1. Introduction to Research Design Threats to Internal Validity One Group Pretest-Posttest Design

2. O X O Campbell & Stanley “pre-experimental.” Wuensch “experimental.” OK design if can achieve “experimental isolation,” as in the chemistry lab. Correlated samples t test or nonparametric equivalent.

3. History Events other than X between pretest and posttest Pre = subjects’ energy consumption. X = Education on importance of conserving resources. Post = subjects’ energy consumption. History = price of energy increases 50% between pre and post.

4. Maturation Processes that normally cause subjects to change across time. Subjects = newly hired employees Pre = Test of morale X = Six month program to elevate morale Post = Test of morale Maturation = end of honeymoon effect

5. Testing Pretesting subjects can change them. Pre = frequency of conservation behaviors –have you installed a low-flow shower head? –et cetera X = Education on importance of conserving resources Post = frequency of conservation behaviors Testing = just (pre) asking them about certain behaviors might cause them to try them.

6. Instrumentation The measuring instrument changes across time. The $1.99 scale for our fishing experiment. –AM versus PM weight of our catch –Spring stretched The human observer as instrument –effect of treatment on number of problems in computer lab –changes in observers from pre to post

7. Statistical Regression When scores have an error component, both high and low scores regress towards the mean upon retesting. My ESP demo in PSYC 2101 Educational research at Miami Univ. –mean IQ in school district = 102 –mean of selected students = 80 –how much regression is expected?

8. Percent of regression towards the mean, PRM = 100(1 – ρ). If pretest-posttest corr =.8, PRM = 100(1 -.8) = 20%. Expect regression (up) of.2(102 - 80) = 4.4 points. That may be enough to get significant pre- post change.

9. Mortality Subjects who drop out of the experiment may differ from those who stay in. Subjects = patients with wasting disease Pre, Post = body weight, X = New drug 20 patients at pre, 10 at post Pre mean weight = 97 lb, post = 125. Was the drug effective?

10. Perhaps the sickest (and lightest) 10 dropped out. Maybe positive effect from some, who stay in, negative for others, who drop out. Correct by computing means only for those who complete study. –creating a problem of external validity.