Repeated measures designs have some disadvantages compared to designs that have independent groups. The biggest drawbacks are known as order effects, and they are caused by
exposing the subjects to multiple treatments
. Order effects are related to the order that treatments are given but not due to the treatment itself.
What are the main advantages and disadvantages of using a repeated measures design?
- Pro: As the same participants are used in each condition, participant variables (i.e., individual differences) are reduced.
- Con: There may be order effects. …
- Pro: Fewer people are needed as they take part in all conditions (i.e. saves time).
What is a weakness of using a repeated measures design?
The biggest weakness of the repeated measures design is
the order of conditions and how this may affect participant performance
. A way of dealing with this is counterbalancing. This ensures that each condition is tested first and second in equal amounts.
Why is it not possible to use repeated measures in all experiments?
Advantages and Disadvantages
A disadvantage of the repeated measure design is that
it may not be possible for each participant to be in all conditions of the experiment
(due to time constraints, location of experiment, etc.).
Why is repeated measures better than independent?
A repeated measures design consists of testing the same individuals on two or more conditions. The advantage of this is that
individual differences between participants are removed as a potential confounding variable
.
When repeated-measures are used which assumption is violated?
Unfortunately, repeated measures ANOVAs are particularly susceptible to violating the
assumption of sphericity
, which causes the test to become too liberal (i.e., leads to an increase in the Type I error rate; that is, the likelihood of detecting a statistically significant result when there isn’t one).
Why use a repeated-measures Anova?
The benefits of repeated measures designs are that
they reduce the error variance
. This is because for these tests the within group variability is restricted to measuring differences between an individual’s responses between time points, not differences between individuals.
What is an example of a repeated measures design?
In a repeated measures design, each group member in an experiment is tested for multiple conditions over time or under different conditions. For example, a group of people with
Type II diabetes might be given medications to see if
it helps control their disease, and then they might be given nutritional counseling.
How do you reduce order effects?
Carryover and interference effects can be reduced
by increasing the amount of time between conditions
. Researchers also reduce order effects by systematically varying the order of conditions so that each condition is presented equally often in each ordinal position. This procedure is known as counterbalancing.
What are the assumptions of repeated-measures Anova?
- Independent and identically distributed variables (“independent observations”).
- Normality: the test variables follow a multivariate normal distribution in the population.
- Sphericity: the variances of all difference scores among the test variables must be equal in the population.
What are two advantages to a repeated measures design?
More
statistical power
: Repeated measures designs can be very powerful because they control for factors that cause variability between subjects. Fewer subjects: Thanks to the greater statistical power, a repeated measures design can use fewer subjects to detect a desired effect size.
What is mixed repeated-measures?
The mixed model for repeated measures (MMRM) is
a popular choice for individually randomized trials with longitudinal continuous outcomes
. This model’s appeal is due to avoidance of model misspecification and its unbiasedness for data missing completely at random or at random.
What can I use instead of a repeated-measures ANOVA?
Consequently, the issues underlying the choice between the univariate, multivariate, and mixed-model approaches to repeated measures ANOVA are completely eschewed. This novel and parsimonious alternative is referred to as an
Ordinal Pattern Analysis
in the context of Observation Oriented Modeling (Grice, 2011, 2014).
What is a repeated measures variable?
Repeated measures design is
a research design that involves multiple measures of the same variable taken on the same or matched subjects
either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.
Why is independent measures design good?
Advantages of independent measures design include
less time/money involved than a within subjects design and increased external validity because more participants are used
. A disadvantage is that individual differences in participants can sometimes lead to differences in the groups’ results.
What are the limitations of independent measures design?
- researcher cannot control the effects of participant variables (i.e. different characteristics or abilities of each participant). This would cause a confounding variable.
- needs more design than the Repeated Measures Design in order to end up with the same amount of data.
