Can you run ANOVA with unequal sample sizes?
The short answer: Yes, you can perform a one-way ANOVA when the sample sizes are not equal. Equal sample sizes is not one of the assumptions made in an ANOVA.
Why can unequal sample sizes be a problem for ANOVA?
Unequal sample sizes can lead to: Unequal variances between samples, which affects the assumption of equal variances in tests like ANOVA. Having both unequal sample sizes and variances dramatically affects statistical power and Type I error rates (Rusticus & Lovato, 2014). A general loss of power.
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 ANOVA with unequal variance?
If your groups have unequal variances, your results can be incorrect if you use the classic test. On the other hand, Welch’s ANOVA isn’t sensitive to unequal variances.
Can I use ANOVA for unbalanced data?
“Standard ANOVA” does not exist for unbalanced designs However, when your design is unbalanced they don’t give the same answers. Furthermore, they are not all equally appropriate to every situation: some methods will be more appropriate to your situation than others.
Can you run at test with unequal sample sizes?
Even though you can perform a t-test when the sample size is unequal between two groups, it is more efficient to have an equal sample size in two groups to increase the power of the t-test.
Can you compare unequal sample sizes?
Even though you can perform a t-test when the sample size is unequal between two groups, it is more efficient to have an equal sample size in two groups to increase the power of the t-test. Welch’s t-test is for unequal variance data.