Multiple Regression Analysis
A statistical procedure for examining the linear relationship between a dependent variable and several independent variables.
(Brians, Craig Leonard, Lars B. Willnat, Jarol B. Manheim and Richard C. Rich. 2008. Empirical Political Analysis: Quantitative and Qualitative Research Methods, 7th ed. New York: Pearson.)
Multiple regression analysis is a technique that allows additional factors to enter the analysis separately so that the effect of each can be estimated. It is valuable for quantifying the impact of various simultaneous influences upon a single dependent variable. Further, because of omitted variables bias with simple regression, multiple regression is often essential even when the investigator is only interested in the effects of one of the independent variables.
Multiple regression is a way of attempting to match on pairs of individuals who are similar in every way expect that they differ in the outcome of interest. In theory, when the data are available on an omitted variable, the solution to the omitted variable bias is to include the omitted variable in the regression. In practice, however, deciding whether to include a particular variable can be difficult and requires judgement.