Intraclass Correlation Coefficient

Member Training: Inter-Rater Reliability

March 1st, 2016 by

In many fields, the only way to measure a construct of interest is to have someone produce ratings:

It’s well established in research that multiple raters need to rate the same stimuli to ensure ratings are accurate.  There are a number of ways to measure the agreement among raters using measures of reliability. These differ depending on a host of details, including: the number of raters; whether ratings are nominal, ordinal, or numerical; and whether one rating can be considered a “Gold Standard.”

In this webinar, we will discuss these and other issues in measures of inter and intra rater reliability, the many variations of the Kappa statistic, and Intraclass correlations.

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

Audrey Schnell is a statistical consultant and trainer at The Analysis Factor.

Audrey first realized her love for research and, in particular, data analysis in a career move from clinical psychology to research in dementia. As the field of genetic epidemiology and statistical genetics blossomed, Audrey moved into this emerging field and analyzed data on a wide variety of common diseases believed to have a strong genetic component including hypertension, diabetes and psychiatric disorders. She helped develop software to analyze genetic data and taught classes in the US and Europe.

Audrey has worked for Case Western Reserve University, Cedars-Sinai, University of California at San Francisco and Johns Hopkins. Audrey has a Master’s Degree in Clinical Psychology and a Ph.D. in Epidemiology and Biostatistics.

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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.

The Intraclass Correlation Coefficient in Mixed Models

August 22nd, 2013 by

The ICC, or Intraclass Correlation Coefficient, can be very useful in many statistical situations, but especially so in Linear Mixed Models.

Linear Mixed Models are used when there is some sort of clustering in the data.

Two common examples of clustered data include:

Three Issues in Sample Size Estimates for Multilevel Models

November 30th, 2012 by

If you’ve ever worked with multilevel models, you know that they are an extension of linear models. For a researcher learning them, this is both good and bad news.

The good side is that many of the concepts, calculations, and results are familiar. The down side of the extension is that everything is more complicated in multilevel models.

This includes power and sample size calculations. (more…)