multivariate analysis

How to Interpret the Width of a Confidence Interval

One issue with using tests of significance is that black and white cut-off points such as 5 percent or 1 percent may be difficult to justify.

Significance tests on their own do not provide much light about the nature or magnitude of any effect to which they apply.

One way of shedding more light on those issues is to use confidence intervals. Confidence intervals can be used in univariate, bivariate and multivariate analyses and meta-analytic studies.

Member Training: Matrix Algebra for Data Analysts: A Primer

by Karen Grace-Martin Leave a Comment

If you’ve been doing data analysis for very long, you’ve certainly come across terms, concepts, and processes of matrix algebra. Not just matrices, but:

Matrix addition and multiplication
Traces and determinants
Eigenvalues and Eigenvectors
Inverting and transposing
Positive and negative definite

Member Training: Cluster Analysis–Hierarchical and KMeans

by Karen Grace-Martin Leave a Comment

Cluster analysis classifies individuals into two or more unknown groups based on a set of numerical variables.

It is related to, but distinct from, a few other multivariate techniques including discriminant Function Analysis, [Read more…] about Member Training: Cluster Analysis–Hierarchical and KMeans

Multiple Regression Model: Univariate or Multivariate GLM?

by Karen Grace-Martin 22 Comments

I would love to promise that the reason there is so much confusing terminology in statistics is NOT because statisticians like to laugh at hapless users of statistics as they try to figure out already confusing concepts. See my post on the different meanings of the term “level” in statistics. (There are other examples–how many different meanings does “beta” have in statistics? I can think of three off the top of my head. That will have to be another post).

But today I talk about the difference between multivariate and multiple, as they relate to regression.

A regression analysis with one dependent variable and 8 independent variables is NOT a multivariate regression. It’s a multiple regression. Multivariate analysis ALWAYS refers to the dependent variable.

So when you’re in SPSS, choose univariate GLM for this model, not multivariate.

I know what you’re thinking–but what about multivariate analyses like cluster analysis and factor analysis, where there is no dependent variable, per se?

Well, I respond, it’s not really about dependency. It’s about which variable’s variance is being analyzed. A regression model is really about the dependent variable. We’re just using the predictors to model the mean and the variation in the dependent variable.

Note: this is actually a situation where the subtle differences in what we call that Y variable can help. Calling it the outcome or response variable, rather than dependent, is more applicable to something like factor analysis.

So when to choose multivariate GLM? When you’re jointly modeling the variation in multiple response variables.