[Python] Building a demand model and correcting for reverse causation with 2-stage least squares regression (OLS in statsmodels, IV2SLS in linearmodels)
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Updated
Jan 19, 2022 - HTML
[Python] Building a demand model and correcting for reverse causation with 2-stage least squares regression (OLS in statsmodels, IV2SLS in linearmodels)
This regression analysis is used to predict the LBM (lean body mass) of athletes and whether or not there is a difference in LBM for males and females. The analysis uses the following explanatory variables: Sex (0: males, 1: females), Ht (height in cm), Wt (weight in kg), WCC (white cell count), Hg (hemoglobin) amnd Hc (hematocrit).
Estimating the effect of Covid-19 Precautions on traffic accidents in Taoyuan City with Regression Discontinuity Design using Python PanelOLS model.
Artificial Intelligence with Python (using Machine Learning)
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