Test Construction: Test Theory & Test Score Interpretation Flashcards
Norm-Referenced Interpretation
Percentile ranks
Standard scores
e.g. Z, t, IQ, stanines
Mean and SD:
Z-score
M = 0 SD = 1
“Z = Zero”
Mean and SD:
T-score
M = 50 SD = 10
“Fif-T-score”
Mean and SD:
IQ scores
M = 100 SD = 15
Mean and SD:
Stanine (Standard Nine) scores
StaNINE divide distribution into NINE parts
M = 5 SD = 2
Criterion-Referenced Interpretation:
Three Main Types
Percentage Score
Regression Equation
Expectancy Table
Classical Test Theory:
Two methods of Item Analysis
Item difficulty
Item discrimination
Classical Test Theory: Item Difficulty
p = percentage of respondents that the item correctly
Range of p = 0.0 to +1.0
Classical Test Theory:
Item Discrimination
D = Extent that a test item differentiates between lower and higher scoring groups of examinees
Limitations of Classical Test Theory
Sample dependent and therefore variable
Scores on one test do not have same value on other tests
(e.g. Math and English score of 50)
Item Response Theory: Benefits
Item characteristics do not very across samples
Scores can be compared on different measures
Use of computer-adaptive tests
(items are based on performance on previous items)
Item Response Theory: Item Characteristic Curve
Relationship between ability level and probability of responding to item correctly
Item Response Theory: Main Assumption
Performance of an examinee on a test item can be explained/predicted by:
traits
latent traits
abilities
High Accuracy Rate and Base Rate Below 50%
Relationship to true/false positive/negatives
More false positives than false negatives
False positive = type I error
False Negative = type II error
IRT: Item Characteristic Curve’s 3 parameters:
difficulty
discrimination
probability of guessing correctly