Multiple regression analysis
published: Aug. 7, 2009, recorded: August 2009, views: 7784
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The course starts with a discussion of the logic of the multivariate regression model and the central assumptions underlying the ordinary least squares approach. Then it proceeds with testing for the adequacy of the assumptions and suitable corrections and extensions to the estimation techniques in the context of cross-sectional data. Particular emphasis will be laid on multicollinearity and heteroskedasticity. The second part of the course focuses on functional form. Models that are nonlinear in variables but linear in parameters, dummy variables, and interaction terms will be covered. In the third part, various topics arising with special data are covered. Firstly, the analysis of binary dependent variables is introduced. Secondly, problems involved with the analysis of longitudinal data, i.e. time series and panel data, are discussed, with special emphasis on autocorrelation. The course assumes proficiency with descriptive and inferential statistics at the level of test theory and bivariate regression analysis.
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