L3 Reliability Flashcards
Classical Test Theory
- Is a measurement theory that defines the conceptual basis of reliability.
- The observed score (X) is the True score (T) plus Error (E)
- X = T + E
True scores
A hypothetical entity devoid of measurement error.
- True scores deal with reliability while construct scores deal with validity.
- True scores may be “perfect” but perfect reliability does not equal perfect validity.
- May get the same consistently wrong score.
Observed scores
Are the actual scores obtained from tests or instruments.
- True scores are hypothetical entities which represent the observed scores under the pretence that they are devoid of measurement error.
- We want observed scores to be as close as possible to true scores.
Reliability (another way to think about it)
- The correlation between observed scores and true scores
- The difference between true scores and observed scores is due to measurement error.
Error scores
Should have a mean of zero.
- This is because an equal amount of people should have an observed score that is too large as too small (and the magnitudes should be the same)
- Effectively, error cancels itself out across cases.
- Error scores should be an independent and random process (not correlate with anything).
R^2 between observed and true scores
- the correlation between observed and true scores is known as the reliability index
- squaring the reliability index gives an estimation of reliability.
- look at slide for formula (Rxx = r2ot
Interpretations of reliability
.60 = too low .70 = bare minimum acceptable for beginning stage research .80 = good level for research purposes .90+ = Necessary in applied contexts where important decisions are made about individuals.
4 different reliabilities
Rxx = r2ot
Rxx = St2/S2o
Rxx = 1 - S2e/S2o
Rxx = 1 - r2oe
Parallel Tests
Are identical to each other psychometrically, but differ in the items that make up each test.
All tau-equivalence assumptions
Tau-equivalence, in parallel tests, implies that the true scores associated with each test represent the same construct.
- Thus a person’s true score on 1 test is expected to be identical on the other test.
- Assumed equal error variances between the 2 tests.
Test-retest interval
- the length of time between test 1 and test 2 matters.
- the magnitude of the interval between the two testing sessions will affect the magnitude of the correlation between the scores.
- Developmental and lifespan changes.
stability coefficient
Is test-retest reliability
Internal-consistency reliability
- A practical alternative to the test-retest procedure.
- only need to complete 1 test at 1 occasion
- it treats different items within the same test as different forms of the test.
Factors that affect internal consistency reliability
- the degree of consistency between the items of the test
- The length of the test
Spilt-half reliability problem
- How should the test be split into halves?
- Cronbach saved the day
- Cronbach introduced a reliability formula that represented the reliability of all possible split-halves.
- Cronbach demonstrated a method of estimation based at the item-level.