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What are order effects in a repeated measures design?
Order effects refer to the order of the conditions having an effect on the participants’ behavior. Performance in the second condition may be better because the participants know what to do (i.e. practice effect). Or their performance might be worse in the second condition because they are tired (i.e., fatigue effect).
How do you deal with 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.
How does counterbalancing overcome order effects?
Counterbalancing is a technique used to deal with order effects when using a repeated measures design. With counterbalancing, the participant sample is divided in half, with one half completing the two conditions in one order and the other half completing the conditions in the reverse order.
How to use repeated measures in SPSS Statistics?
Alternately, you could use a repeated measures ANOVA to understand whether there was a difference in breaking speed in a car based on three different coloured tints of windscreen (e.g., breaking speed under four conditions: no tint, low tint, medium tint and dark tint).
When to use repeated measures in a study?
A repeated-measures ANOVA design is sometimes used to analyze data from a longitudinal study, where the requirement is to assess the effect of the passage of time on a particular variable.
Are there large sample differences in repeated measures ANOVA?
Large sample differences, however, are unlikely; these suggest that the population means weren’t equal after all. The simplest repeated measures ANOVA involves 3 outcome variables, all measured on 1 group of cases (often people). Whatever distinguishes these variables (sometimes just the time of measurement) is the within-subjects factor.
Why do we need descriptive statistics in SPSS?
The descriptive statistics that SPSS outputs are easy enough to understand. The comparison between means (see above) gives us an idea of the direction of any possible effect.