Experimental Designs Flashcards
Repeated measures design
-There is only one group of participants, who experience BOTH conditions of the IV
Independent groups design
-There are two separate groups of participants, who each take part in ONE condition of the IV. E.G one group experiences only condition A and the other only experiences condition B
Matched pairs design
-There are two separate groups. Each participant is matched into pairs based on certain shared characteristics (E.G gender, ethnicity, age, intelligence) Each person within the pair will only experience ONE condition of the IV that is different to the condition that the other experienced. E.Gone takes part in condition A, the other takes part in condition B
Experiments design
-Refers to how participants are allocated to the different conditions in an experiment
Strengths of repeated measures design
-Reduces participant variables as the same people are used for both conditions.
-Less participants so is cheaper
Limitations of repeated measures design
-Order effects- EV’s that arise due to the way the conditions are presented. E.G fatigue, practise, boredom
-Demand characteristics- may find out the purpose of the experiment and so act differently
Strengths of independent groups design
-No order effects- individuals only experiences one condition of the IV
Limitations of independent groups design
-Participants variables - Any differences between participants across the two groups that could affect results
Strengths of matched pars design
-No demand characteristics
-No order effects
Limitations of repeated measures design
-Cannot control all participant variables (can only reduce)
-Time consuming
What is used to deal with the limitations of repeated measures design
-Counterbalancing (ABBA). E.G Half participants experience conditions A then condition B. The other group experiences B then A. This helps to reduce order effects.
What is used to deal with the limitations of independent groups design
-Random allocation- Placing participants into groups by chance to remove bias. This can be done by using a random number generator or picking names out of a hat.
What is used to deal with the limitations of repeated measures design
-Pilot studies- To pre match Particpants on the main variables that could affect the DV. Key variables are considered when matching participants. E.G age
