Experimental Design (7)

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1 Experimental Design (7) Kerry Kilborn Department of Psychology

2 Overview Confounding variables Experiment vs. Correlational Study Between-Subjects Design Equivalent Groups Quasi-Experiments Summary

3 Experimental Studies Manipulation of IV Alcohol level Memory load Drug/Placebo causal link Change in DV Reaction Time Recall Rate Pain Score

4 Alcohol Sample (N = 100) No Alcohol Reaction Time [ms] No Alcohol Yes

5 Confounding Variables Confounding IV Reaction Time Testing Time No Alcohol 325 ms 10 am Alcohol 366 ms 10 pm

6 Confounding Variables Possible Confounding Variables Person-specific Situation-specific Age Experimenter Education Time point of testing Socio-economic status Testing environment Motivation Apparatus Memory Stimulus intensity Intelligence Duration

7 Experimental Studies what happens in an Experiment: Manipulation of independent variables (IVs) Control of confounding (extraneous) variables Measurement of dependent variables (DVs)

8 Experiments - Evaluated Strength isolates cause and effect control of extraneous variables high internal validity elimination of alternative explanations easy to replicate Weakness participant bias artificial conditions and measures (low) external validity participants contribution completely prescribed kind of studied phenomena is limited

9 Experiments - Compared Experimental Method Correlational Method Manipulates IV and observes effect on DV Observes IV and DV Comparable Conditions across all levels of IV application limited cause-effect relationship Further (extraneous) variables may covary with levels of DV widely applicable ambiguous cause-effect interpretations

10 Experiments compare at least two conditions A and B at least 2 levels of independent variable (IV) Subjects who participate might be placed into condition A, B or both 2 different types of experimental designs If subjects receive either level A or B but not both between-subjects design If each subject receives both levels of IV (A, B), i.e., both levels exist within the same subject within-subjects design (repeated measures design)

11 Sometimes a between-subjects design must be used. If the independent variable is a subject-variable (e.g., anxiety, gender,..) manipulated in a certain way that precludes within-subjects measures (e.g., social Ψ experiments), i.e., participating in one condition makes it impossible for the same person to be in a second condition

12 Example (Sigall & Ostrove, 1975): on the influence of physical attractiveness of a defendant on recommended sentence written descriptions of a crime - asked to recommend a jail IV1 = Type of crime (2 levels: burglary in which woman stole 2,200 $ vs. swindle in which woman induced man to invest 2,200 $) IV2 = Attractiveness of woman (2 levels: very attractive vs. unattractive (vs. no photo)

13 Result Attractiveness of woman Crime attractive unattractive control burglary 5.2 yrs 5.1 yrs swindle 4.4 yrs 4.4 yrs

14 Result Attractiveness of woman Crime attractive unattractive control burglary 2.8 yrs 5.2 yrs 5.1 yrs swindle 5.5 yrs 4.4 yrs 4.4 yrs

15 Advantage subjects enter the study fresh and naive with respect to procedures Disadvantage large number of individuals needed differences between conditions might be due to differences between groups

16 with a small number of participants it could happen that random assignment places all A-subjects into one group non-equivalent groups Group 1 Short Group 2 Long 1 N N N A N A N A N A4 15 Mean SD

17 Creating Equivalent Groups Random Assignment method for placing randomly selected subjects into the different groups equal probability for each subject to be assigned to a specific condition spread possible individual difference factors evenly across conditions

18 Equal probability of assignment PLUS Allow for relevant individual differences Group 1 Short Group 2 Long 1 N 17 6 N 27 2 N 16 7 N 26 3 N 19 8 N 26 4 A A A A4 15 Mean SD

19 Matching Pair subjects together for a specific characteristic and then assign randomly to groups. You need to measure the matching variable in a reasonable manner. Example: obtain scores for test anxiety and then sort subjects into pairs and assign subjects from each pair randomly to the two groups (flip a coin) P1 N1 - N4 P2 N6 - N5 P3 N3 - N2 P4 A2 - A4 P5 A5 - A1 P6 A3 - A6 G1={N1,N5,N2,A2,A1,A6} G2={N4,N6,N3,A4,A5,A3} Matched Pair Design (e.g. identical monozygotic twins)

20 Equivalent Groups Sample Control Group Experimental Group IV Level 1 IV Level 2 DV DV Comparison 1. Random Sample 2. Matched Identical conditions except manipulation of IV

21 Manipulated vs. Subject Variables Comparisons may be made also between groups of people who differ from each other in ways not manipulated by experimenter comparison between factors which are nonmanipulated variables or ex-post-facto variables subject variables Refer to already existing characteristics of the participants in the study (e.g., gender, intelligence, age, RT)

22 Example Group study of relationship between anger level and cardiovascular responsiveness (CR) to film scenes a) induce different levels of anger and measure CR b) select two groups differing in pretest-level of anger here subjects cannot be randomly assigned to groups Pre-test: measure of participants before an experiment in order to balance or compare groups, or to assess change by comparison with scores after the experiment No "true" experiment!

23 Problems with subject variables experimenter can not hold all other variables constant extraneous variables can not be controlled e.g., person with higher scores in anger may also differ in the way they cope with everyday life situations; they might be prone to have cardiovascular problems,... no cause-effect conclusions can be drawn in contrast to a confound free experiment Studies using subject variables are also called ex post facto studies or quasi-experiment

24 Ex post facto research study where pre-existing and non-manipulated variables among people are measured Quasi-experiment study in which experimenter does not have control over the allocation of participants to conditions and/or the independent variable Group difference study study, which compares the measurement of an existing variable in two contrasting groups (male vs. female, intro- vs. extrovert)

25 Quasi-experiment University A University B Control Group Traditional Teaching Method Experimental Group New Interactional Teaching Method DV DV Comparison onequivalent Groups

26 Quasi-experiment Nonequivalent Groups Dyslexics Control Group Experimental Group No Treatment Treatment DV DV Comparison after 3 years oluntary participation in yslexia treatment program i.e., self-selection)

27 Summary True Experiment Manipulation of IV Control of confounding variables Quasi-Experiment Manipulation of IV No control of confounding variables

Lecture 4: Research Approaches

Lecture 4: Research Approaches Lecture Objectives Theories in research Research design approaches ú Experimental vs. non-experimental ú Cross-sectional and longitudinal ú Descriptive approaches How to