Chapter 14: Small-N Designs Flashcards

1
Q

Small-N designs

A

True experiments
Manipulation of one/more IVs and comparison of outcome on the DV
Involve observing an individual before and after treatment

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2
Q

Methods of dealing with unstable data (3)

A

1) Wait until data stabilizes
2) Average a set of 2/more observations
3) Look for patterns within the inconsistencies

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3
Q

Interrupted time series designs

A

Ongoing flow of events/time is interrupted by the introduction of a treatment at some specific point in time
Repeated measurements of the same participants

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4
Q

Types of interrupted time series designs (4)

A

1) AB designs
2) Stable baseline designs
3) Multiple measures designs
4) ABA & ABAB reversal designs

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5
Q

AB design

A

A single before and after measurement is taken

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6
Q

Stable baseline design

A

Multiple pre-treatment measures are taken to ensure that the baseline is stable and there is no evidence of improvement before the treatment

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7
Q

Multiple measures design

A

Multiple measures taken pre- and post-treatment to ensure that any changes are stable (reduces risk that difference is due to chance)

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8
Q

ABAB design

A

Consists of 4 phases: baseline (A), treatment (B), withdrawal of treatment (return to baseline) (A), repetition of treatment phase (B)

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9
Q

Problems with simple reversal design (2)

A

1) Irreversibility of treatment: not appropriate if long-lasting effects are expected
2) Ethics of discontinuing treatment: why remove an effective treatment?

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10
Q

Types of multiple baseline designs (3)

A

1) Multiple-baseline across subjects
2) Multiple-baseline across behaviours
3) Multiple-baseline across situations

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11
Q

Multiple-baseline across subjects

A

Same treatment, different participants

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12
Q

Multiple-baseline across behaviours

A

Same treatment, different problems

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13
Q

Multiple-baseline across situations

A

Same treatment, different situations

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14
Q

Advantages of small-N designs (3)

A

1) Can establish cause and effect with single participant
2) Integrates experimental research into applied clinical settings
3) Flexibility

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15
Q

Disadvantages of small-N designs (3)

A

1) Low external validity
2) Multiple observations required (subject reactivity?)
3) No statistical control

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