L models and multiple regressions designs

Gini's Multiple Regressions Gini's Multiple Regressions

Two regression methods can be interpreted as based on Gini's mean difference (GMD). One relies on a weighted average of slopes defined between adjacent observations and the other is based on minimization of the GMD of the errors. The properties of the former approach are investigated in a multiple regression framework. These estimators have representations that resemble the OLS estimators, and ...

QSAR models to predict physico-chemical Properties of some barbiturate derivatives using molecular descriptors and genetic algorithm- multiple linear regressions

In this study the relationship between choosing appropriate descriptors by genetic algorithm to the Polarizability (POL), Molar Refractivity (MR) and Octanol/water Partition Coefficient (LogP) of barbiturates is studied. The chemical structures of the molecules were optimized using ab initio 6-31G basis set method and Polak-Ribiere algorithm with conjugated gradient within HyperChem 8.0 environ...

Estimation of Soil Infiltration in Agricultural and Pasture Lands using Artificial Neural Networks and Multiple Regressions

Common methods to determine the soil infiltration need extensive time and are expensive. However, the existence of non-linear behaviors in soil infiltration makes it difficult to be modeled. With regards to the difficulties of direct measurement of soil infiltration, the use of indirect methods toestimate this parameter has received attention in recent years. Despite the existence of various th...

Salary : Issues in Multiple Regressions

Inconsistency Between Univariate and Multiple Logistic Regressions

Logistic regression is a popular statistical method in studying the effects of covariates on binary outcomes. It has been widely used in both clinical trials and observational studies. However, the results from the univariate regression and from the multiple logistic regression tend to be conflicting. A covariate may show very strong effect on the outcome in the multiple regression but not in t...