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From | Steve Samuels <sjsamuels@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re:st: margins, vce(unconditional) after estimation with replicate weights |
Date | Tue, 6 Nov 2012 14:01:37 -0500 |
Sam Schulhofer-Wohl <sschulh1.work@gmail.com> wrote on Nov. 5: I get a syntax error message, r(459), when I try to use -margins, vce(unconditional)- after estimating a linear regression in survey data with SDR or BRR weights. The manual entry for -margins- (p. 1077, Version 12) states that vce(unconditional) uses the linearized variance matrix, so, by implication, can't be used directly with replicate-based standard errors. I forwarded Sam's post to Stata Technical support. Isabelle Canette of StataCorp, responded and demonstrated how to write a wrapper program to feed into -svy: brr-, -svy: sdr-, or -svy: jackknife-. Steve The option -vce(unconditional)- for -margins- uses the linearized variance estimator to compute the standard errors. Therefore, it can't be used with -svy brr-. If you want to compute standard errors for your margins based on balanced repeated replications, you can write a wrapper for your command and for -margins- and call it with -svy brr-, for example: use nhanes2brr, clear capture program drop mymargins program mymargins, eclass version 12 syntax [anything] [if] [iw pw] if "`weight'" != "" { local wgtexp "[`weight' `exp']" } set buildfvinfo on logit highbp weight i.region `if' `wgtexp' margins region, post end webuse nhanes2brr, clear svy brr _b: mymargins Notice that the program (-mymargins-) needs to accept weights. Also, the line set buildfvinfo on is set so -margins- checks for estimability. It is usually set on, but when using replication methods is set off because it increases the computation time, so you need to set it on. The option -post- for -margins- posts the results on e(b), so they can be used by -svy brr-. -----Begin Original Message----- Re: st: margins, vce(unconditional) after estimation with replicate weights From: Sam Schulhofer-Wohl <sschulh1.work@gmail.com> I get a syntax error message, r(459), when I try to use -margins, vce(unconditional)- after estimating a linear regression in survey data with SDR or BSR weights. There is no error when I don't specify vce(unconditional) or when I don't use replicate weights. Some examples are below. I think this may be the same problem that Eva Chang mentioned at http://www.stata.com/statalist/archive/2012-09/msg01007.html, but I don't see any replies to Eva's message. I also can't find any indication in the manual that -margins, vce(unconditional)- is incompatible with replicate weights. Any suggestions on how to avoid this error? -- Sam Schulhofer-Wohl Senior Economist Research Department Federal Reserve Bank of Minneapolis 90 Hennepin Ave. Minneapolis MN 55480-0291 wohls@minneapolisfed.org *example of the error using SDR weights . webuse ss07ptx . svyset pweight: pwgtp VCE: sdr MSE: off sdrweight: pwgtp1 pwgtp2 pwgtp3 pwgtp4 pwgtp5 pwgtp6 pwgtp7 pwgtp8 pwgtp9 pwgtp10 pwgtp11 pwgtp12 pwgtp13 pwgtp14 pwgtp15 pwgtp16 pwgtp17 pwgtp18 pwgtp19 pwgtp20 pwgtp21 pwgtp22 pwgtp23 pwgtp24 pwgtp25 pwgtp26 pwgtp27 pwgtp28 pwgtp29 pwgtp30 pwgtp31 pwgtp32 pwgtp33 pwgtp34 pwgtp35 pwgtp36 pwgtp37 pwgtp38 pwgtp39 pwgtp40 pwgtp41 pwgtp42 pwgtp43 pwgtp44 pwgtp45 pwgtp46 pwgtp47 pwgtp48 pwgtp49 pwgtp50 pwgtp51 pwgtp52 pwgtp53 pwgtp54 pwgtp55 pwgtp56 pwgtp57 pwgtp58 pwgtp59 pwgtp60 pwgtp61 pwgtp62 pwgtp63 pwgtp64 pwgtp65 pwgtp66 pwgtp67 pwgtp68 pwgtp69 pwgtp70 pwgtp71 pwgtp72 pwgtp73 pwgtp74 pwgtp75 pwgtp76 pwgtp77 pwgtp78 pwgtp79 pwgtp80 Single unit: missing Strata 1: <one> SU 1: <observations> FPC 1: <zero> . svy: reg agep i.sex (running regress on estimation sample) SDR replications (80) ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 .................................................. 