2way sex games
Or in other words, while a particular rater might rate Ratee 1 high and Ratee 2 low, it should all even out across many raters.
Like ICC(1), it assumes a random effects model for raters, but it explicitly models this effect – you can sort of think of it like “controlling for rater effects” when producing an estimate of reliability.
An intraclass correlation (ICC) can be a useful estimate of inter-rater reliability on quantitative data because it is highly flexible. This is where ICC comes in (note that if you have qualitative data, e.g. Unfortunately, this flexibility makes ICC a little more complicated than many estimators of reliability.
A Pearson correlation can be a valid estimator of interrater reliability, but only when you have meaningful pairings between two and only two raters. While you can often just throw items into SPSS to compute a coefficient alpha on a scale measure, there are several additional questions one must ask when computing an ICC, and one restriction.
This means ICC(3) will also always be larger than ICC(1) and typically larger than ICC(2), and is represented in SPSS as “Two-Way Mixed” because 1) it models both an effect of rater and of ratee (i.e.
Social scientists of all sorts will appreciate the ordinary, approachable language and practical value – each chapter starts with and discusses a young small business owner facing a problem solvable with statistics, a problem solved by the end of the chapter with the statistical kung-fu gained.
Recently, a colleague of mine asked for some advice on how to compute interrater reliability for a coding task, and I discovered that there aren’t many resources online written in an easy-to-understand format – most either 1) go in depth about formulas and computation or 2) go in depth about SPSS without giving many specific reasons for why you’d make several important decisions.
The primary resource available is a 1979 paper by Shrout and Fleiss, which is quite dense.
So I am taking a stab at providing a comprehensive but easier-to-understand resource.
Reliability, generally, is the proportion of “real” information about a construct of interest captured by your measurement of it.