多變量群組標準化效用信賴區間之樣本數

Abstract

本研究利用信賴區間對於多變量群組標準化效用的估計提供了兩種精確的樣本數計算方式。利用信賴區間法可以提供更多的參數資訊，在估計樣本數時一般都希望信賴區間越窄越好，但要在維持信賴區間狹窄的情況下同時擁有高度的準確度，則必須要有足夠的樣本數。在統計軟體的幫助下利用隨機模擬的方式，產生多變量近似的抽樣分配，並透過反轉信賴區間找出非中心分配參數的上下界，以找出效果量的信賴區間。最後討論在不同參數組合的條件下，計算達到信賴水準所需要的最適樣本數。

The confidence interval width was expected to be narrow when estimating the sample size. The enough sample size is necessary to maintain the confidence interval narrow with high accuracy. This article provides the sample size calculation for precise confidence interval of standardized effect in one-way MANOVA. Researchers can produce the multivariate approximate sample distribution with the approach of stochastic simulation, and get the upper limit and lower limit of noncentral parameters by the inversion confidence interval principle. Finally, using the confidence interval of effect sizes to calculate a appropriate sample size with different combination of population parameters under required confidence level.