# Data week 7

version from 2017-11-13 13:02

## Section 1

Repeated measures designs (within-participants design)There are many situations in which we might want to study the same individual under a number of different conditions. This is because the research design involves taking repeated measures of the same individual(s) for different treatments or conditions.
Describe repeated measures ANOVA Repeated measures ANOVA is the equivalent of the one-way ANOVA, but for related, and not independent groups. It is an the extension of the paired t-test . A repeated measures ANOVA is also referred to as a within-subjects ANOVA. This week we will look at a One Way Repeated Measures ANOVA.
Advantages of repeated measures designsThe main advantage of repeated measures designs is increased statistical power. This is because the design removes the effects of individual differences. A second advantage is that fewer participants are needed for most experimental designs. This is a big advantage if data is difficult to obtain because we cannot find the participants for our experiment.
Disadvantages of repeated measures designs The main disadvantage of a repeated measures design is that the independent variable may be confounded with order of testing or carry over effects. Practice effects, fatigue effects, contrast effects, demand characteristics.
Practice effects subjects get better at the task over time because of practice, so that they perform best in the later conditions
Fatigue effects subjects get worse at a task over time because of fatigue, so they perform worse in the later conditions
Contrast effects a noisy condition experienced after a quiet condition might be perceived as even noisier than it normally would be.
Demand characteristics being in more than one condition makes it clear to subjects what the independent variable is. They may behave how they think you want them to in later conditions
Solutions to problems of Order Effects for repeated measures designs Randomising the order of testing and counterbalancing order of testing (ex. pg 10)
Another disadvantage of repeated measures designs; missing data -Repeated measures designs run into problems when there is missing data (e.g. one of the participants doesnβt turn up for the third condition of testing). -One solution is to exclude participants with missing data from the analysis (however losing participants means losing power). This is always a risk with a repeated measures design. -Other solutions involve estimating what values the missing data would take (multiple imputation) but this is far more complicated and beyond the scope of this module.