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Experiment Basics: Designs
Psych 231: Research Methods in Psychology
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Announcements Exam 2 on Monday
First draft of Class Experiment APA paper due in Labs this week Announcements
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So far we’ve covered a lot of the about details experiments generally
Now let’s consider some specific experimental designs. Some bad (but common) designs Some good designs 1 Factor, two levels 1 Factor, multi-levels Factorial (more than 1 factor) Between & within factors Experimental designs
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2 x 2 factorial design Interaction of AB A1 A2 B2 B1 B1 mean B2 mean
What’s the effect of A at B1? What’s the effect of A at B2? Condition mean A1B1 Condition mean A2B1 B1 mean B2 mean A1 mean A2 mean Main effect of B Condition mean A1B2 Condition mean A2B2 Main effect of A 2 x 2 factorial design
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Factorial Designs Advantages Interaction effects
Consider the interaction effects before trying to interpret the main effects Adding factors decreases the variability Because you’re controlling more of the variables (and their variability) that influence the dependent variable This increases the statistical Power of the statistical tests Increases generalizability of the results More variables = a situation closer to the real world (where all sorts of variables are interacting) Factorial Designs
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Factorial Designs Disadvantages
Experiments can become very large and unwieldy The statistical analyses get much more complex Interpretation of the results can get hard Especially for higher-order interactions Higher-order interactions (when you have more than two interactions, e.g., ABC). Factorial Designs
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So far we’ve covered a lot of the about details experiments generally
Now let’s consider some specific experimental designs. Some bad (but common) designs Some good designs 1 Factor, two levels 1 Factor, multi-levels Factorial (more than 1 factor) Between & within factors Experimental designs
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What is the effect of presenting words in color on memory for those words?
Clock Chair Cab So you present lists of words for recall either in color or in black-and-white. Two different designs to examine this question Example
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Between-Groups Factor
2-levels Each of the participants is in only one level of the IV levels Clock Chair Cab Colored words participants Test Clock Chair Cab BW words
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Within-Groups Factor levels participants Colored words BW Test Clock
Sometimes called “repeated measures” design 2-levels, All of the participants are in both levels of the IV levels participants Colored words BW Test Clock Chair Cab Clock Chair Cab
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Between vs. Within Subjects Designs
All participants participate in all of the conditions of the experiment. Between-subjects designs Each participant participates in one and only one condition of the experiment. participants Colored words BW Test participants Colored words BW Test Between vs. Within Subjects Designs
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Between vs. Within Subjects Designs
All participants participate in all of the conditions of the experiment. Between-subjects designs Each participant participates in one and only one condition of the experiment. participants Colored words BW Test participants Colored words BW Test Between vs. Within Subjects Designs
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Within subjects designs
Advantages: Don’t have to worry about individual differences Same people in all the conditions Variability between conditions is smaller (statistical advantage) Fewer participants are required participants Colored words BW Test Within subjects designs
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Within subjects designs
Disadvantages: Range effects Order effects: Carry-over effects Progressive error Counterbalancing is probably necessary to address these order effects participants Colored words BW Test Within subjects designs
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Within subjects designs
Range effects (context effects) The range of values for your levels may impact performance (typically best performance in middle of range). Since all the participants get the full range of possible values, they may “adapt” their performance (the DV) to this range. Within subjects designs
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Order effects Carry-over effects
Transfer between conditions is possible Effects may persist from one condition into another e.g. Alcohol vs no alcohol experiment on the effects on hand-eye coordination. Hard to know how long the effects of alcohol may persist. test Condition 2 Condition 1 How long do we wait for the effects to wear off? Order effects
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Order effects Progressive error
Practice effects – improvement due to repeated practice Fatigue effects – performance deteriorates as participants get bored, tired, distracted Order effects
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Dealing with Order Effects
Counterbalancing is probably necessary This is used to control for “order effects” Ideally, use every possible order (n!, e.g., AB = 2! = 2 orders; ABC = 3! = 6 orders, ABCD = 4! = 24 orders, etc). All counterbalancing assumes Symmetrical Transfer The assumption that AB and BA have reverse effects and thus cancel out in a counterbalanced design Dealing with Order Effects
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Counterbalancing Simple case Two conditions A & B
Two counterbalanced orders: AB BA participants Colored words BW Test Counterbalancing
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Partial counterbalancing
Often it is not practical to use every possible ordering Partial counterbalancing Latin square designs a form of partial counterbalancing, so that each group of trials occur in each position an equal number of times Example: consider four conditions (Recall: ABCD = 4! = 24 possible orders) 1) Unbalanced Latin square: each condition appears in each position (4 orders) D C B A Order 1 Order 2 Order 3 Order 4 A D C B B A D C C B A D Partial counterbalancing
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Partial counterbalancing
Often it is not practical to use every possible ordering Partial counterbalancing Latin square designs a form of partial counterbalancing, so that each group of trials occur in each position an equal number of times Example: consider four conditions (Recall: ABCD = 4! = 24 possible orders) 2) Balanced Latin square: each condition appears before and after all others (8 orders) A B C D A B D C Partial counterbalancing
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Between vs. Within Subjects Designs
All participants participate in all of the conditions of the experiment. Between-subjects designs Each participant participates in one and only one condition of the experiment. participants Colored words BW Test participants Colored words BW Test Between vs. Within Subjects Designs
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Between subjects designs
Advantages: Independence of groups (levels of the IV) No range effects Exposure to different levels of the independent variable(s) cannot “contaminate” the dependent variable No order effects to worry about Counterbalancing is not required Sometimes between groups is a ‘must,’ because you can’t reverse the effects of prior exposure to other levels of the IV Reduced demand characteristics Harder to guess what the experiment is about without experiencing the other levels of IV participants Colored words BW Test Clock Chair Cab Between subjects designs
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Between subjects designs
Disadvantages Individual differences between the people in the groups Excessive variability Non-Equivalent groups participants Colored words BW Test Clock Chair Cab Between subjects designs
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Individual differences
The groups are composed of different individuals participants Colored words BW Test Individual differences
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Individual differences
The groups are composed of different individuals participants Colored words BW Test Excessive variability due to individual differences Harder to detect the effect of the IV if there is one R NR Individual differences
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Individual differences
The groups are composed of different individuals participants Colored words BW Test Non-Equivalent groups (possible confound) The groups may differ not only because of the IV, but also because the groups are composed of different individuals Individual differences
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Dealing with Individual Differences
Strive for Equivalent groups Created equally Use the same process to create both groups Treated equally Keep the experience as similar as possible for the two groups Composed of equivalent individuals Random assignment to groups - eliminate bias Matching groups - match each individuals in one group to an individual in the other group on relevant characteristics Dealing with Individual Differences
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Matching groups Group A Group B Matched groups
Trying to create equivalent groups Also trying to reduce some of the overall variability Eliminating variability from the variables that you matched people on Red Short 21yrs matched Red Short 21yrs matched Blue tall 23yrs Blue tall 23yrs matched Green average 22yrs Green average 22yrs Color Height Age matched Brown tall 22yrs Brown tall 22yrs Matching groups
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Mixed factorial designs
Treat some factors as within-subjects (participants get all levels of that factor) and others as between-subjects (each level of this factor gets a different group of participants). This only works with factorial (multi-factor) designs Mixed factorial designs
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Exam 2 Topics (Chpts 4, 6, 11) Relevant stuff from Ex1 Variables
types, operationalizing IV: methods of manipulation, getting the right range DV: measurement Validity and Reliability Sampling Control Experimental Designs Vocabulary Single factor designs Between & Within Factorial designs Exam 2 Topics (Chpts 4, 6, 11)
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