How do you calculate intraclass correlation in SPSS?
Run the analysis in SPSS.
- Analyze>Scale>Reliability Analysis.
- Select Statistics.
- Check “Intraclass correlation coefficient”.
- Make choices as you decided above.
- Click Continue.
- Click OK.
- Interpret output.
What is intraclass correlation SPSS?
The intraclass correlation coefficient, or ICC, is computed to measure agreement between two or more raters (judges) on a metric scale. The raters build the columns of the data matrix, each case is represented by a row. There may be two raters or or more.
How do you calculate intraclass correlation?
The ICC serves as a quantitative estimate of this aspect of reliability. Very generally speaking, the ICC is calculated as a ratio ICC = (variance of interest) / (total variance) = (variance of interest) / (variance of interest + unwanted variance).
How do you read icc2?
For assessing reliability of group-level means, ICC(2) <0.40 are poor, those from 0.40 to 0.75 are fair to good, and those >0.75 are excellent (Fleiss, 1986).
How do you read ICC results?
Under such conditions, we suggest that ICC values less than 0.5 are indicative of poor reliability, values between 0.5 and 0.75 indicate moderate reliability, values between 0.75 and 0.9 indicate good reliability, and values greater than 0.90 indicate excellent reliability.
When do you need ICC ( 2 ) in SPSS?
If your answer to Question 1 is yes and your answer to Question 2 is “sample”, you need ICC (2). In SPSS, this is called “Two-Way Random.” Unlike ICC (1), this ICC assumes that the variance of the raters is only adding noise to the estimate of the ratees, and that mean rater error = 0.
When to use an intraclass correlation ( ICC )?
An intraclass correlation (ICC) can be a useful estimate of inter-rater reliability on quantitative data because it is highly flexible. A Pearson correlation can be a valid estimator of interrater reliability, but only when you have meaningful pairings between two and only two raters. What if you have more?
Which is larger ICC ( 3 ) or ICC ( 1 )?
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. two effects) and 2) assumes a random effect of ratee but a fixed effect of rater (i.e. a mixed effects model).
Do you have to have same number of ratings for ICC?
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. The restriction is straightforward: you must have the same number of ratings for every case rated.
