Research Design Flashcards

1
Q

independent variable

A
  • the cause
  • experimenter has control over it

example: treatment for depression
IV = type of treatment
DV = level of depression

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2
Q

dependent variable

A
  • the effect
  • the thing that changes in response to the independent variable

example: treatment for depression
IV = type of treatment
DV = level of depression

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3
Q

manipulated vs. non-manipulated IV’s

A

manipulated = 3 different kinds of treatment for depression

non-manipulated = men vs. women (pre-existing, cannot be changed)

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4
Q

true experiment
(types of research)

A
  • at least one independent variable is manipulated and subjects are randomly assigned

example: comparing two types of treatment for anxiety

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5
Q

quasi-experimental
(types of research)

A
  • at least one independent variable is manipulated, but there is non-random assignment of subjects

example: comparing two types of treatment for anxiety, and the groups are already pre-existing (ward A in a hospital vs. ward B)

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6
Q

observational/passive/non-experimental
(types of research)

A
  • no interventions or manipulation of variables

example: studying the extent of cigarette smoking in males and females

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7
Q

between-group designs
(group designs)

A
  • compares two independent groups
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8
Q

within subjects designs
(group designs)

A
  • the groups being compared are correlated or related
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9
Q

counterbalancing

A
  • each group starts with a different treatment or tasks in order to avoid carryover effects

example: Latin square

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10
Q

AB design
(single subject designs)

A
  • baseline condition followed by a treatment condition

associated problem: history

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11
Q

ABAB design
(single subject designs)

A
  • baseline condition, followed by treatment condition, then baseline condition again, then treatment condition again

associated problem: failure of return to baseline, ethical concerns around removing treatment that is helpful

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12
Q

example of a multiple baseline design across subjects
(single subject designs)

A

looking at the effect of medication on hyperactivity for 3 different children

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13
Q

example of a multiple baseline design across situations
(single subject designs)

A

applying an intervention to one problem behaviour (example: biting) in three different settings (home, school, park)

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14
Q

example of a multiple baseline design across behaviours
(single subject designs)

A

applying one intervention for three different problems in one subject (biting, head-banging, and rocking)

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15
Q

simultaneous treatment design
(single subject designs)

A
  • two or more interventions are implemented during the treatment phase in a balanced format (example: alternating during the day and balancing across days)
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16
Q

simple random sampling

A
  • every member of the targeted population has an equal chance of being randomly selected

example: a study focused on registered voters in Alberta, subjects would be randomly selected from a pool of all registered voters

17
Q

stratified random sampling

A
  • first the targeted population is divided into strata (example: ethnicity, age groups, income levels)
  • then a random sample of equal size from each stratum is selected
18
Q

proportional sampling

A
  • individuals are randomly selected in proportion to their representation in the general population
19
Q

systematic sampling

A
  • involves selecting every (n)th element

example: if 100 out of 1000 people are needed, every 10th person would be selected

20
Q

cluster sampling

A
  • identifying naturally occurring groups of subjects and then randomly selecting certain clusters

example: randomly selecting 10 schools in a school district and studying all of the 5th graders from those schools

21
Q

threats to internal validity

A
  • history (ex - trauma)
  • maturation (ex - aging)
  • testing / test practice (use the Solomon Four-group design)
  • instrumentation (ex- equipment breakdown)
  • statistical regression (ex - extreme scores naturally become less extreme)
  • selection bias (ex - all volunteers)
  • attrition (ex - drop out)
  • diffusion
22
Q

threats to construct validity

A
  • attention and contact with clients (this alone can have an effect)
  • experimenter cues/clues
  • demand characteristics (ex - informing subjects about side effects)
  • john henry effect (ex - competition between groups)
23
Q

threats to external validity

A
  • sample characteristics (differences between sample & population are too extreme)
  • stimulus characteristics
  • contextual characteristics (ex - people react in different ways when they know they are being observed)
24
Q

threats to statistical conclusion validity

A
  • low power (contributors are small sample size / inadequate interventions)
  • unreliable measures
  • variability in procedures
  • subject heterogeneity
25
Q

Triangulation (within-method triangulation vs between-method triangulation)

A

More than one approach is used to collect data

Within: methods are same (qualit. & qualit. / quanti & quanti)

Between: methods are different (qualitative AND quantitative)

26
Q

SEM

A

allows researchers to test models of relationships among observed and latent variables.

27
Q

Experiment-wise error rate

A

Increased prob. of TYPE 1 error