Experimental Design: Between and Within factors

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Experimental Design Between and Within factors

• Psych 231 Research Methods in Psychology

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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

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Example

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

• Two different designs to examine this question

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• 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
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• 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
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Between vs. Within Subjects Designs

• 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.

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Between vs. Within Subjects Designs

• 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.

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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 cant
  reverse the effects of prior exposure to other
  levels of the IV

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Between subjects designs

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

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Individual differences

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

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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

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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

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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
Blue tall 23yrs
Green average 22yrs
Color Height Age
Brown tall 22yrs
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Between vs. Within Subjects Designs

• 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.

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Within subjects designs

• Advantages
• Dont have to worry about individual differences
• Same people in all the conditions
• Variability between groups is smaller
  (statistical advantage)
• Fewer participants are required

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Within subjects designs

• Disadvantages
• Order effects
• Carry-over effects
• Progressive error
• Counterbalancing is probably necessary
• Range effects

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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.

How long do we wait for the effects to wear off?
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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

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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

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Counterbalancing

• Simple case
• Two conditions A B
• Two counterbalanced orders
• AB
• BA

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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

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Partial counterbalancing

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

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Partial counterbalancing

• 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 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
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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.

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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