Karen Grace-Martin

Member Training: Discrete Time Event History Analysis

February 1st, 2014 by

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.

(more…)


Effect Size Statistics

January 29th, 2014 by

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.

Statistically Speaking members can access this recording from the Analysis Toolbox Resources page at the Programs Center without signing up.

 


3 Tips to Make Interpreting Moderation Effects Easier

January 24th, 2014 by

Understanding moderation is one of those topics in statistics that is so much harder than it needs to be.

Here are three suggestions to make it just a little easier.

1. Realize that moderation just means an interaction

I have spoken with a number of researchers who are surprised to learn that moderation is just another term for interaction.

Perhaps it’s because moderation often appears with discussions of mediation. Or because we tend to think of interaction as being part of ANOVA, but not regression.

In any case, both an interaction and moderation mean the same thing: the effect of one predictor on a response variable is different at different values of the second predictor. (more…)


Do I Really Need to Learn R?

January 23rd, 2014 by

Do I really need to learn R?

Someone asked me this recently.

Many R advocates would absolutely say yes to everyone who asks.

I don’t.

(I actually gave her a pretty long answer, summarized here).

It depends on what kind of work you do and the context in which you’re working.

I can say that R is (more…)


Member Training: Interactions in ANOVA and Regression Models, Part 2

January 1st, 2014 by

In this follow-up to December’s webinar, we’ll finish up our discussion of interactions.

There is something about interactions that is incredibly confusing.

An interaction between two predictor variables means that one predictor variable affects a  third variable differently at different values of the other predictor.

How you understand that interaction depends on many things, including:

  • Whether one, or both, of the predictor variables is categorical or numerical
  • How each of those variables is coded (specifically, whether each categorical variable is dummy or effect coded and whether numerical variables are centered)
  • Whether it’s a two-way or three-way interaction
  • Whether there is a directionality to the interaction (moderation) or not

Sometimes you need to get pretty sophisticated in your coding, in the output you ask for, and in writing out regression equations.

In this webinar, we’ll examine how to put together and break apart output to understand what your interaction is telling you.


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.

Not a Member? Join!

About the Instructor

Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.

She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.

Not a Member Yet?
It’s never too early to set yourself up for successful analysis with support and training from expert statisticians.

Just head over and sign up for Statistically Speaking.

You'll get access to this training webinar, 130+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.


Member Training: Interactions in ANOVA and Regression Models, Part 1

December 1st, 2013 by

There is something about interactions that is incredibly confusing.Stage 2

An interaction between two predictor variables means that one predictor variable affects a  third variable differently at different values of the other predictor.

How you understand that interaction depends on many things, including:

  • Whether one, or both, of the predictor variables is categorical or numerical
  • How each of those variables is coded (specifically, whether each categorical variable is dummy or effect coded and whether numerical variables are centered)
  • Whether it’s a two-way or three-way interaction
  • Whether there is a directionality to the interaction (moderation) or not

Sometimes you need to get pretty sophisticated in your coding, in the output you ask for, and in writing out regression equations.

In this webinar, we’ll examine how to put together and break apart output to understand what your interaction is telling you.


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.

Not a Member? Join!

About the Instructor

Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.

She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.

Not a Member Yet?
It’s never too early to set yourself up for successful analysis with support and training from expert statisticians.

Just head over and sign up for Statistically Speaking.

You'll get access to this training webinar, 130+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.