Karen Grace-Martin

Complex Surveys use a sampling technique other than a simple random sample. Terms you may have heard in this area include cluster sampling, stratified sampling, oversampling, two-stage sampling, and primary sampling unit.

Complex Samples require statistical methods that take the exact sampling design into account to ensure accurate results.

This webinar, by guest presenter Dr. Trent Buskirk, will give you an overview of the common sampling techniques, and their effects on data analysis.

Multicollinearity isn’t an assumption of regression models; it’s a data issue.

And while it can be seriously problematic, more often it’s just a nuisance.

In this webinar, we’ll discuss:

• What multicollinearity is and isn’t
• What it does to your model and estimates
• How to detect it
• What to do about it, depending on how serious it is

Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

What is the relationship between predictors and whether and when an event will occur?

This is what event history (a.k.a., survival) analysis tests.

There are many flavors of Event History Analysis, though, depending on how time is measured, whether events can repeat, etc.

In this webinar, we discussed many of the issues involved in measuring time, including censoring, and introduce one specific type of event history model: the logistic model for discrete time events.

Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.