1. Reliability and Validity in Testing

2. What is Reliability? Consistency Accuracy There is a value related to reliability that ranges from -1 to 1.

3. Types of Reliability Test-retest Parallel/Equivalent forms Inter-rater Intra rater Split half (Internal consistency)

4. Accuracy and Error Every measurement has an error Error can work either ‘for’ you or ‘against’ you. Obtained score = True score +/- Error Or True score = Obtained score +/- Error

5. Standard Error of Measurement SD √1 – r SD = Standard deviation 1 is a constant r = Reliability value What happens if SD = 0? What happens if r = 1?

6. Using the SEM To find the True score True score = Obtained score +/- Error As SEM is a standardised measure (much like standard deviation), can use the normal curve Normal curve helps us to become more precise

7. What is our True Score? How precise do we want to be? Example: SEM = 4.5 Raw score = 42 True score = 42 +/- 4.5 = 37.5 to 46.5 This is at 1 SEM Using the Normal curve, we can be 68% sure that our score is between 37.5 and 46.5 If we want to be 92% sure, we use 2 SEM and the range will be between 33 to 51 (i.e. add another 4.5) What would the range be if we wanted to be 100% sure?

8. Validity What is test validity? Does the test measure what it claims to measure Usually determined logically and through reasoning, not with a value

9. Types of validity Face validity Construct validity Concurrent validity Predictive validity Content validity

10. Issues with Validity Types of validity often independent of each other Other types of validity exists or can be created Validity is often a matter of degree, not whether the test is valid or not valid.

11. Validity and Reliability Does one require the other? Can a test be valid but not reliable? Can a test be reliable but not valid? How does one affect the other? Which is more important – reliability or validity? Practicality – another concern and how it affects validity/reliability