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How to compare two groups with multiple measurements?
If you are, I’d say you can definitely take the average (or median) per individual and then you’ll have one measure per individual in group A and one measure per individual in group B.
Is it possible to estimate individual treatment means?
By the way, though usually you are interested in the differences between population means with various treatments, you can also estimate the individual means. If you’re interested, see Estimating Individual Treatment Meansin the Appendix. Step 1: ANOVA Test for Equality of All Means The ANOVA procedure tests these hypotheses:
How are between treatments variation and within treatment variation summarized?
These two measures of variation are often summarized in an analysis of variance (ANOVA) table. The between treatments variation and within treatment variation are two components of the total variation in the response.
Why do you use more than two means in ANOVA?
You look at the absolute difference of means between treatments (samples), but you also consider the variability within each treatment. Intuitively, if the difference betweentreatments is a lot bigger than the difference withintreatments, you conclude that it’s not due to random chanceand there is a real effect.
In each group there are 3 people and some variable were measured with 3-4 repeats. As you can see there are two groups made of few individuals for which few repeated measurements were made. I would like to compare two groups using means calculated for individuals, not measure simple mean for the whole group.
Which is the best method for measuring change?
None of them is perfect, but some are better than others. Before getting into the six methods, a little background is in order. When you have one variable that you think is related to a bunch of other variables, perhaps even causally, then you are in the field of regression.
Are there any real problems with measuring change?
You may not know what the problem is (he was sick, the student next to him was hitting him, he fell asleep, whatever) but you know that the 72 is weird in some way, and his ability is more or less constant. The second problem is that many of the common methods for measuring change make assumptions about the data that are completely unrealistic.
What happens when you reduce the number of measurements?
“By reducing multiple measurements to a single variable, there is typically a substantial loss of statistical power” – briefly, statistical power relates to your ability to find what you are looking for.