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The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square distribution under H[subscript a]. However, with either violation of normality or not a large enough sample size, both empirical and analytical results indicate that the chi-square distribution assumptions are not realistic and consequently methods of power analysis based on such assumptions are not valid. This article describes a Monte Carlo (MC) method for power analysis. A measure of effect size for characterizing the power property of different rescaled statistics is also provided. Robust methods are proposed to increase the power of T[subscript ml] and other statistics. Simulation results show that the MC method reliably controls Type I errors and robust estimation methods effectively increase the power, and their combination is thus recommended for conducting power analysis in SEM.

1Boy Crusoe

By Allan Eric

Also published as" A Yankee Crusoe" . A 15 year old hard working and studious farm boy finds the lure of adventure on the seas as a merchant seaman more than he can resist. This is his story. " I was born in a little town in the State of Maine, near the close of the Civil War. My boyhood life did not differ materially from that of the average farmer's son in the remote country districts of New England--except, perhaps, that I read more and thought more. Hard work on the rugged soil, two terms each year in the little yellow country schoolhouse, a day's fishing now and then filled the early years of my life full to over-flowing. " What he gets is enough excitement and adventure to overflow his wildest dreams. How he experiences disaster and uses his wits and knowledge to overcome every problem makes for a great read. - Summary by Phil Chenevert