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Abstract
For general linear models with normally distributed random errors, the probability of a Type II error decreases exponentially as a function of sample size. This potentially rapid decline reemphasizes the importance of performing power calculations.
Keywords
asymptotic relative efficiency,
experimental design,
Hodges-Lehmann efficiency,
linear models,
Mills’ ratio,
minimum detectable difference,
noncentral F,
normal tail,
Pitman efficiency,
power,
sample size
Citation
Verrill, Steve P.; Durst, Mark. 2005. The decline and fall of Type II error rates. American Statistician. 59(4): 287-291.