysis?

May 27th, 2011 by

Sure.  One of the big advantages of multiple imputation is that you can use it for any analysis.

It’s one of the reasons big data libraries use it–no matter how researchers are using the data, the missing data is handled the same, and handled well.

I say this with two caveats. (more…)


Using Case Summaries in SPSS to Debug your Variable Creation

April 1st, 2011 by

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…)


Recoding Variables in SPSS Menus and Syntax

March 11th, 2011 by

SPSS offers two choices under the recode command: Into Same Variable and Into Different Variables.

The command Into Same Variable replaces existing data with new values, but the command Into Different Variables adds a new variable to the data set.

In almost every situation, you want to use Into Different Variables. Recoding Into Same Variables replaces the values in the existing variable.

So if you notice a mistake after you’ve recoded, you can’t fix it.

But you may not even notice the mistake, because you can’t even test it.

And that’s just dangerous. (more…)


Approaches to Repeated Measures Data: Repeated Measures ANOVA, Marginal, and Mixed Models

March 8th, 2011 by

There are three main ways you can approach analyzing repeated measures data, assuming the dependent variable is measured stage-3continuously: repeated measures ANOVA, Mixed Models, and Marginal Models. Let’s take a look at how the three approaches differ and some of their advantages and disadvantages.

For a few, very specific designs, you can get the exact same results from all three approaches.  This makes it difficult to figure out what each one is doing, and how to apply them to OTHER designs.

For the sake of the current discussion, I will define repeated measures data as repeated measurements of the same outcome variable on the same individual.  The individual is often a person, but could just as easily be a plant, animal, colony, company, etc.  For simplicity, I’ll use “individual.” (more…)


Mixed Models for Logistic Regression in SPSS

February 25th, 2011 by

Can I use SPSS MIXED models for (a) ordinal logistic regression, and (b) multi-nomial logistic regression?

Every once in a while I get emailed a question that I think others will find helpful.  This is definitely one of them.

My answer:

No.

(And by the way, this is all true in SAS as well.  I’ll include the SAS versions in parentheses). (more…)