Experiment Basics: Designs

Experiment Basics: Designs Psych 231: Research Methods in Psychology

Exam 2 on Monday • First draft of Class Experiment APA paper due in Labs this week Announcements

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

Interaction of AB A1 A2 B1 mean B1 Main effect of B B2 mean B2 A1 mean A2 mean Main effect of A Condition mean A1B1 What’s the effect of A at B1? What’s the effect of A at B2? Condition mean A2B1 Condition mean A1B2 Condition mean A2B2 2 x 2 factorial design

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

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

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

So you present lists of words for recall either in color or in black-and-white. Clock Chair Cab Clock Chair Cab • What is the effect of presenting words in color on memory for those words? • Two different designs to examine this question Example

levels • Between-Groups Factor • 2-levels • Each of the participants is in only one level of the IV Clock Chair Cab Colored words participants Test Clock Chair Cab BW words

levels participants Colored words BW words Test Test • Within-Groups Factor • Sometimes called “repeated measures” design • 2-levels, All of the participants are in both levels of the IV Clock Chair Cab Clock Chair Cab

participants Colored words Colored words BW words Test Test participants Test BW words • 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. Between vs. Within Subjects Designs

participants Colored words BW words Test Test • 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 Within subjects designs

participants Colored words BW words Test Test • Disadvantages: • Range effects • Order effects: • Carry-over effects • Progressive error • Counterbalancing is probably necessary to address these order effects 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

Condition 1 Condition 2 test test • 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. How long do we wait for the effects to wear off? Order effects

Progressive error • Practice effects – improvement due to repeated practice • Fatigue effects – performance deteriorates as participants get bored, tired, distracted 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

Colored words BW words Test Test participants BW words Colored words Test Test • Simple case • Two conditions A & B • Two counterbalanced orders: • AB • BA Counterbalancing

A B C D Order 1 B C D A Order 2 C D A B Order 3 D A B C Order 4 Example: consider four conditions(Recall: ABCD = 4! = 24 possible orders) 1) Unbalanced Latin square: each condition appears in each position (4 orders) • 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 Partial counterbalancing

2) Balanced Latin square: each condition appears before and after all others (8 orders) • 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) Partial counterbalancing

participants Colored words Colored words BW words Test Test participants Test BW words • 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. Between vs. Within Subjects Designs

Clock Chair Cab Clock Chair Cab Colored words participants Test BW words • 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 Between subjects designs

Clock Chair Cab Clock Chair Cab Colored words participants Test BW words • Disadvantages • Individual differencesbetween the people in the groups • Excessive variability • Non-Equivalentgroups Between subjects designs

Colored words Test participants BW words • The groups are composed of different individuals Individual differences

Colored words Test participants BW words • Excessive variability due to individual differences • Harder to detect the effect of the IV if there is one R NR R • The groups are composed of different individuals Individual differences

Colored words Test participants BW words • 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 • The groups are composed of different individuals 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

matched matched matched matched Red Short 21yrs Blue tall 23yrs Green average 22yrs Brown tall 22yrs • 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 Group A Group B Red Short 21yrs Blue tall 23yrs Green average 22yrs Color Height Age Brown tall 22yrs Matching groups

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

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)

Experiment Basics: Designs