Member Training: Group Comparisons

How do you know which method to use when you want to compare groups?

In research, it is very common to compare measures across groups. Questions might sound like “are these groups different?” or “which group has the best outcomes?” And the good news is that there are a lot of statistical analyses that can help us to make these comparisons.

However, this also makes things complicated. With so many analyses that we can use to compare groups, it can be difficult to pick the right one. Which analysis is correct depends on a number of things:

·        What kind of variable is the outcome measure?
·        How many groups are you comparing?

·        Do you need to adjust for other things that might be different across individuals, besides the group?

In this webinar, we will discuss these considerations, talk about why they lead to the choice of particular models, and provide some examples of these analyses and their results.

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.

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About the Instructor

Kim LoveKim is a Statistically Speaking mentor and workshop instructor for The Analysis Factor. She is also owner/lead consultant at K.R. Love Quantitative Consulting and Collaboration.

She has worked as a statistical consultant and collaborator in multiple professional roles, most recently as the associate director of the University of Georgia Statistical Consulting Center.

Kim has more than a decade of professional and academic experience in the fields of regression and linear models, categorical data, generalized linear models, mixed effects models, nonlinear models, repeated measures, and experimental design. She has a B.A. in mathematics from the University of Virginia, and an M.S. and PhD in statistics from Virginia Tech.

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