One approach to model building is to use all predictors that make theoretical sense in the first model. For example, a first model for determining ... Continue Reading
One approach to model building is to use all predictors that make theoretical sense in the first model. For example, a first model for determining ... Continue Reading
There is a bit of art and experience to model building. You need to build a model to answer your research question but how do you build a statistical ... Continue Reading
Suppose you are asked to create a model that will predict who will drop out of a program your organization offers. You decide to use a binary logistic ... Continue Reading
How should I build my model? I get this question a lot, and it's difficult to answer at first glance--it depends too much on your particular ... Continue Reading
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 ... Continue Reading
No matter what statistical model you're running, you need to go through the same steps. The order and the specifics of how you do each step will ... Continue Reading
When we think about model assumptions, we tend to focus on assumptions like independence, normality, and constant variance. The other big assumption, ... Continue Reading
The practice of choosing predictors for a regression model, called model building, is an area of real craft. There are many possible strategies and ... Continue Reading
Have you ever compared the list of model assumptions for linear regression across two sources? Whether they’re textbooks, lecture notes, or web pages, ... Continue Reading
When you’re model building, a key decision is which interaction terms to include. And which interactions to remove. As a general rule, the default ... Continue Reading
One of the many decisions you have to make when model building is which form each predictor variable should take. One specific version of this ... Continue Reading
Pretty much all of the common statistical models we use, with the exception of OLS Linear Models, use Maximum Likelihood estimation. This includes ... Continue Reading
The LASSO model (Least Absolute Shrinkage and Selection Operator) is a recent development that allows you to find a good fitting model in the ... Continue Reading
An “estimation command” in Stata is a generic term used for a command that runs a statistical model. Examples are regress, ANOVA, Poisson, logit, and ... Continue Reading
A few years ago, I was in Syracuse for a family trip to the zoo. Syracuse is about 50 miles from where I live and it has a very nice little ... Continue Reading
Have you ever been told you need to run a mixed (aka: multilevel) model and been thrown off by all the new vocabulary? It happened to me when I ... Continue Reading
This one is relatively simple. Very similar names for two totally different concepts. Hierarchical Models (aka Hierarchical Linear Models or HLM) ... 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
Hierarchical regression is a very common approach to model building that allows you to see the incremental contribution to a model of sets of ... Continue Reading
Multicollinearity in regression is one of those issues that strikes fear into the hearts of researchers. You've heard about its dangers in statistics ... Continue Reading
structural equation modeling resources Listed below are workshops, trainings, and articles to help you learn Structural Equation Modeling (SEM). SEM ... Continue Reading
Stata resources Stata is an extremely robust and popular general statistical software program. The Analysis Factor has numerous resources about ... Continue Reading
linear regression resources Listed below are workshops, trainings, and articles to help you learn linear regression. Widely used, this family of ... Continue Reading