%0 Journal Article
	%A Sin Yin Teh and  Abdul Rahman Othman and  Michael Boon Chong Khoo
	%D 2010
	%J International Journal of Mathematical and Computational Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 38, 2010
	%T Dichotomous Logistic Regression with Leave-One-Out Validation
	%U https://publications.waset.org/pdf/2393
	%V 38
	%X In this paper, the concepts of dichotomous logistic
regression (DLR) with leave-one-out (L-O-O) were discussed. To
illustrate this, the L-O-O was run to determine the importance of the
simulation conditions for robust test of spread procedures with good
Type I error rates. The resultant model was then evaluated. The
discussions included 1) assessment of the accuracy of the model, and
2) parameter estimates. These were presented and illustrated by
modeling the relationship between the dichotomous dependent
variable (Type I error rates) with a set of independent variables (the
simulation conditions). The base SAS software containing PROC
LOGISTIC and DATA step functions can be making used to do the
DLR analysis.
	%P 296 - 305