Ch. 8: Experimental Designs: Between-Subjects Design Flashcards

1
Q

two basic experimental research designs

A

within-subjects and between-subjects designs

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2
Q

within-subjects design

A

the groups of scores all can be obtained from the same group of participants

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3
Q

between-subjects design

A

involves obtaining each group of scores from a different group of participants

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4
Q

synonym for between-subjects design

A

independent-measures experimental design

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5
Q

goal of between-subjects designs

A

to determine whether differences exist between two or more treatment conditions

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6
Q

independent scores

A

there is only one score for each participant

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7
Q

advantages of between-subjects designs

A
  • Each score is independent of other scores, so it is not influenced by factors such as practice, fatigue, or contrast effects
  • Can be used for a wide variety of research questions
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8
Q

disadvantages of between-subjects designs

A
  • They require a relatively large number of participants
  • Individual differences
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9
Q

individual differences

A

personal characteristics that differ from one participant to another

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10
Q

concerns about individual differences

A
  • Individual differences can become confounding variables
  • Individual differences can produce high variability in the scores
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11
Q

Two major sources of confounding that exist in a between-subjects design

A

Individual differences
Environmental variables

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12
Q

The separate groups in a between-subjects design must be

A

created equally, treated equally, composed of equivalent individuals

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13
Q

created equally

A

the process used to obtain participants should be as similar as possible for all of the groups

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14
Q

treated equally

A

except for the treatment conditions that are deliberately varied between groups, the groups of participants should receive the same experiences

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15
Q

composed of equivalent individuals

A

the characteristics of participants in any one group should be as similar as possible to the characteristics of the participants in every other group

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16
Q

three ways to limit confounding by individual differences

A
  1. Random assignment (randomization)
  2. Matching groups (matched assignment)
  3. Holding variables constant or restricting the range of variability
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17
Q

goal of random assignment

A

to ensure that all individuals have the same chance of being assigned to a group

18
Q

assumption of random assignment

A

It is reasonable to assume that characteristics such as age, IQ, and gender are also randomly distributed across groups

19
Q

restricted random assignment

A

the group assignment process is limited to ensure predetermined characteristics (such as equal size) for separate groups

20
Q

advantage of random assignment

A

it is fair and unbiased

21
Q

disadvantage of random assignment

A

it doesn’t guarantee a perfectly balanced outcome; in the long run, it will be fair, but in the short run, anything can happen by chance

22
Q

matching groups

A

involves assigning individuals to groups so that a specific participant variable is balanced, or matched across the groups

23
Q

goal of matching groups

A

to create groups that are equivalent concerning the variable matched

24
Q

three steps of matching groups

A
  1. Identification of the variable(s) to be matched across groups
  2. Measurement of the matching variable for each participant
  3. Assignment of participants to groups using restricted random assignment ensures a balance between groups
25
advantage of matching groups
provides a relatively easy way to ensure that specific participant variables do not become confounding
26
disadvantages of matching groups
- The researcher must first measure the matched variable which can be tedious and costly - It can be difficult or impossible to match groups on several different variables simultaneously - Groups cannot be matched on every single variable that might differentiate participants
27
advantage of holding variables constant or restricting range of variability
it can be an effective way to prevent the variable from confounding
28
disadvantage of holding variables constant or restricting range of variability
it limits the external validity of the research
29
recommendations for limiting confounding
- Random assignment provides a simple way of balancing characteristics across groups without addressing reach individual variable - When one or two specific variables can be identified as likely to influence the dependent variable, use matching or holding the variable constant
30
individual differences and variability
- Individual differences have the potential to produce high variability in the scores - This can obscure treatment effects and undermine the likelihood of a successful study
31
variance
a statistical value that measures the size of the differences from one score to another
32
variance and patterns in the data
Large variances can obscure patterns in the data
33
differences between treatments and variance within treatments
- Big differences between treatments are good because they provide evidence of differential treatment effects - Big differences within treatments are bad because the differences that exist inside the treatment condition determine the variance of the scores
34
4 ways to minimize variance within treatments
- standardize procedures and treatment setting - limit individual differences - random assignment and matching - sample size
35
standardize procedures and treatment setting
be sure that participants within a group are treated the same
36
limit individual differences
this can be done by matching variables, holding variables constant, or restricting their range
37
random assignment and matching
this has no effect on the variance within groups
38
sample size
using a large sample size can help minimize the problems associated with high variance
39
what is the best way to minimize the negative consequences of high variance?
to standardize treatments and minimize individual differences between participants
40
two advantages of holding a variable constant or restricting its range
- It helps create equivalent groups, which reduces the threat of confounding variables - It helps reduce the variance within groups, which makes the treatment effects easier to see