Experimental Control Design Psych 231 Research Methods in

Experimental Control & Design Psych 231: Research Methods in Psychology

n Methods of Experimental Control n n n Constancy/Randomization Comparison Production Controlling Variability

n Constancy/Randomization n If there is a variable that may be related to the DV that you can’t (or don’t want to) manipulate • Control variable: hold it constant • Random variable: let it vary randomly across all of the experimental conditions n But beware of potential confounds, variables that co-vary with both the IV and DV but aren’t controlled Methods of Controlling Variability

n Comparison n An experiment always makes a comparison, so it must have at least two groups • Sometimes there are control groups • This is typically the absence of the treatment Training group • • No training (Control) group Without control groups if is harder to see what is really happening in the experiment It is easier to be swayed by plausibility or inappropriate comparisons Methods of Controlling Variability

n Comparison n An experiment always makes a comparison, so it must have at least two groups • Sometimes there are control groups • This is typically the absence of the treatment • Sometimes there a range of values of the IV 1 week of Training group 2 weeks of Training group 3 weeks of Training group Methods of Controlling Variability

n Production n The experimenter selects the specific values of the Independent Variables 1 week of Training group 2 weeks of Training group 3 weeks of Training group • Need to do this carefully • Suppose that you don’t find a difference in the DV across your different groups • Is this because the IV and DV aren’t related? • Or is it because your levels of IV weren’t different enough Methods of Controlling Variability

n n So far we’ve covered a lot of the about details experiments generally Now let’s consider some specific experimental designs. n n Some bad designs Some good designs • • 1 Factor, two levels 1 Factor, multi-levels Factorial (more than 1 factor) Between & within factors Experimental designs

n Bad design example 1: Does standing close to somebody cause them to move? n n n “hmm… that’s an empirical question. Let’s see what happens if …” So you stand closely to people and see how long before they move Problem: no control group to establish the comparison group (this design is sometimes called “one-shot case study design”) Poorly designed experiments

n Bad design example 2: n n Testing the effectiveness of a stop smoking relaxation program The participants choose which group (relaxation or no program) to be in Poorly designed experiments

n Bad design example 2: Non-equivalent control groups Self Assignment Independent Variable Dependent Variable Training group Measure No training (Control) group Measure participants Random Assignment Problem: selection bias for the two groups, need to do random assignment to groups Poorly designed experiments

n Bad design example 3: Does a relaxation program decrease the urge to smoke? n Pretest desire level – give relaxation program – posttest desire to smoke Poorly designed experiments

n Bad design example 3: One group pretest-posttest design Dependent Variable participants Add another factor Independent Variable Pre-test Training group Dependent Variable Post-test Measure Pre-test No Training group Post-test Measure Problems include: history, maturation, testing, and more Poorly designed experiments

n Good design example n How does anxiety level affect test performance? • Two groups take the same test • Grp 1 (moderate anxiety group): 5 min lecture on the importance of good grades for success • Grp 2 (low anxiety group): 5 min lecture on how good grades don’t matter, just trying is good enough n 1 Factor (Independent variable), two levels • Basically you want to compare two treatments (conditions) • The statistics are pretty easy, a t-test 1 factor - 2 levels

n Good design example n How does anxiety level affect test performance? Random Assignment Anxiety Dependent Variable Low Test Moderate Test participants 1 factor - 2 levels

Good design example n How does anxiety level affect test performance? One factor Use a t-test to see if anxiety low moderate 60 80 test performance n these points are statistically different Observed difference between conditions T-test = Difference expected by chance low Two levels 1 factor - 2 levels moderate anxiety

n Advantages: n n Simple, relatively easy to interpret the results Is the independent variable worth studying? • If no effect, then usually don’t bother with a more complex design n Sometimes two levels is all you need • One theory predicts one pattern and another predicts a different pattern 1 factor - 2 levels

n Disadvantages: n “True” shape of the function is hard to see • Interpolation and Extrapolation are not a good idea Interpolation test performance What happens within of the ranges that you test? low 1 factor - 2 levels moderate anxiety

n Disadvantages: n “True” shape of the function is hard to see • Interpolation and Extrapolation are not a good idea Extrapolation test performance What happens outside of the ranges that you test? low moderate anxiety 1 factor - 2 levels high

n n For more complex theories you will typically need more complex designs (more than two levels of one IV) 1 factor - more than two levels n n Basically you want to compare more than two conditions The statistics are a little more difficult, an ANOVA (Analysis of Variance) 1 Factor - multilevel experiments

n Good design example (similar to earlier ex. ) n How does anxiety level affect test performance? • Two groups take the same test • Grp 1 (moderate anxiety group): 5 min lecture on the importance of good grades for success • Grp 2 (low anxiety group): 5 min lecture on how good grades don’t matter, just trying is good enough • Grp 3 (high anxiety group): 5 min lecture on how the students must pass this test to pass the course 1 Factor - multilevel experiments

Random Assignment participants Anxiety Dependent Variable Low Test Moderate Test High Test 1 factor - 3 levels

low mod high 60 80 60 test performance anxiety low mod high anxiety 1 Factor - multilevel experiments

n Advantages n n Gives a better picture of the relationship (function) Generally, the more levels you have, the less you have to worry about your range of the independent variable 1 Factor - multilevel experiments

2 levels test performance 3 levels low moderate anxiety low mod high anxiety Relationship between Anxiety and Performance

n Disadvantages n n Needs more resources (participants and/or stimuli) Requires more complex statistical analysis (analysis of variance and pair-wise comparisons) 1 Factor - multilevel experiments

n The ANOVA just tells you that not all of the groups are equal. n If this is your conclusion (you get a “significant ANOVA”) then you should do further tests to see where the differences are • High vs. Low • High vs. Moderate • Low vs. Moderate Pair-wise comparisons