1. Threats to Validity

2. overview of threats to validity confounding variables faulty manipulation loose procedures order effects experimenter effects Hawthorne effect sensitization history and maturation regression to the mean basement and ceiling effects social desirability bias selection bias (sampling) attrition (mortality)

3. confounding variables confounding variables; may reinforce or suppress the interaction between the independent and dependent variables (p. 267). extraneous variables; outside factors, that are not controlled for, that affect the outcome of an experiment (p. 267). independent variable dependent variable confounding variable

4. faulty manipulation failure to manipulate a variable, or create a stimulus condition as intended –example: Janis & Feshbach's (1953) study on fear appeals Remedies: –include a manipulation check: Teven & Comadena (1996) office aesthetics and teacher credibility –cover story can disguise true purpose of an experiment –use neutral observers to judge stimulus materials

5. loose procedures ambiguity or imprecision in the experimental protocol –The experimental procedures changes slightly from one subject to the next –Example: observer drift on judgments or ratings. Remedies: –run a pilot study –script out all instructions to participants

6. order effects the order, sequence, or placement of items in a series can influence participants' perceptions –example: Schuman, Presser, & Ludwig (1981) survey on attitudes toward abortion Remedies: –shuffle the order of items within a questionnaire, e.g. use multiple versions of the questionnaire –alter the order if diff erent questionnaires are completed together

7. experimenter effects experimenter expectancies (p. 208) –example: intercessory prayer cueing (p. 266) –example: Rosenthal (1966) unintentional paralinguistic and kinesic cues by experimenters demand characteristics of the experimental situation Remedies: –Have people other than the principle investigator perform the experiment –Have people other than the principle investigator measure the outcome

8. Hawthorne effect Self-consciousness: the mere knowledge by a participant that he/she is being observed may alter his/her natural behavior (p. 266) –example: Western Electric plant in Illinois (circa late 1970's) Remedies: –use a cover story –use unobtrusive measures

9. sensitization Also known as “testing effects” familiarity with, or practice on, a specific test or task may improve scores. pre-test measurements may bias post-test measurements Remedies: –avoid pre-tests, if possible –use different pre- and post-test measures

10. history and maturation history: events happening outside the experiment that influence participants' responses within the experiment (p. 270) maturation: changes within in participants during an experiment (developmental, emotional, etc.) (p. 270) Remedies: –keep experiments short –sequester participants if possible

11. regression toward the mean Regression to the mean is a statistical fact of life. Simply stated, things tend to even out over time. –High or low scores are less likely to recur and more likely to gravitate toward what is normal or average. –example: Extremely tall parents tend to have children who are taller than other children, but not as tall as the parents. –example: Sports teams that have a great season are less likely to repeat the following season. –Remedy: Don’t rely on extreme scores from a nonrandom sample.

12. ceiling or basement effects ceiling effect: responses exceed capacity of measuring instrument; responses are “off the scale.” floor or basement effect: responses are below threshold of measuring instrument (see threshold effects, p. 266) Remedies: –use sensitive, precise measures –use established scales, instruments

13. social desirability bias Self reports are often distorted because respondents want to present themselves in the best possible light (p. 208) –Examples: in person interviews involving embarrassing topics; infidelity, spouse abuse, cheating, etc. Remedies: –Emphasize anonymity of responses, importance for obtaining genuine responses, no correct answers –use of indirect questioning: asking respondents to project how they think other persons would answer

14. selection bias failure to gather a random or representative sample, or a reliance on self-selected groups (p. 272) –example: the proverbial "college freshman" used in many social science studies Remedies: –use a random, representative, sufficient sample (easier said than done) –use random assignment within the experiment

15. mortality or attrition Subjects may drop-out or cease participating in a study. The ones who drop out may be different from the ones who remain (p. 272). –example: long-term “longitudinal” research –example: studies on intimates Remedies: –keep studies short –provide incentives for participating