.-
help for ^icc23^
.-

^Calculation of ICC Models 2 and 3^
^---------------------------------^

        .^icc23^ <dv> <classvar> <within_var>, MOdel(#) LEvel(#)


^Description^
^-----------^

^icc23^ computes the intra-class correlation for random effects models based on
>  repeated
measures ANOVA.  These models are ICC[2,1], ICC[2,k], ICC[3,1], and ICC[3,k], a
> s described
by Shrout and Fleiss, 1979 (see reference below).  (For the ICC[1,1] and ICC[1,
> k] models
based on a one-way ANOVA, see @loneway@).  ^icc23^ runs a repeated measures ANO
> VA to derive
the appropriate estimates and degrees of freedom.  In the event there is a sign
> ificant F-test
for the ^classvar^ (e.g., a significant differernce among raters), the program 
> will provide
the p-value from the ANOVA table.

Data must be in the "long" format.  If not, use the @reshape@ command to reconf
> igure the data.

Four types of ICC models are considered:

        ICC[2,1]:  reflects the case where the same group of subjects is rated 
> by k raters,
                   interest is in the reliability of individual scores.  In thi
> s model, raters
                   are considered a representative sample of a population of si
> milar raters. This
                   model is a two-way random effects model.

        ICC[2,k]:  is the same approach as ICC[2,1] above, but interest is in t
> he reliability
                   of the MEAN score, rather than among single observations.

        ICC[3,1]:  reflects the case where the same group of subjects is rated 
> by k raters,
                   interest is in the reliability of individual scores.  In thi
> s model, the only
                   raters of interest are those participating in the study (e.g
> ., there is no 
                   intention of generalizing the raters' scores to a larger pop
> ulation of raters).
                   This model is considered a "mixed" model (subjects are rando
> m, raters are fixed). 
                  
        ICC[3,k]:  is the same approach as ICC[3,1] above, but interest is in t
> he reliability
                   of the MEAN score, rather than among single observations.

Three inputs are required:

            dv     is the dependent variable

         classvar  the class variable refers to factor that is repeated within 
> subjects, e.g., raters,
                   devices, time points, etc., e.g., the variable which would b
> e entered as the 
                   repeated() variable in the ANOVA option.

       within_var  refers to the "within subject" variable, e.g., subjects bein
> g assessed
   

^NOTE:  The order of entry of the variables is critical!^  



^Options^
^-------^
       ^MO^del(#)  refers to the type of model to be estimated.  ICC model 2 is
>  the default (
                 producing ICC[2,1] and ICC[2,k] estimates).
       
       ^LE^vel(#)  the degree of precision of the confidence interval, entered 
> as a decimal.
                 The default is 95%, i.e., level(.95)
                

Examples
--------

For ICC[2,1] and ICC[2,k]: Two-way random effects (Subjects and raters are cons
> idered to be
                           sampled from larger populations); 95% CIs are assume
> d. 
                
^.icc23 score rater person_id^



For ICC[3,1] and ICC[3,k]: Two-way mixed model: Subjects are random, but raters
>  are fixed 
                           (i.e., the raters are not considered a sample -- the
> y are the 
                           only raters of interest); 90% CIs are requested.
                
^.icc23 score rater person_id, model(3) level(.90)^
                

References
----------
Shrout PE, FLeiss JL. Intraclass correlation: uses in assessing rater reliabili
> ty. Psychol
Bull, 1979; 86: 420-428.

Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Pract
> ice (2nd ed.).
Prentice-Hall, Inc: Upper Saddle River, NJ., 2000.


Author
------
Paul F. Visintainer, PhD
Baystate Health System
Springfield, MA 01089
visint46@gmail.com

Luis C.Orozco, MD, MSc
Facultad de Salud
Universidad Industrial de Santander
Colombia
lcorovar@gmail.com


Also see
--------
Manual or on-line help for: @loneway@, @reshape@, @iclassr@, @iclassr2@