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From |
"Feiveson, Alan H. (JSC-SK311)" <alan.h.feiveson@nasa.gov> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Calculation of covariance matrix for unbalanced sample? |

Date |
Thu, 3 Nov 2011 07:51:32 -0500 |

Of course, there is no guarantee such a matrix will be positive (semi)definite. If you want that, you need to make further assumptions such as multivariate normal and then use maximum likelihood, multiple imputation or Bayesian methods. Al -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Cameron McIntosh Sent: Thursday, November 03, 2011 7:44 AM To: STATA LIST Subject: RE: st: Calculation of covariance matrix for unbalanced sample? Nick, Stas Just curious. What's the estimation method being applied below: EM, FIML, MI...? Thanks, Cam > From: n.j.cox@durham.ac.uk > To: statalist@hsphsun2.harvard.edu > Date: Thu, 3 Nov 2011 12:30:22 +0000 > Subject: RE: st: Calculation of covariance matrix for unbalanced sample? > > -makematrix- (SJ) can do this. But it's better to use Stas' custom code, which is more direct. > > Nick > n.j.cox@durham.ac.uk > > Stas Kolenikov > > I don't think there's any. I vaguely remember a discussion some time > back on the list about this. Here's the basic outline from scratch: > > program define pwcovmat, rclasssyntax varlistunab vars : > `varlist'local p : word count `vars'tempname Covmatrix `Cov' = > J(`p',`p',.)matrix rownames `Cov' = `vars'matrix colnames `Cov' = > `vars'forvalues i=1/`p' { forvalues j=`i'/`p' { local x : word `i' > of `vars' local y : word `j' of `vars' quietly corr `x' `y', cov > matrix `Cov'[`i',`j'] = r(C) matrix `Cov'[`j',`i'] = r(C) > }}return matrix Cov = `Cov'end // of pwcovmat > sysuse auto > corr weight price mpg, cov > corr weight price mpg rep, cov > pwcovmat weight price mpg rep > matrix list r(Cov) > > On Thu, Nov 3, 2011 at 6:00 AM, <S.Jenkins@lse.ac.uk> wrote: > > > A colleague has data on a relatively large number of variables. His > > sample is unbalanced in the sense that each variable has some missing > > values. He wishes to calculate the covariance matrix for his data but > > without the listwise deletion of cases that is imposed by -correlation, > > covariance- or -matrix accum-. > > > > My first thought was that he could use -pwcorr- and loop over his > > variables, and build up his matrix from the saved results. But I thought > > there must be an easier or more straightforward way -- but Googling and > > -findit- have not suggested any. I guess there is a relatively easy > > Mata solution, but I am currently unfamiliar with that route. > > > > Suggestions using Stata or Mata please > > * > * 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/

**References**:**st: Calculation of covariance matrix for unbalanced sample?***From:*<S.Jenkins@lse.ac.uk>

**Re: st: Calculation of covariance matrix for unbalanced sample?***From:*Stas Kolenikov <skolenik@gmail.com>

**RE: st: Calculation of covariance matrix for unbalanced sample?***From:*Nick Cox <n.j.cox@durham.ac.uk>

**RE: st: Calculation of covariance matrix for unbalanced sample?***From:*Cameron McIntosh <cnm100@hotmail.com>

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