Chapter 8

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1

between subject experimental design

(independent measures experimental design)

requires a separate, independent group of individuals for each treatment condition

2

individual differences

are personal characteristics that can differ from one participant to another

3

assignment bias

when characteristics in one group are significantly different from the participants in the other group

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  • created equally
  • treated equally
  • composed of equivalent individuals

when researcher has control over the assignment of individuals to groups, the groups must be

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random assignment

a random process is used to assign participants to a group

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restricted random assignment

the group assignment process is limited to ensure predetermined characteristics for the separate groups

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matching

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

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variance within treatments/groups

a measure of differences between scores for a group individuals who have all received the same treatment.

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  • standardizing procedures and treatment setting
  • limit individual differences
  • random assignment and matching
  • sample size

how to minimize variance within treatments

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differential attrition

differences in attrition rates from one group to another and can threaten the internal validity of a between-subjects experiment

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diffusion

the spread of treatment from the experimental group to the control group, which tends to reduce the difference between the two conditions

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compensatory equalization

an untreated group learns about the treatment being received by the other group, and demands the same or equal treatment

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compensatory rivalry

the untreated group works extra hard to show that they can perform just as well as the individuals receiving the special treatment

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resentful demoralization

participants in an untreated group simply give up when they learn that the other group is receiving special treatment.

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two-group design

comparing only two groups of participants: the researcher manipulates one independent variable with only two levels

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single-factor multiple-group design

research design comparing more than two groups of participants representing more than two levels of the same factor