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Experimental Design (7) Kerry Kilborn Department of Psychology Overview • • • • • • Confounding variables Experiment vs. Correlational Study Between-Subjects Design Equivalent Groups Quasi-Experiments Summary Experimental Studies Manipulation of IV Change in DV causal link Alcohol level Reaction Time Memory load Recall Rate Drug/Placebo Pain Score Alcohol 50 No Alcohol Reaction Time [ms] Sample (N = 100) 50 375 350 325 300 0 No Yes Alcohol Confounding Variables Confounding IV Reaction Time Testing Time No Alcohol 325 ms 10 am Alcohol 366 ms 10 pm 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 Experimental Studies • what happens in an Experiment: • Manipulation of independent variables (IVs) • Control of confounding (extraneous) variables • Measurement of dependent variables (DVs) Experiments - Evaluated Strength Weakness isolates cause and effect participant bias control of extraneous variables → high internal validity artificial conditions and measures → (low) external validity elimination of alternative explanations participants contribution completely prescribed easy to replicate kind of studied phenomena is limited Experiments - Compared Experimental Method • Manipulates IV and observes effect on DV • Comparable Conditions across all levels of IV • application limited • cause-effect relationship Correlational Method • Observes IV and DV • Further (extraneous) variables may covary with levels of DV • widely applicable • ambiguous cause-effect interpretations Between-Subjects Design • 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) Between-Subjects Design • 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 Between-Subjects Design • 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) Between-Subjects Design Result Attractiveness of woman Crime attractive unattractive control burglary 5.2 yrs 5.1 yrs swindle 4.4 yrs 4.4 yrs Between-Subjects Design 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 Between-Subjects Design 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 Between-Subjects Design • 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 N1 17 6 N6 25 2 N2 16 7 A1 14 3 N3 19 8 A2 16 4 N4 20 9 A3 17 5 N5 18 10 A4 15 __________________________________________ Mean 18.0 17.4 SD 1.58 4.39 Between-Subjects Design • 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 Between-Subjects Design Equal probability of assignment PLUS Allow for relevant individual differences Group 1 Short Group 2 Long 1N 17 6N 27 2N 16 7N 26 3N 19 8N 26 4 A1 10 9 A3 17 5 A2 11 10 A4 15 __________________________________________ Mean 14.6 22.2 SD 3.91 5.72 _________________________________________ Between-Subjects Design • 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 P4 N1 - N4 A2 - A4 P2 P5 N6 - N5 A5 - A1 G1={N1,N5,N2,A2,A1,A6} P3 P6 N3 - N2 A3 - A6 G2={N4,N6,N3,A4,A5,A3} → Matched Pair Design (e.g. identical monozygotic twins) Between-Subjects Design Control Group IV Level 1 DV Experimental Group IV Level 2 DV Sample 1. Random Sample 2. Matched Identical conditions except manipulation of IV Comparison Equivalent Groups Between-Subjects Design • 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) 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 ! Between-Subjects Design • 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 Between-Subjects Design • 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) University A Control Group Traditional Teaching Method DV University B Experimental Group New Interactional Teaching Method DV Nonequivalent Groups Comparison Quasi-experiment Quasi-experiment Control Group No Treatment DV Experimental Group Treatment DV Dyslexics Voluntary participation in dyslexia treatment program (i.e., self-selection) Comparison after 3 years Nonequivalent Groups Summary • True Experiment – Manipulation of IV – Control of confounding variables • Quasi-Experiment – Manipulation of IV – No control of confounding variables