Lecture 3 Flashcards
Measurement precision has two different aspects
- Information; this concept applies to the test score of a single person, thus the within-person aspect of measurement precision
- Reliability, this concept applies to a population of persons, thus the between-person aspect of measurement precision
How can we compute the information concept for a single observed test score?
Inf = 1 / (Var(Ej))
–> the info on test taker j’s true score is the reciprocal of his within person error variance
What does a small amount of info means?
A small amount of info (large within-person error variance) means that the test taker j’s observed score vary widely around j’s true score across repeated test administrations
Definition and formula for reliability
Def: the reliability of the observed test scores is the squared product moment correlation between observed and true test scores in a population of persons
Formula: REL(S) = cor(S,T)^2
However, since you have no information about the true score, this cannot be computed.
What are the two approaches to estimate the reliability?
- parallel tests
- lower bound reliability
Name three requirements of parallel tests
Parallel tests are tests that have:
- True scores are equal
- Equal error variances
- Cov(Ej, E’j) = 0
Definition and formula for the standard error of measurement of a test
Def = the standard error of measurement of a test is the square root of the error variance in the population of persons
Formula = SEM = wortel(Var(s)*(1-Rel(s))
How can you compute alpha
Use the covariance matrix
- Add all the elements in the diagonal
- Divide by the sum of all the elements in the matrix
- 1 - outcome of step 2
- Compute N/(n-1)
- Outcome 3 * outcome 4
How is the correlation corrected for attenuation calculated?
The correlation between two tests corrected for attenuation is the product moment correlation between the true scores of the two tests in a population of persons
- Compute the correlation between the two tests
- Multiply the reliabilities of the tests and take the square root
- Divide 1 by 2
What is the signal to noise ratio?
The signal to noise ratio of a test is the ratio of the true score variance and the error variance of the test in a population of persons.
F = Rel(S)/1-Rel(S)
How can we calculate the correlation between two items?
N-1
- For all persons: compute the differences between the personal score on an item and the item mean score
- Multiply those outcomes and sum up for all the persons
- Divide by N minus 1