One issue in data analysis that feels like it should be obvious, but often isn't, is setting up your data. The kinds of issues involved ... Continue Reading
One issue in data analysis that feels like it should be obvious, but often isn't, is setting up your data. The kinds of issues involved ... Continue Reading
What is the difference between Clustered, Longitudinal, and Repeated Measures Data? You can use mixed models to analyze all of them. But the issues ... Continue Reading
Some repeated measures designs make it quite challenging to specify within-subjects factors. Especially difficult is when the design contains two ... Continue Reading
Repeated measures is one of those terms in statistics that sounds like it could apply to many design situations. In fact, it describes only one. A ... Continue Reading
As mixed models are becoming more widespread, there is a lot of confusion about when to use these more flexible but complicated models and when to use ... Continue Reading
Lately, I've gotten a lot of questions about learning how to run models for repeated measures data that isn't continuous. Mostly categorical. But ... Continue Reading
I have recently worked with two clients who were running generalized linear mixed models in SPSS. Both had repeated measures experiments with a ... Continue Reading
Repeated measures ANOVA is the approach most of us learned in stats classes for repeated measures and longitudinal data. It works very well in certain ... Continue Reading
One area in statistics where I see conflicting advice is how to analyze pre-post data. I've seen this myself in consulting. A few years ago, I ... Continue Reading
"Because mixed models are more complex and more flexible than the general linear model, the potential for confusion and errors is higher." - Hamer ... Continue Reading
There are three main ways you can approach analyzing repeated measures data, assuming the dependent variable is measured continuously: repeated ... Continue Reading
There are two ways to run a repeated measures analysis.The traditional way is to treat it as a multivariate test--each response is considered a ... Continue Reading
If you are new to using generalized linear mixed effects models, or if you have heard of them but never used them, you might be wondering about the ... Continue Reading
In the past few months, I've gotten the same question from a few clients about using linear mixed models for repeated measures data. They want to ... Continue Reading
You may have heard of McNemar tests as a repeated measures version of a chi-square test of independence. This is basically true, and I wanted to show ... Continue Reading
If you've ever worked with multilevel models, you know that they are an extension of linear models. For a researcher learning them, this is both good ... Continue Reading
If you learned much about calculating power or sample sizes in your statistics classes, chances are, it was on something very, very simple, like a ... Continue Reading
One of those tricky, but necessary, concepts in statistics is the difference between crossed and nested factors. As a reminder, a factor is any ... Continue Reading
Interactions in statistical models are never especially easy to interpret. Throw in non-normal outcome variables and non-linear prediction functions ... Continue Reading
Are you learning Multilevel Models? Do you feel ready? Or in over your head? It's a very common analysis to need to use. I have to say, learning it ... Continue Reading
statistical consulting Sometimes you need one-on-one intensive guidance. With ... Continue Reading
Hourly Statistical Consulting For when you need guidance and advice for a statistical plan or analysis. Perfect if you have: a need for help to ... Continue Reading
Currently Enrolling Interpreting (Even Tricky) Regression Coefficients Instructor: Karen Grace-Martin Stage: 2, Linear ... Continue Reading
Resources to improve your data analysis practice and skills As a data analyst, it's not enough to understand statistics or to be able to use the ... Continue Reading
learn R The statistical programming language R is becoming a popular means for analyzing data. But it’s not always easy to use. We have a number of ... Continue Reading
logistic regression resources Listed below are workshops, trainings, and articles to help you learn logistic regression. Logistic regression is an ... Continue Reading
mixed and multilevel models resources Listed below are workshops, trainings, and articles to help you learn Mixed, Hierarchical, and Multilevel ... Continue Reading
analysis of variance and covariance resources Listed below are workshops, trainings, and articles to help you learn Analysis of Variance (ANOVA) and ... Continue Reading
missing data resources I don't need to tell you, missing data stinks. And frankly, it's in just about every data set. These days, though, there are ... Continue Reading