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repeated measures design
A repeated measures design is a type of experimental design where the same participants are exposed to all conditions of the experiment.
repeated measures strengths
1. reduces risk of participant variables
2. less people so more cost effective and less time consuming
repeated measures limitations
order effects like fatigue and boredom can take place thereby reducing validity
high chance of demand characteristics which also reduces validity
repeated measures limitation control
Counterbalancing: Change the order of conditions for different participants to reduce order effects.
Example: If there are two conditions (A and B), some participants do A→B, others do B→A.
Randomization: Randomly assign the order of conditions.
independent groups design
An independent measures design is an experimental design where different participants are used in each condition of the experiment.
Each participant experiences only one condition.
Comparisons are made between different groups of participants.
independent groups strengths
no chance of order effects
and lower chance of demand characteristics
independent groups limitations
high chance of participant variables
more participants required so less cost effective and more time consuming
independent groups limitation control
Random assignment: Assign participants randomly to conditions to balance individual differences.
matched pairs design
A matched pairs design is a type of experimental setup where participants are paired up based on similarities, and then each member of the pair is given a different treatment. The goal is to control for confounding variables and make the comparison between treatments more precise.
matched pairs design strengths
lower chance of participant variables which increases validity
no chance of order effects and low chance of demand characteristics
matched pairs limitation
it is impossible to completely match 2 people based on everything so participant variables can still occur
matching people can be costly and time consuming