Within-person (or within-subject) effects represent the variability of a particular score for individuals in your sample. You will commonly see this being examined in repeated measures analysis (such as repeated measures ANOVA, repeated measures ANCOVA, repeated measures MANOVA or MANCOVA…etc). In this instance, a within person effect is a measure of how much an individual in your sample tends to change (or vary) over time. In other words, it is the average of the average change of scores for an individual in your sample.
For example, imagine we collected a score from every person in your town that measured how much they wanted ice cream at the particular moment of data collection (let's say scores could range from 1 to 100, with 100 meaning REALLY WANT ice cream). Further, let's pretend we did this once a day for 5 days. Our within-subject effect would be a measure of how much individuals in our sample tended to change on their wanting of ice cream over the five days.
Between-persons (or between-subjects) effects, by contrast, don't examine scores of individuals, but instead examine differences between individuals. This can be between groups of cases (when the independent variable[IV] is categorical) or between individuals (when the [IV] is continuous). These type of effects can be observed in either the univariate context or the multivariate context (including repeated measures). Either way, between-subjects effects ask the question: do respondents differ on their score for the DV, depending on their group (males vs. females, young vs. old…etc) or depending on their score on a particular continuous IV?
For example, let's return to our ice cream anecdote. If we want to test whether respondents are more likely to want ice cream if they score highly on an IQ test, we are testing for between-subjects effects. In this example, we are seeing if differences between persons with different IQs also have correspondingly different scores for "wanting ice cream". For more information, such as how to test for these types of effects, feel free to submit a question to our Stats Question or post to our discussion forum. If demand is great, it may even be a topic for a future video tutorial.
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