Factor analysis: predicted variance and covariance of indicators - part 2 @SpartacanUsuals
Factor analysis: predicted variance and covariance of indicators - part 2  @SpartacanUsuals
Uploaded February 2014 | Updated September 2026, 1 hour ago
This video provides an example as to how we can use the model estimated variance-covariance matrices for the factors and errors in order to derive the variance and covariance of indicators. Check out ben-lambert.com/econometrics-course-problem-sets-and-data for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: ben-lambert.com/bayesian Accompanying this series, there will be a book: amazon.co.uk/gp/product/1473916364/ref=pe_3140701_247401851_em_1p_0_ti
Factor analysis: predicted variance and covariance of indicators - part 2Bayesian statistics syllabusDerivation of variance-covariance matrix in factor analysis - part 1Factor Analysis - an introductionSimultaneous equation models - parameter identificationCauchy Schwarz Inequality   Proof   part 2Maximum Likelihood estimation of Logit and ProbitMaximum likelihood estimation of factor analysis models - fitting functionThe conditional independence assumption - intuitionGeometric intepretation of least squares - orthogonal projectionFree econometrics lectures channel advertisement - new and improved ad!GLS estimators in matrix form - part 3
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Factor analysis: predicted variance and covariance of indicators - part 2

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