Efficiency of Adaptive Methods Using Simulated Alpha Skew Normal Two-Stage Data

Two-stage sampling improves variances for estimators of means and regression coefficients because of intra-class homogeneity. To choose the appropriate way of allowing for clustering using sample data, an adaptive method will be evaluated in this paper based on testing the null hypothesis that the variance component of the random effect is zero. Rejecting the null hypothesis, clustering will be allowed for in variance estimation; otherwise clustering will be ignored. The data will be simulated from alpha-skew normal distribution with different values of the parameter