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From |
Ivan Png <iplpng@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Mata: Calculating conditional expectation |

Date |
Tue, 23 Apr 2013 11:45:51 +0800 |

Many thanks to Statalist members for their previous help on constructing the matrix. To recall, my dependent variable is categorical: Mobility = 1 if inventor changed employer, else = 0. I'm investigating the effect of classification error. Obviously, this cannot be classical. Let Y = true mobility and Z = recorded mobility. If Y = 0 and Z = 1, then error = -1, while if Y = 1 and Z = 0, error = +1. Meyer and Mittag, U of Chicago (2012) characterize the bias as N(X'X)^{-1} [ Pr( Y = 0 & Z = 1) E(X : Y = 0 & Z = 1) - Pr(Y = 1 & Z = 0) E(X : Y = 1 & Z = 0) ]. I have a benchmark data set with both the true and inaccurate mobility data, and would like to compute the bias. So, I need to compute the conditional expectations, E(X : Y = 0 & Z = 1) and E(X : Y = 1 & Z = 0), and then weight by the probabilities, take the difference, and pre-multiply by N(X'X)^{-1}. My idea: . keep if Y = 0 & Z = 1 . mata : F = mean(X) . mata : mata matsave filename and repeat for Y = 1 & Z = 0. But, sadly, I don't how to proceed. How to combine the original data with the two new files containing the conditional expectations, and then going back to MATA to calculate the bias. Grateful to Statalisters for help. -- Best wishes Ivan Png Skype: ipng00 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

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