Experiment Basics: Designs

Psych 231: Research Methods in Psychology

Between vs. Within Subjects Designs

Within-subjects designs

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

participants

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Between-subjects designs Each participant

participates in one and only one condition of the experiment.

Between subjects designs

Advantages Independence of groups (levels of the IV)

Disadvantages Individual differences between the people in the

groups• Excessive variability• Non-Equivalent groups

participants

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Chair

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Within-subjects designs

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

participants

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Testparticipants

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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 Fewer participants are required

Disadvantages Range effects Order effects:

• Carry-over effects • Progressive error

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.

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

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Note: this becomes a factorial design

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 orders

1) Unbalanced Latin square: each condition appears in each position (4 orders)

DCBA

ADCB

BADC

CBAD

Order 1

Order 2

Order 3

Order 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

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

Describing your design

You need to describe: How many factors How many levels of each factor Whether the factors are within or between groups

• e.g., 2 (shallow/deep processing) x 2 (abstract/concrete) mixed groups factorial design

Describing your results

You need to report: The main effects

• Depth of processing• Word Type

The interaction For each report the means (in the case of the main effects,

report the marginal means) and the statistical outcomes (the ANOVA results)

• Depth of processing: F(1,226) = 98.6, p < 0.001

• Word type: F(1,226) = 34.0, p < 0.001

• Interaction: F(1,226) = 5.0, p < 0.026

Do this with within complete sentences and paragraphs Feel free to supplement the text with a graph if it helps with clarity.

abstract concrete

Shallow 3.5 4.1Deep 4.6 5.8

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