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From |
Nick Winter <nwinter@virginia.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: calculating effect sizes when using svy command |

Date |
Tue, 07 Dec 2010 16:18:22 -0500 |

http://www.stata.com/support/faqs/stat/survey.html

-Nick Winter On 12/7/2010 4:11 PM, Vogt, Dawne wrote:

Thanks. So it sounds like I can take the square root of the R squared value to get the correlation coefficient for a regression with 1 predictor. But how do I get effect size indicators (preferably in the form of correlation coefficients) for each predictor in a regression with multiple predictors? -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steven Samuels Sent: Tuesday, December 07, 2010 4:00 PM To: statalist@hsphsun2.harvard.edu Subject: Re: st: calculating effect sizes when using svy command -- - I should have added: The relation of (partial) r-squares to t- statistics holds only for ordinary least squares, not for the estimation formulas of survey regression. So, neither of your calculated r's is correct. Steve On Dec 7, 2010, at 3:31 PM, Vogt, Dawne wrote: I have two questions related to calculating effect sizes using svyreg (pweights): First, when doing unweighted regressions in SPSS, I like to provide effect sizes for each predictor by calculating a correlation coefficient value (r) from the t values provided in the output. I like using r because it is easy for most people to interpret. Can I do the same using svyreg output? My second question is related to the first. Since there is no correlation option under the svy commands, I have been computing regressions of Y on X and X and Y and using the largest p value of the two sets of results, as recommended elsewhere. I've having trouble figuring out how to convert the results provided in the output to a correlation coefficient though. I noticed that the r value I get by taking the square root of the R squared is different from my own hand calculation of r derived from the t value provided in the regression output [sqrt of (t squared divided by t squared + df). I'm not sure which r is correct (or if either of them are correct). Thanks in advance for any guidance others may be able to offer. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

-- -------------------------------------------------------------- Nicholas Winter 434.924.6994 t Assistant Professor 434.924.3359 f Department of Politics nwinter@virginia.edu e University of Virginia faculty.virginia.edu/nwinter w S385 Gibson Hall, South Lawn * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: calculating effect sizes when using svy command***From:*Steven Samuels <sjsamuels@gmail.com>

**References**:**st: calculating effect sizes when using svy command***From:*"Vogt, Dawne" <Dawne.Vogt@va.gov>

**Re: st: calculating effect sizes when using svy command***From:*Steven Samuels <sjsamuels@gmail.com>

**RE: st: calculating effect sizes when using svy command***From:*"Vogt, Dawne" <Dawne.Vogt@va.gov>

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