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From |
Inna Becher <inna.becher@uni-konstanz.de> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: implementation of variance formula |

Date |
Fri, 13 Mar 2009 16:55:49 +0100 |

Dear Stas, the variance formula I use is

Stas Kolenikov schrieb:

Tell us more about the problem. As far as I know, sampling networks is heck of a mess. To simulate anything, you would need to have almost perfect understanding how your network was formed. Any simulation is just as good as the model to create the data that was used in that simulation. And survey bootstrap is a moderately crazy topic. No textbook covers it sufficiently well, unfortunately. Certainly not in Efron's book; there is a chapter in Shao & Tu (1995) Springer book, but it only covered stuff until late 1980s. The newer (and important!) methods are only out there in the papers. Yates-Grundy-Sen variance estimator for Horvitz-Thompson estimator is sum over j<k (p[j]*p[k] - p[j,k]) (y[j]/p[j] - y[k]/p[k])^2 If you can write Mata functions to compute the unit and pair probabilities of selection, you can have a pretty compact code for your variance estimator. You won't have to store the huge matrices of pairwise selection probabilities that likely have well structured form if you talk about cluster sampling. On Wed, Mar 11, 2009 at 3:49 AM, Inna Becher <inna.becher@uni-konstanz.de> wrote:I can calculate the probability for each network (=cluster) to be included in the sample. I also can calculate for each pair of selected clusters to be included in the sample. My problem is: this probabilities are to be saved somewhere. Should it be a matrix? I have not yet worked with matrices to calculate variances. The version of H-T-estimator I need is not implemented in svy-. I wrote an ado for sampling design that I need and implemented H-T-estimator for the mean, but not for the variance.

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**References**:**st: implementation of variance formula***From:*Inna Becher <inna.becher@uni-konstanz.de>

**Re: st: implementation of variance formula***From:*Steven Samuels <sjhsamuels@earthlink.net>

**Re: st: implementation of variance formula***From:*Inna Becher <inna.becher@uni-konstanz.de>

**Re: st: implementation of variance formula***From:*Stas Kolenikov <skolenik@gmail.com>

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