The paper studies four methods about selection of independent variables in multivariate analysis. In general condition, advanced statistical method and backward statistical method could not obtain the best subset of i...The paper studies four methods about selection of independent variables in multivariate analysis. In general condition, advanced statistical method and backward statistical method could not obtain the best subset of independent variables. It is possibly affected by the orders of variables or associations among variables. When multicollinearity is presented in a set of explanatory variables-abnormal state, it is not effective to use the method, although stepwise regression and optimum selecting method of total subsets is widely used.;According to this case, the paper proposes a new method which combines deleting variables with ingredient analysis and is used in research and science practically.;The important characteristic of this paper is that it gives some examples to support each conclusion.展开更多
文摘The paper studies four methods about selection of independent variables in multivariate analysis. In general condition, advanced statistical method and backward statistical method could not obtain the best subset of independent variables. It is possibly affected by the orders of variables or associations among variables. When multicollinearity is presented in a set of explanatory variables-abnormal state, it is not effective to use the method, although stepwise regression and optimum selecting method of total subsets is widely used.;According to this case, the paper proposes a new method which combines deleting variables with ingredient analysis and is used in research and science practically.;The important characteristic of this paper is that it gives some examples to support each conclusion.
