Do sample sizes have to be equal?

Do sample sizes have to be equal?

A sample size imbalance isn’t a tell-tale sign of a poor study. You don’t need equal-sized groups to compute accurate statistics. If the sample size imbalance is due to drop-outs rather than due to design, simple randomisation or technical glitches, this is something to take into account when interpreting the results.

Can you do two way ANOVA with unequal sample sizes?

According to Keppel (1993), there is no good rule of thumb for how unequal the sample sizes need to be for heterogeneity of variance to be a problem. 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.

Can you do two way Anova with unequal sample sizes?

Why are sample sizes unequal in table 15.6?

Weighted and unweighted means will be explained using the data shown in Table 15.6. 4. Here, Diet and Exercise are confounded because 80 % of the subjects in the low-fat condition exercised as compared to 20 % of those in the high-fat condition. However, there is not complete confounding as there was with the data in Table 15.6.

Are there unequal sample sizes for mixed ANOVA?

However, all these different groups have different numbers of examinees. The first group has 490 participants, the second group has 1919 participants and the third group has 529 participants. Thus, I can say that I have unequal sample sizes for Mixed ANOVA.

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.