help reganat
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Title

    reganat --   Graphical inspection of linear multivariate models


Syntax

        reganat depvar varlist [if] [in] [, options]

    options               Description
    -------------------------------------------------------------------------
    Options
      dis(varlist)        graphs only the variables in varlist and omits the
                            rest
      biline              plots a regression line for the bivariate linear
                            model
      biscat              plots a scatterplot for the bivariate linear model
      reg                 displays the results for the estimation of the
                            multivariate model
      nolegend            prevents the legend to be displayed
      nocovlist           prevents the list of covariates to be displayed
      scheme(scheme)      specifies the graphical scheme
    -------------------------------------------------------------------------
    by is not allowed.


Description

    reganat is a graphical tool for inspecting the effect of a covariate on a
    dependent variable in the context of multivariate OLS estimation.  The
    name is an acronym for the expression regression anatomy, a result in
    OLS' algebra originally due to Frisch and Waugh (1933) and recently
    revived by Angrist and Pischke's Mostly Harmless Econometrics (2009).  In
    a bivariate regression model Y = bx1 + g, the graphical inspection of the
    scatterplot provides useful information on the relation between the
    independent variable x1 and the dependent variable Y, but can be highly
    misleading when the underlying real model is multivariate of the type Y =
    X'B + e where X' includes also x1.  In general, the OLS multivariate
    estimator is not equivalent to an OLS estimator obtained using a separate
    regression on each independent variable since correlation among
    independent variables must be accounted for.  Angrist and Pischke (2009)
    show that in a multivariable model, the regression parameter for a given
    regressor is the bivariate slope coefficient for the corresponding
    regressor after partialling out all other covariates.  Accordingly, this
    command displays a table of scatterplots, with the dependent variable
    plotted against the independent variable net of any linear correlation
    with the other independent variables.  This combined graph can be helpful
    when inspecting the data for outliers, nonlinearities, and other
    modelling issues.

Options

        +---------+
    ----+ Options +----------------------------------------------------------

    dis(varlist) specifies that the sense only the covariates included in 
        varlist will be plotted in the graph.  Nonetheless, the other
        variables still work as controls.

    biline specifies that on the graph will also be displayed the fitted
        regression line for the linear model Y = x1 + g, where x1 is the
        variable of interest.

    biscat specifies that on the graph will also be displayed the scatterplot
        for (Y,x1), where x1 is the variable of interest.

    reg displays the numerical results for the estimation of the multivariate
        model Y = X'B + e.

    nolegend prevents the legend to be displayed.

    nocovlist prevents the list of covariates to be displayed.

    scheme(graphical scheme) can be used to specify the graphical scheme to
        be applied to the composite graph. By default, the command uses the
        sj scheme.

Examples

    Setup
        . sysuse auto, clear

    Obtain a combined graph of the effect of several regressors
        . reganat price length weight headroom mpg

    Obtain a combined graph of the effect of a subset of the regressors,
    along with scatterplots and fitted line for the univariate models
        . reganat price length weight headroom mpg, dis(weight length) biline

References

    Angrist, J. and Pischke, J. S. (2009) Mostly Harmless Econometrics.
        Princeton University Press.

    Frisch, R. and Waugh, F. W. (1933) Partial Time Regression as Compared
        with Individual Trends. Econometrica 1: 387-401.

Acknowledgment

    The author wishes to express his deep gratitude to Joshua Angrist for a
        number of insights and advices which have greatly enhanced the scope
        and the reliability of this command.

Author

    Valerio Filoso, Department of Economics, University of Naples "Federico
    II", Italy.