Ch. 8: Experimental Designs: Between-Subjects Design Flashcards
two basic experimental research designs
within-subjects and between-subjects designs
within-subjects design
the groups of scores all can be obtained from the same group of participants
between-subjects design
involves obtaining each group of scores from a different group of participants
synonym for between-subjects design
independent-measures experimental design
goal of between-subjects designs
to determine whether differences exist between two or more treatment conditions
independent scores
there is only one score for each participant
advantages of between-subjects designs
- 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
disadvantages of between-subjects designs
- They require a relatively large number of participants
- Individual differences
individual differences
personal characteristics that differ from one participant to another
concerns about individual differences
- Individual differences can become confounding variables
- Individual differences can produce high variability in the scores
Two major sources of confounding that exist in a between-subjects design
Individual differences
Environmental variables
The separate groups in a between-subjects design must be
created equally, treated equally, composed of equivalent individuals
created equally
the process used to obtain participants should be as similar as possible for all of the groups
treated equally
except for the treatment conditions that are deliberately varied between groups, the groups of participants should receive the same experiences
composed of equivalent individuals
the characteristics of participants in any one group should be as similar as possible to the characteristics of the participants in every other group
three ways to limit confounding by individual differences
- Random assignment (randomization)
- Matching groups (matched assignment)
- Holding variables constant or restricting the range of variability
goal of random assignment
to ensure that all individuals have the same chance of being assigned to a group
assumption of random assignment
It is reasonable to assume that characteristics such as age, IQ, and gender are also randomly distributed across groups
restricted random assignment
the group assignment process is limited to ensure predetermined characteristics (such as equal size) for separate groups
advantage of random assignment
it is fair and unbiased
disadvantage of random assignment
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
matching groups
involves assigning individuals to groups so that a specific participant variable is balanced, or matched across the groups
goal of matching groups
to create groups that are equivalent concerning the variable matched
three steps of matching groups
- Identification of the variable(s) to be matched across groups
- Measurement of the matching variable for each participant
- Assignment of participants to groups using restricted random assignment ensures a balance between groups
advantage of matching groups
provides a relatively easy way to ensure that specific participant variables do not become confounding
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
advantage of holding variables constant or restricting range of variability
it can be an effective way to prevent the variable from confounding
disadvantage of holding variables constant or restricting range of variability
it limits the external validity of the research
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
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
variance
a statistical value that measures the size of the differences from one score to another
variance and patterns in the data
Large variances can obscure patterns in the data
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
4 ways to minimize variance within treatments
- standardize procedures and treatment setting
- limit individual differences
- random assignment and matching
- sample size
standardize procedures and treatment setting
be sure that participants within a group are treated the same
limit individual differences
this can be done by matching variables, holding variables constant, or restricting their range
random assignment and matching
this has no effect on the variance within groups
sample size
using a large sample size can help minimize the problems associated with high variance
what is the best way to minimize the negative consequences of high variance?
to standardize treatments and minimize individual differences between participants
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
