2-10 Flashcards
within-subjects design
An experimental design in which each subject is exposed to all levels of an independent variable.
data is averaged for analysis
also called repeated measures
An experimental design in which each subject is exposed to all levels of an independent variable.
data is averaged for analysis
within-subjects design
also called repeated measures
between-subjects design
An experimental design in which different groups of subjects are exposed to the various levels of the independent variable.
data is averaged for analysis
An experimental design in which different groups of subjects are exposed to the various levels of the independent variable.
data is averaged for analysis
between-subjects design
Pros/cons of and when to use within-subjects?
PROS: reduces error variance
CONS: • more demanding on subjects, especially in complex designs
• Subject attrition is a problem
• Carryover effects
WHEN TO USE: • Subject variables are correlated with the DV
• It is important to economize on participants or subjects
• You want to assess the effects of increasing exposure on behavior
• Track over time
Advantages of matching?
Control over subject variables that can mask effects of your
independent variable
Increases sensitivity to effects of your independent variable
What are main effects and how do we determine them?
The independent effect of one independent variable in a factorial design on the dependent variable. There are as many main effects as there are independent variables.
determine them:
The independent effect of one independent variable in a factorial design on the dependent variable.
main effects
interaction effects
When the effect of one independent variable on the dependent variable in a factorial design changes over the levels of another independent variable.
When the effect of one independent variable on the dependent variable in a factorial design changes over the levels of another independent variable.
interaction effects
error variance
Variability in the value of the dependent variable that is related to extraneous variables and not to the variability in the independent variable.
Variability in the value of the dependent variable that is related to extraneous variables and not to the variability in the independent variable.
error variance
How do we reduce error variance?
Hold extraneous variables constant by treating participants as
similarly as possible
Match participants on crucial characteristics
How do we know whether our results are due to error variance or our manipulation (IV)?
You can estimate the probability that observed differences are caused by error variance by using inferential statistics
If you have one IV, with multiple levels, you have a _____________ design. Multiple IVs with multiple levels is _________ design.
single-factor; factorial
carryover effects
Exposure to a previous treatment affects performance in a subsequent treatment
Exposure to a previous treatment affects performance in a subsequent treatment
carryover effects
What are sources of carryover effect?
learning fatigue habituation (repeated exposure to a stimulus) sensitization contrast adaptation
How to reduce carryover effect?
counterbalancing: treatments presented in a different order for different subjects
partially-counter balancing: like counterbalancing except each treatment appears equally often in each position
confounding
Two variables that vary together in such a way that the effects of one cannot be separated from the effects of the other.
Two variables that vary together in such a way that the effects of one cannot be separated from the effects of the other.
confounding
Sources of confounding?
experimenter bias
treatment conditions are not carefully conceived and unintended variables are introduced
How do we deal with confounding variables?
plan carefully how your independent variables are to be executed.
Careful evaluation of your experimental design and variables
