Multiple regression: Difference between revisions
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gen y=1.5+0.8*x1-0.7*x2+1.1*x3-1.7*x4+rnormal()</lang> |
gen y=1.5+0.8*x1-0.7*x2+1.1*x3-1.7*x4+rnormal()</lang> |
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Now, use the regress command: |
Now, use the '''[https://www.stata.com/help.cgi?regress regress]''' command: |
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<lang stata>reg y x*</lang> |
<lang stata>reg y x*</lang> |
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------------------------------------------------------------------------------</pre> |
------------------------------------------------------------------------------</pre> |
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The regress command also sets a number of '''ereturn''' values, which can be used by subsequent commands. The coefficients and their standard errors also have a special syntax: |
The regress command also sets a number of '''[https://www.stata.com/help.cgi?ereturn ereturn]''' values, which can be used by subsequent commands. The coefficients and their standard errors also have a special syntax: |
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<lang stata>. di _b[x1] |
<lang stata>. di _b[x1] |
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.06978623</lang> |
.06978623</lang> |
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One can compute the covariance matrix of the estimates, the predicted values, residuals... See '''estat''', '''predict''', '''estimates''', '''margins''' and others. Here are a few examples: |
One can compute the covariance matrix of the estimates, the predicted values, residuals... See '''[https://www.stata.com/help.cgi?estat estat]''', '''[https://www.stata.com/help.cgi?predict predict]''', '''[https://www.stata.com/help.cgi?estimates estimates]''', '''[https://www.stata.com/help.cgi?margins margins]''' and others. Here are a few examples: |
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<lang stata>. estat ic |
<lang stata>. estat ic |
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. predict yhat, xb |
. predict yhat, xb |
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. predict r, r</lang> |
. predict r, r</lang> |
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=={{header|Tcl}}== |
=={{header|Tcl}}== |
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