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Fwd: st: reliability with -icc- and -estat icc-


From   Lenny Lesser <lenny3200@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Fwd: st: reliability with -icc- and -estat icc-
Date   Tue, 26 Feb 2013 08:16:19 -0800

Thanks Rebecca,
With that code, I get the same problem when I eliminate one rater.

the var(rater) goes to zero, which makes my ICC 0, rather go up to a
higher number as I expected.


---------- Forwarded message ----------
From: Rebecca Pope <rebecca.a.pope@gmail.com>
Date: Tue, Feb 26, 2013 at 7:08 AM
Subject: Re: st: reliability with -icc- and -estat icc-
To: statalist@hsphsun2.harvard.edu


Lenny,
I don't think you've got the correct syntax for -xtmixed- if you are
trying to duplicate ANOVA results, which is the type of analysis that
-icc- appears to conduct (documentation is still limited, so I won't
swear to anything).

Use this syntax for -xtmixed-:
xtmixed rank i.Application || _all: R.Rater, reml var

-estat icc- is not a valid post-estimation command after this
specification. However, you can just use the definition that ICC =
Var(Rater)/(Var(Rater)+Var(Residual)).

You might also want to take a look at
http://www.ats.ucla.edu/stat/stata/faq/xtmixed.htm which will give you
instructions for using -xtmixed- to conduct ANOVA-type analyses (using
Stata 10, so you'll need to modify somewhat).

Regards,
Rebecca



On Mon, Feb 25, 2013 at 10:56 PM, Lenny Lesser <lenny3200@gmail.com> wrote:
> I have 4 raters that gave a score of 0-100 on 11 smartphone applications.
> The data is skewed right, as they all got low scores.  I'm using the
> ranks (within an individual) instead of the actual scores.  I want to
> know the correlation in ranking between the different raters.
>
> I've tried the two commands:
>
> -xtmixed rank Application || Rater: , reml
> -estat icc
>
> (icc=0.19)
>
> and
>
> -icc rank Rater Application, mixed consistency
>
> (icc=0.34)
>
> They give me two different answers. Which one is correct?
>
>
> Next, we found out that rater 4 was off the charts, and we want to
> eliminate her and rerun the analysis. When we do this we get wacky
> ICCs.  In the first method we get an ICC of 2e-26.  In the 2nd method
> (-icc), we get -.06.  Eliminating any of the other raters gives us
> ICCs close to the original ICC.  Why are we getting such a crazy
> number when we eliminate this 4th rater?
>
>
> I'm guessing this might be instability in the model, but I'm not sure
> how to get around it.
>
> Lenny
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