Experimental design Flashcards
(13 cards)
Independent groups design
-Independent groups design is when different sets of participants are placed into each condition
-Participants are randomly allocated to each condition (to avoid researcher bias when being assigned to conditions)
what type of data does the independent groups design produce
-Independent groups design produces unrelated data:
-This means that none of the individual data points produced in one condition can be paired with any of the data points in the other condition
Disadvantage of independent groups design
-A disadvantage of independent groups design is that a change in the measurement of the dependent variable may not be due to manipulations of the level of Independent variable, but rather participant variables (characteristics of individuals taking part in the study); For example if there are more participants with a particular characteristic e.g gender in one condition, this may affect the measurement of the dependent variable
-Independent measures design requires twice the amount of participants compared to repeated measures design for the same amount of data
Advantages of independent group design
-Participants that take part in the independent groups design are less likely to guess the aim of the study as they only complete one condition, this, therefore, reduces the likelihood of behaviour being altered due to demand characteristics
-Order effects are not a problem as participants only complete one condition
Repeated measures design
-Repeated measures design is where the same set of participants take part in both conditions
What type of data does repeated measures design produce
-Related data: meaning that each data point in one condition can be paired with a data point in another condition
Disadvantage of repeated measures design
-Order effects: taking part in the first condition can affect the performance of the participant in the second condition; For example worsening performance due to fatigue or boredom, or improving performance due to practice
-Participants are also more likely to figure out the aim of the study, leading to them altering their behaviour due to demand characteristics
Advantages of repeated measures design
-Repeated measures design only uses half the participants compared to independent groups design and gathers the same amount of results
-Participant variables do not affect the measurement of the dependent variable/ are not a problem because the participants complete both conditions
How to control for order effects when using a repeated measures design
-Counterbalancing is used to control for order effects
-This uses the ABBA method, where half the participants complete condition A first and condition B second, while the other half complete condition B first and A second
Matched pairs design
-Different participants complete each condition
-Researchers first assess and rank participants for a certain characteristic that they believe may affect the measurement of the dependent variable e.g aggression
-The top two participants (then the following two) are then randomly assigned to separate conditions
What type of data does matched pairs design produce
-Related data as the data point in one condition can be paired with a data point in another condition
Advantages of matched pairs
-There are reduced participant variables as the participants only complete one condition
-There are no order effects as the participants only complete one condition
-The participants are less likely to guess the aim of the study, reducing the likelihood of altered behaviour due to demand characteristics
Disadvantages of matched pairs design
-Matched pairs design requires double the amount of participants compared to repeated measures design for the same amount of data
-Participants are similar but not identical so there still might be participant variables affecting the measurement of the dependent variable
-Matched pairs design is a lot more time consuming to set up compared to repeated measures or independent groups design
