Contents
What is a test-retest correlation?
Test reliability is measured with a test-retest correlation. In other words, give the same test twice to the same people at different times to see if the scores are the same. For example, test on a Monday, then again the following Monday. The two scores are then correlated.
What statistic is used for test-retest?
The correlation coefficient between such two sets of responses is often used as a quantitative measure of the test-retest reliability. For example, a group of respondents is tested for IQ scores: each respondent is tested twice – the two tests are, say, a month apart.
How do you show test-retest reliability?
To measure test-retest reliability, you conduct the same test on the same group of people at two different points in time. Then you calculate the correlation between the two sets of results.
How high is test-retest reliability?
Between 0.8 and 0.7: acceptable reliability. Between 0.7 and 0.6: questionable reliability. Between 0.6 and 0.5: poor reliability. Less than 0.5: unacceptable reliability.
What is a good level of test-retest reliability?
Test-retest reliability has traditionally been defined by more lenient standards. Fleiss (1986) defined ICC values between 0.4 and 0.75 as good, and above 0.75 as excellent. Cicchetti (1994) defined 0.4 to 0.59 as fair, 0.60 to 0.74 as good, and above 0.75 as excellent.
How to test for correlation in a panel?
Serial Correlation – IS test In cases of severe amnesia Syntax: xtistest [varlist], lags(p) Tests for serial correlation up to order p Accepts any kind of unbalanced data (including gaps) Test only works when N > p*T Jesse Wursten (KUL) Five panel correlation tests SUGM 2017 8 / 15
How to test for autocorrelation I panel data-Statalist?
You can use cluster-robust inference to get accurate standard errors given your specification, though if you do find strong serial correlation, it might be a sign that a dynamic panel model is more appropriate. Doing the xtistest i get an error error saying: 3300 argument out of shape.
How to use Wooldridge serial correlation test for panel data?
In this article, we will follow Drukker (2003) procedure to derive the first-order serial correlation test proposed by Jeff Wooldridge (2002) for panel data. It has to be mentioned that this test is considered a robust test, since works with lesser assumptions on the behavior of the heterogeneous individual effects.
What’s the best way to find serial correlation?
You can try the xtistest and xtqptest commands from ssc. The latter will only work on a dataset without gaps though. You can use cluster-robust inference to get accurate standard errors given your specification, though if you do find strong serial correlation, it might be a sign that a dynamic panel model is more appropriate.