Dummy Variable Multiple Regression Analysis of Matched Samples

Customer Satisfaction Measurement with Dummy Variable Regression with Constraints

A new method for measuring and analyzing customer satisfaction is presented in this paper. The mathematical model expresses the fundamental relationship between criteria and the overall utility which expresses the global customer satisfaction. The procedure used to estimate the basic model is dummy variable regression with constraints. The method can very simply consider nonmetric data by codif...

Multiple regression analysis of twin data obtained from selected samples.

The multiple regression analysis of twin data in which a cotwin's score is predicted from that of a proband (the member of a twin pair selected because of a deviant score) and the coefficient of relationship provides a powerful test of genetic etiology (DeFries and Fulker: Behav Genet 15:467-473, 1985). Moreover, when an augmented model containing an interaction term is fitted to the same data ...

Multiple Regression of Fuzzy-Valued Variable

In fuzzy domain, a variable (vague linguistic term) often depends not only on a single variable but on more then one variables. In such a situation multiple regression analysis is more appropriate than simple regression analysis involving one independent variable. This paper introduces fuzzy multiple regression equations of fuzzy sets those are treated as a variable with certain values assigned...

Dummy variable (statistics) - Wikipedia, the free encyclopedia

In statistics and econometrics, particularly in regression analysis, a dummy variable (also known as an indicator variable) is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome.[1] For example, in econometric time series analysis, dummy variables may be used to indicate the occurrence of wars, or major strik...

misconceptions about nested studies, matched analysis, significancy, power, normality and multivariate regression analysis