50 .............................. Survey: Linear regression Number of obs = 230817 Population size = 23904380 Replications = 80 Wald chi2(1) = 1515.50 Prob > chi2 = 0.0000 R-squared = 0.0021 ------------------------------------------------------------------------------ | SDR agep | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- 2.sex | 1.994219 .0512265 38.93 0.000 1.893817 2.094621 _cons | 33.24486 .0470986 705.86 0.000 33.15255 33.33717 ------------------------------------------------------------------------------ . margins sex, vce(unconditional) vce(sdr) is not supported something that should be true of your data is not r(459); *margins works fine if I don't specify vce(unconditional) . margins sex Adjusted predictions Number of obs = 230817 Model VCE : SDR Expression : Linear prediction, predict() ------------------------------------------------------------------------------ | Delta-method | Margin Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- sex | 1 | 33.24486 .0470986 705.86 0.000 33.15255 33.33717 2 | 35.23908 .0386398 911.99 0.000 35.16335 35.31481 ------------------------------------------------------------------------------ *using the BSR equivalent of SDR doesn't help . svyset [pw=pwgtp], bsrweight(pwgtp?*) bsn(4) vce(bootstrap) pweight: pwgtp VCE: bootstrap MSE: off bsrweight: pwgtp1 pwgtp2 pwgtp3 pwgtp4 pwgtp5 pwgtp6 pwgtp7 pwgtp8 pwgtp9 pwgtp10 pwgtp11 pwgtp12 pwgtp13 pwgtp14 pwgtp15 pwgtp16 pwgtp17 pwgtp18 pwgtp19 pwgtp20 pwgtp21 pwgtp22 pwgtp23 pwgtp24 pwgtp25 pwgtp26 pwgtp27 pwgtp28 pwgtp29 pwgtp30 pwgtp31 pwgtp32 pwgtp33 pwgtp34 pwgtp35 pwgtp36 pwgtp37 pwgtp38 pwgtp39 pwgtp40 pwgtp41 pwgtp42 pwgtp43 pwgtp44 pwgtp45 pwgtp46 pwgtp47 pwgtp48 pwgtp49 pwgtp50 pwgtp51 pwgtp52 pwgtp53 pwgtp54 pwgtp55 pwgtp56 pwgtp57 pwgtp58 pwgtp59 pwgtp60 pwgtp61 pwgtp62 pwgtp63 pwgtp64 pwgtp65 pwgtp66 pwgtp67 pwgtp68 pwgtp69 pwgtp70 pwgtp71 pwgtp72 pwgtp73 pwgtp74 pwgtp75 pwgtp76 pwgtp77 pwgtp78 pwgtp79 pwgtp80 bsn: 4 Single unit: missing Strata 1: <one> SU 1: <observations> FPC 1: <zero> . svy: reg agep i.sex (running regress on estimation sample) Bootstrap replications (80) ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 .................................................. 50 .............................. Survey: Linear regression Number of obs = 230817 Population size = 23904380 Replications = 80 Wald chi2(1) = 1515.50 Prob > chi2 = 0.0000 R-squared = 0.0021 ------------------------------------------------------------------------------ | Observed Bootstrap Normal-based agep | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- 2.sex | 1.994219 .0512265 38.93 0.000 1.893817 2.094621 _cons | 33.24486 .0470986 705.86 0.000 33.15255 33.33717 ------------------------------------------------------------------------------ . margins sex, vce(unconditional) vce(bootstrap) is not supported something that should be true of your data is not r(459); *no problem if I don't use replicate weights . svyset [pw=pwgtp] pweight: pwgtp VCE: linearized Single unit: missing Strata 1: <one> SU 1: <observations> FPC 1: <zero> . svy: reg agep i.sex (running regress on estimation sample) Survey: Linear regression Number of strata = 1 Number of obs = 230817 Number of PSUs = 230817 Population size = 23904380 Design df = 230816 F( 1, 230816) = 350.93 Prob > F = 0.0000 R-squared = 0.0021 ------------------------------------------------------------------------------ | Linearized agep | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- 2.sex | 1.994219 .1064544 18.73 0.000 1.785571 2.202867 _cons | 33.24486 .0730543 455.07 0.000 33.10168 33.38805 ------------------------------------------------------------------------------ . margins sex, vce(unconditional) Adjusted predictions Number of obs = 230817 Expression : Linear prediction, predict() ------------------------------------------------------------------------------ | Linearized | Margin Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- sex | 1 | 33.24486 .0730543 455.07 0.000 33.10168 33.38805 2 | 35.23908 .0774313 455.10 0.000 35.08732 35.39084 ------------------------------------------------------------------------------ * * 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/ -----End Original Message----- * * 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/