Experimental Designs: Repeated Measures Design Flashcards

1
Q

What is Repeated Measures Design?

A

ONE GROUP of the SAME participants are exposed to DIFFERENT experiments

(DV what is being measured) (IV What is changing)

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2
Q

What is Independent Groups Design?

A

One Experimental group & One Control group

……..both groups are exposed to:

The Experiment AND The Control

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3
Q

How do you report on a Repeated Measures Design experiment
As a denotation?

A

DV ➡️ IV1 ➡️DV ➡️IV2 ➡️DV

Base line result Time ➡️ Introduce first exp ➡️ Retest to get a Result ➡️ second ex ➡️ Final result time

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4
Q

How do you report a Repeated Measure Design
As a graph?

A

Y axis is vertical
X axis is horizontal

Y axis will be DV (what is being measured)
X axis will be IV (what is being tested)

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5
Q

How do you identify Repeated measures design in a paper?

A

It will say:

✅ Within Subjects

✅ Repeated administrations

✅ Multiple measures
(This explains that the same participants have completed multiple levels of the independent variable)

✅ Will be detailed in Statistical test description in abstract
(ie Repeated measures t-test or Repeated measures ANNOVA)

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6
Q

Counterbalancing
in
Repeated Measures Design

A

❌ Participants can be effected by Order Effects

❌ They pre-empt experiments

❌ Results can get better over time - or worse (because they get bored or fatigued)

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7
Q

What is Counterbalancing and why is it used?

A

✅ Split participants into groups and changing the sequence of the experiment.

✅ Because all experimental conditions have been completed, just in a different order to mitigate against ORDER EFFECTS

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8
Q

How do you counterbalancing 3 conditions?

A

3x2x1

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9
Q

How do you counterbalancing 4 conditions?

A

4x3x2x1

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10
Q

What is Incomplete Counterbalancing?

A

It is the Random allocation of participates to a sequence when there is more than 4 experimental conditions

The Latin square procedure is used to work out the required sequence

Using incomplete sequencing allows us to keeps sample size low but still cover all experimental conditions

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11
Q

Blinding in Repeated Measures Design

A

SINGLE BLIND:

Where the participant OR the researcher are unaware of the experimental condition they have been assigned to

DOUBLE BLIND

Where the participant AND the researcher are unaware of the experimental condition they have been assigned to

Mitigates against:

Experimenter Bias
Demand Characteristics

Experimenter Bias: influencing results by expecting an outcome
Demand Characteristics: participants changing behaviour because they know the aims of the experiment

Only during a debrief should participants know aims.

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12
Q

What are the weaknesses of a Repeated Measures Design experiment?

A

Weakness

  1. Order effect - participants know what the experiment is and can anticipate which can effect performance
  2. More testing materials are required - all participants require material
  3. Limited Scope - Same people.
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13
Q

What are the strengths of a Repeated Measures Design?

A

Strengths

  1. Fewer participants needed
  2. Reduces confounding variables (uncontrollable variable such as time or temp)
  3. Access the effect over time (gathered in one session)
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