How do you compare data with different sample sizes?
One way to compare the two different size data sets is to divide the large set into an N number of equal size sets. The comparison can be based on absolute sum of of difference. THis will measure how many sets from the Nset are in close match with the single 4 sample set.
How many participants do you need for ANOVA?
The model needs at least one participant in each group and more participant than there are coefficients to be estimated. This means for instance for a one-way ANOVA on k groups you will need at least k+1 participants. This is the technical minimum requirement.
When are unequal sample sizes are and are not a problem in ANOVA?
So if you have equal variances in your groups and unequal sample sizes, no problem. If you have unequal variances and equal sample sizes, no problem. The only problem is if you have unequal variances and unequal sample sizes.
When is the sample size of an experiment not equal?
Whether by design, accident, or necessity, the number of subjects in each of the conditions in an experiment may not be equal. For example, the sample sizes for the “Bias Against Associates of the Obese” case study are shown in Table 15.6. 1.
Why do we need equal sample sizes in randomised trials?
We cringe at the pervasive notion that a randomised trial needs to yield equal sample sizes in the comparison groups. Unfortunately, that conceptual misunderstanding can lead to bias by investigators who force equality, especially if by non-scientific means.
What is the statistical advantage of equal sample sizes?
Additionally, while equal-sized groups maximise statistical power, the advantage is easily overstated. An experiment with 30+30 participants has a 76% chance to detect a systematic difference of 0.7 standard deviations between the two group means; for an experiment with 20+40 participants, this probability is 71%.