Experimental Design: Between and Within

factors

Psych 231: Research Methods in Psychology

Announcements

Exam 2 coming up (Oct. 30) In labs

Turn in methods & Appendix sections for group projects

Turn in IRB form (in PIP packet) (include your informed consent form)

Be prepared to pilot your studies next week

Example

What is the effect of presenting words in color on memory for those words?

Two different designs to examine this question

Clock

Chair

Cab

Clock

Chair

Cab

Clock

Chair

Cab

Clock

Chair

Cab

So you present lists of words for recall either in color or in black-and-white.

participants

Coloredwords

BWwords

Test

2 -levels

Each of the participants is in only one level of the IV

Between-Groups Factor

Clock

Chair

Cab

Clock

Chair

Cab

Clock

Chair

Cab

Clock

Chair

Cab

levelslevels

participantsColoredwords

BWwords

TestTest

2-levels, All of the participants are in both levels of the IV

Clock

Chair

Cab

Clock

Chair

Cab

Clock

Chair

Cab

Clock

Chair

Cab

levelslevels

Sometimes called “repeated measures” design

Within-Groups Factor

Between vs. Within Subjects Designs

Within-subjects designs

All participants participate in all of the conditions of the experiment.

participants

Coloredwords

BWwords

Test participantsColoredwords

BWwords TestTest

Between-subjects designs Each participant participates in one and only one condition of the experiment.

Within-subjects designs

All participants participate in all of the conditions of the experiment.

participants

Coloredwords

BWwords

Test participantsColoredwords

BWwords TestTest

Between-subjects designs Each participant participates in one and only one condition of the experiment.

Between vs. Within Subjects Designs

Between subjects designs

Advantages: Independence of groups (levels of the IV)• Harder to guess what the experiment is about without experiencing the other levels of IV • 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 this is a ‘must,’ because you can’t reverse the effects of prior exposure to other levels of the IV

Between subjects designs

Disadvantages Individual differences between the people in the groups• Excessive variability• Non-Equivalent groups

Individual differences

Excessive variability due to individual differences Harder to detect the effect of the IV if there is one

RNRexp

R

Difference detector

Individual differences

Non-Equivalent groups The groups may differ not only because of the IV, but also because the groups are composed of different individuals

participants

Coloredwords

BWwords

Test

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

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

RedShort21yrs

Bluetall23yrs

Greenaverage22yrs

Browntall22yrs

ColorHeightAge

matchedRedShort21yrs

matched Bluetall23yrs

matchedGreenaverage22yrs

matchedBrowntall22yrs

Within-subjects designs

All participants participate in all of the conditions of the experiment.

participants

Coloredwords

BWwords

Testparticipants

Coloredwords

BWwords TestTest

Between-subjects designs Each participant participates in one and only one condition of the experiment.

Between vs. Within Subjects Designs

Within subjects designs

Advantages: Don’t have to worry about individual differences• Same people in all the conditions• Variability between groups is smaller (statistical advantage)

Fewer participants are required

Within subjects designs

Disadvantages Order effects:

• Carry-over effects • Progressive error• Counterbalancing is probably necessary

Range effects

testCondition 2Condition 1

test

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. 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

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

Counterbalancing

Simple case Two conditions A & B Two counterbalanced orders:

• AB• BA

participants

Coloredwords

BWwords

TestTest

Coloredwords

BWwords

TestTest

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

Partial counterbalancing

Example: consider four conditions Recall: ABCD = 4! = 24 possible orders1) Unbalanced Latin square: each condition appears in each position (4 orders)

DCBA

ADCB

BADC

CBAD

Order 1Order 2Order 3Order 4

Partial counterbalancing

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

A B D C

B C A D

C D B A

D A C B

A B C D

B C D A

C D A B

D A B C

Example: consider four conditions Recall: ABCD = 4! = 24 possible orders

Within subjects designs

Range effects – (context effects) can cause a problem 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.

Mixed factorial designs

Mixed 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

Next time: Factorial designs