Dichotomous logistic regression with leave-one-out validation

被引：0

作者：

Teh, Sin Yin ^{[1
]}

Othman, Abdul Rahman ^{[2
]}

Khoo, Michael Boon Chong ^{[1
,3
,4
]}

机构：

[1] School of Mathematical Sciences, USM, Malaysia

[2] Institute of Graduate Studies and an associate, School of Distance Education, Universiti Sains Malaysia (USM), School of Pharmacy, Malaysia

[3] American Society for Quality, United States

[4] Malaysian Mathematical Society, Malaysia

来源：

World Academy of Science, Engineering and Technology | 2010年 / 62卷

关键词：

Error analysis;

D O I：

暂无

中图分类号：

O212 [数理统计];

学科分类号：

摘要：

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.

引用

页码：1001 / 1010

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