External validity

1. External validity • Generalization based upon representation • If you can’t see it you can’t talk about it.

2. EXTERNAL VALIDITYFOUR ISSUES

3. GENERALIZATION • One can only generalize to that which one has examined. • If ya haven’t looked it ya can’t talk about it! • It “it” compares with what you’re examining you can apply what you found. • Note the “judgment” which must enter in here. • Hence science is tentative.

4. Setting • Are other variables combining with X which influence the X-Y relationship so that there is more than one relationship (statistical interaction; context)? • Can we / do we see that X acts differently on Y in diffferent situations (i.e. in combination with additional variables)?

5. Setting • EX of pretest. • R OXO Classical design • R O O • Vs. • R XO Posttest only design • R O

6. Solomon 4 Design • R OXO • R O O • R XO • R O • Look at the XY effect when there is a pretest vs one when there isn’t.

7. R OXO R O O R XO R O O and Z are Sam Ting R ZXO R Z O R XO R O Pretest is just example of any second variable Z Factorial

8. Factorial • We can now see how X and Z interact.

9. Example • Drug rehab program • Negotiating in neutral territory vs. under threat… • Driving on dry vs. icy road.

10. Statistical partitioning • Same as factorial without randomizing the Zs. • Without randomizing Zs we don’t know what other variables may be confounded with Z and be the real causal culprit.

11. Subjects • We’ve already considered generalization when looking at sampling…We know our odds of being wrong in rejecting no relationship in a population on the basis of a sample. • also…whatever you want to study…make certain that these are the types of people you are studying!

12. Subjects • Because of statistical interaction, we won’t know how a given experiment generalizes without specifically examining each “Z” that can influence the X-Y relationship. • This is an issue raised by experimental psychologists that sociologists “know” but don’t often pass on to their students.

13. Subjects • …so for each type of subject to which we want to generalize…we must examine the X-Y relationship within different categories of the relevant subject characteristic. • Note also…whatever you want to study…make certain that these are the types of people you are studying!

14. How? • Factorial • Statistical partitioning • Note also…whatever you want to study…make certain that these are the types of people you are studying!

15. Operationalizations • Manipulations …we “play god” and “decide” what amount of X the subject will receive by using random assignment…the subject doesn’t decide the amount…so we’re doing more than measuring the independent variable.

16. Operationalizations • We measure the effect of Y. • X manipulates Y we don’t.

17. X • Type • Example • Aggression • Pain pill • Counseling • Tutoring • Diet program • Drug rehab program

18. X • Amount • Total hours of counseling • Total hours of tutoring • Total hours of studying • Total amount of penicillin

19. Y • Type • (amount is measured but we don’t give different amounts as we could with X) • Aggression • Hitting Bobo doll vs. person • Tutoring • One on one vs. group

20. timING • We’re not talking about the “times”…that’s a setting issue. • We’re not talking about time…that’s a manipulation issue. • We’re talking about when we administer the total amount of X…how we dole X out. • & we’re talking about when we assess the effects of X…do we measure Y right after X occurs or later after it’s had time to have an effect or lose its effect?

21. Timing of X • …all at once or in measured doses? • E.g. tutoring, studying, counseling, exercising, dieting, drugging…etc

22. Timing of Y • Right after or later? • Some effects occur immediately and then fade…e.g.: diet programs, inspirational speeches or sales pitches • Others have a sleeper effect…they don't “kick in” ‘till later…e.g.: your appreciation of this great class,