1. Validity, Reliability, & Sampling
Psych 231: Research Methods in Psychology

2. Errors in measurement Reliability Validity
If you measure the same thing twice do you get the same values?
Validity
Does your measure really measure what it is supposed to measure??
reliable valid
unreliable
invalid
reliable
invalid

3. Reliability True score + measurement error
A reliable measure will have a small amount of error
Multiple “kinds” of reliability
Test-retest
Internal consistency
Inter-rater

4. Reliability Test-restest reliability
Test the same participants more than once
Measurement from the same person at two different times
Should be consistent across different administrations
Reliable
Unreliable

5. Reliability Internal consistency reliability
Multiple items testing the same construct
Extent to which scores on the items of a measure correlate with each other
Cronbach’s alpha (α)
Split-half reliability
Correlation of score on one half of the measure with the other half (randomly determined)

6. Reliability Inter-rater reliability At least 2 raters observe behavior
Extent to which raters agree in their observations
Are the raters consistent?
Requires some training in judgment

7. Validity
Does your measure really measure what it is supposed to measure?
There are many “kinds” of validity

8. Many kinds of Validity VALIDITY CONSTRUCT INTERNAL EXTERNAL FACE
CRITERION-
ORIENTED
PREDICTIVE
CONVERGENT
CONCURRENT
DISCRIMINANT

9. Many kinds of Validity VALIDITY CONSTRUCT INTERNAL EXTERNAL FACE
CRITERION-
ORIENTED
PREDICTIVE
CONVERGENT
CONCURRENT
DISCRIMINANT

10. Construct Validity
Usually requires multiple studies, a large body of evidence that supports the claim that the measure really tests the construct

11. Face Validity
At the surface level, does it look as if the measure is testing the construct?
“This guy seems smart to me,
and
he got a high score on my IQ measure.”

12. Internal Validity The precision of the results
Did the change in the DV result from the changes in the IV or does it come from something else?

13. Threats to internal validity
The precision of the results
History – an event happens the experiment
Maturation – participants get older (and other changes)
Selection – nonrandom selection may lead to biases
Mortality – participants drop out or can’t continue
Testing – being in the study actually influences how the participants respond

14. External Validity
Are experiments “real life” behavioral situations, or does the process of control put too much limitation on the “way things really work?”

15. External Validity Variable representativeness
Relevant variables for the behavior studied along which the sample may vary
Setting representativeness
Are the properties of the research setting similar to those outside the lab (Ecological validity)
Subject representativeness
Characteristics of sample and target population along these relevant variables

16. Sampling Why do we do we use sampling methods?
Typically don’t have the resources to test everybody, so we test a subset

17. Sampling Everybody that the research is targeted to be about
Population
Everybody that the research is targeted to be about
The subset of the population that actually participates in the research
Sample

18. Sampling Population Sample Sampling to make data collection manageable
Inferential statistics used to generalize back
Sampling to make data collection manageable
Sample

19. Sampling Why do we do we use sampling methods?
Goals of “good” sampling:
Maximize Representativeness:
To what extent do the characteristics of those in the sample reflect those in the population
Reduce Bias:
A systematic difference between those in the sample and those in the population

20. Sampling Methods Probability sampling Non-probability sampling
Simple random sampling
Systematic sampling
Stratified sampling
Non-probability sampling
Convenience sampling
Quota sampling
Have some element of random selection
Susceptible to biased selection

21. Simple random sampling
Every individual has a equal and independent chance of being selected from the population

22. Systematic sampling
Selecting every nth person

23. Stratified sampling Step 1: Identify groups (strata)
Step 2: randomly select from each group

24. Convenience sampling
Use the participants who are easy to get

25. Quota sampling Step 1: identify the specific subgroups
Step 2: take from each group until desired number of individuals

26. Next time
Read: Chpt 8