This free, one-hour webinar is part of our regular Craft of Statistical Analysis series. In it, we will introduce and demonstrate two of the core concepts of mixed modeling—the random intercept and the random slope.
Most scientific fields now recognize the extraordinary usefulness of mixed models, but they’re a tough nut to crack for someone who didn’t receive training in their methodology.
But it turns out that mixed models are actually an extension of linear models. If you have a good foundation in linear models, the extension to mixed models is more of a step than a leap. (Okay, a large step, but still).
You’ll learn what random intercepts and slopes mean, what they do, and how to decide if one or both are needed. It’s the first step in understanding mixed modeling.
Date: Friday, August 21, 2015
Time: 12pm EDT (New York time)
Cost: Free
***Note: This webinar has already taken place. Sign up below to get access to the video recording of the webinar.
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.
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
Effect Size Statistics are all the rage.
Journal editors want to see them in every results section.
You need them for performing sample size estimates. (And editors want those too).
But statistical software doesn’t always give us the effect sizes we need.
In this webinar, we will go over:
- The difference between standardized and unstandardized effect size statistics
- An overview of effect size statistics for some common analyses (there seem to be so many!)
- How to calculate these when your software doesn’t give them to you
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
Have you starting using R?
One secret to using any statistical software well and without frustration is learning the little “tricks” that make it easy to do the things you need to do.
This is especially true in R, which is constantly being updated.
In this webinar, R expert David Lillis will show you 10 tips for getting the most of R.
David Lillis has taught R to many researchers and statisticians. His company, Sigma Statistics and Research Limited, provides both on-line instruction and face-to-face workshops on R, and coding services in R. David holds a doctorate in applied statistics and is a frequent contributor to The Analysis Factor.
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
We also offer some online R workshops taught by David.
All statistical modeling–whether ANOVA, Multiple Regression, Poisson Regression, Multilevel Model–is about understanding the relationship between independent and dependent variables. The content differs, but as a data analyst, you need to follow the same 13 steps to complete your modeling.
This webinar will give you an overview of these 13 steps:
- what they are
- why each one is important
- the general order in which to do them
- on which steps the different types of modeling differ and where they’re the same
Having a road map for the steps to take will make your modeling more efficient and keep you on track.
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
Odds ratios are the bane of many data analysts. Interpreting them can be like learning a whole new language. This webinar will go over an example to show how to interpret the odds ratios in binary logistic regression. You will learn:
- how probability and odds both measure the same thing on different scales
- the meaning of odds
- how to interpret an odds ratio for continuous and categorical predictors in logistic regression
This webinar has already taken place. You can gain free access to a video recording of the webinar by completing the form below.
