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111 lines
4.0 KiB
Plaintext
111 lines
4.0 KiB
Plaintext
10 months ago
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.-
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help for ^icc23^
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^Calculation of ICC Models 2 and 3^
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^---------------------------------^
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.^icc23^ <dv> <classvar> <within_var>, MOdel(#) LEvel(#)
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^Description^
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^-----------^
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^icc23^ computes the intra-class correlation for random effects models based on repeated
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measures ANOVA. These models are ICC[2,1], ICC[2,k], ICC[3,1], and ICC[3,k], as described
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by Shrout and Fleiss, 1979 (see reference below). (For the ICC[1,1] and ICC[1,k] models
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based on a one-way ANOVA, see @loneway@). ^icc23^ runs a repeated measures ANOVA to derive
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the appropriate estimates and degrees of freedom. In the event there is a significant F-test
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for the ^classvar^ (e.g., a significant differernce among raters), the program will provide
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the p-value from the ANOVA table.
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Data must be in the "long" format. If not, use the @reshape@ command to reconfigure the data.
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Four types of ICC models are considered:
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ICC[2,1]: reflects the case where the same group of subjects is rated by k raters,
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interest is in the reliability of individual scores. In this model, raters
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are considered a representative sample of a population of similar raters. This
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model is a two-way random effects model.
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ICC[2,k]: is the same approach as ICC[2,1] above, but interest is in the reliability
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of the MEAN score, rather than among single observations.
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ICC[3,1]: reflects the case where the same group of subjects is rated by k raters,
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interest is in the reliability of individual scores. In this model, the only
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raters of interest are those participating in the study (e.g., there is no
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intention of generalizing the raters' scores to a larger population of raters).
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This model is considered a "mixed" model (subjects are random, raters are fixed).
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ICC[3,k]: is the same approach as ICC[3,1] above, but interest is in the reliability
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of the MEAN score, rather than among single observations.
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Three inputs are required:
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dv is the dependent variable
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classvar the class variable refers to factor that is repeated within subjects, e.g., raters,
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devices, time points, etc., e.g., the variable which would be entered as the
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repeated() variable in the ANOVA option.
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within_var refers to the "within subject" variable, e.g., subjects being assessed
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^NOTE: The order of entry of the variables is critical!^
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^Options^
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^-------^
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^MO^del(#) refers to the type of model to be estimated. ICC model 2 is the default (
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producing ICC[2,1] and ICC[2,k] estimates).
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^LE^vel(#) the degree of precision of the confidence interval, entered as a decimal.
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The default is 95%, i.e., level(.95)
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Examples
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--------
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For ICC[2,1] and ICC[2,k]: Two-way random effects (Subjects and raters are considered to be
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sampled from larger populations); 95% CIs are assumed.
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^.icc23 score rater person_id^
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For ICC[3,1] and ICC[3,k]: Two-way mixed model: Subjects are random, but raters are fixed
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(i.e., the raters are not considered a sample -- they are the
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only raters of interest); 90% CIs are requested.
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^.icc23 score rater person_id, model(3) level(.90)^
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References
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----------
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Shrout PE, FLeiss JL. Intraclass correlation: uses in assessing rater reliability. Psychol
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Bull, 1979; 86: 420-428.
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Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice (2nd ed.).
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Prentice-Hall, Inc: Upper Saddle River, NJ., 2000.
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Author
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------
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Paul F. Visintainer, PhD
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Baystate Health System
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Springfield, MA 01089
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visint46@gmail.com
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Luis C.Orozco, MD, MSc
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Facultad de Salud
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Universidad Industrial de Santander
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Colombia
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lcorovar@gmail.com
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Also see
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--------
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Manual or on-line help for: @loneway@, @reshape@, @iclassr@, @iclassr2@
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