A Review of the Behrens–Fisher Problem and Some of its Analogs
Does the Same Size Fit All?
DOI:
https://doi.org/10.57805/revstat.v17i4.281Keywords:
the Behrens–Fisher problem, the beta-binomial model, the negative binomial model, the Weibull modelAbstract
The traditional Behrens–Fisher (B-F) problem is to test the equality of the means µ1 and µ2 of two normal populations using two independent samples, when the quotient of the population variances is unknown. Welch [43] developed a frequentist approximate solution using a fractional number of degrees of freedom t-distribution. We make a a comprehensive review of the existing procedures, propose new procedures, evaluate these for size and power, and make recommendation for the B-F and its analogous problems for non-normal populations. On the other hand, we investigate and answer a question: does the same size fit all all, i.e. is the t-test with Welch’s degree of freedom correction robust enough for the B-F problem analogs, and what sample size is appropriate to use a normal approximation to the Welch statistic.
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