Causal ModelingA substantially revised and updated edition of an earlier volume in the series. Asher presents a number of techniques of causal modelling, beginning with the work of Simon and Blalock, and moving on to recursive and non-recursive path estimation. Special attention is given to a number of problems in the causal analysis of data, with illustrations from studies in political socialization and voting behaviour. |
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2SLS arrow diagram assumptions basic Blalock causal analysis causal modeling collinearity compound paths confounding variables correlation coefficients covariance decomposition direct discussed endogenous estimation technique exactly identified example exogenous variables expected value explanatory variables Figure Goldberg Hence impact independent variables indirect effects influence instrumental variable interval linear matrix of coefficients measured variables Miller and Stokes multicollinearity nonrecursive models nonzero Note observations obtained omitted one's order condition ordinary least squares ordinary regression overidentified panel data partisanship party identification path analysis path estimation predictions problem random measurement error reader reciprocal linkages recursive model recursive system regression analysis regression coefficients representative's residual correlations residual path coefficient residual terms residual variables respondent's sample Simon Simon-Blalock technique spurious standard deviation statistical Stokes model structural equations student performance substantive system of equations three variables three-variable uncorrelated underidentified unexplained variance unknowns unstandardized coefficients variance Wright's rules X₁ and X2 X2 and X3 yield zero
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Page 95 - Politicization of the Electorate in France and the United States', in A. Campbell, et al.. Elections and the Political Order, New York, 1966.