Non-random Exogenous Variables in Path Analysis

Path analysis requires that exogenous and residual variables not be correlated. An alternative to assuming the two to be independent is to treat the exogenous variables as fixed or non-random. Examination of path models, however, reveals that the usual standardized path coefficients are biased and inconsistent when exogenous variables are considered fixed. At the same time, the path coefficient divided by the residual term is a large-sample unbiased estimate of the true coefficient. Variants of this basic transformation are discussed and an empirical example is included

Econometrics · Path (computing · Path analysis (statistics · Statistics · Advanced Statistical Modeling Techniques · Computer Science · Mathematics · Optimal Experimental Design Methods · Psychology

• On the evaluation of causal models

  Open Access•David A Specht•Social Science Research•1975

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• Non-Random Exogenous Variables in Path Analysis

  Lawrence S Mayer•American Sociological Review•1974

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• Non-Random Exogenous Variables in Path Analysis

  William T Bielby, James R Kluegel•American Sociological Review•1974

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• Priority Position of Communication in the African Development Process

  David O Edeani•African Studies Review•1980

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• The Method of Path Coefficients

  Open Access•Sewall Wright•The Annals of Mathematical…•1934

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• Problems in Path Analysis and Causal Inference

  D R Heise•Sociological Methodology•1969

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• Principles of Path Analysis

  K C Land•Sociological Methodology•1969

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• Causal Inferences, Closed Populations, and Measures of Association

  Open Access•Hubert M Blalock•American Political Science Review•1967

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• Path Analysis

  Otis Dudley Duncan•American Journal of Sociology•1966

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