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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Dear Nate,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Such differences are very unpleasant indeed, and unacceptable for practical purposes. I assume that your estimates were obtained with the Method of Moments
(the default estimation method).<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">The parameter for increasing precision of standard errors is the number of runs in Phase 3; this is set by the n3 parameters in sienaModelCreate.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">However, such a large instability of s.e.s obtained with n3 = 1000 suggest that something is not right. My guess is that perhaps this has to do with multicollinearity
between parameter estimates, which can be diagnosed by looking at the estimates for the inter-parameter correlations given under the heading “Covariance matrix of estimates (correlations below diagonal)” in the output file, and in the summary(...) of the estimation
results. If this is the case, then the thing to do is drop some of the effects highly correlated with others. If this is not the case, then there is reason for worry and it would be good to try and find out the cause of this instability – because it is unacceptable.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">By the way, just 2 weeks ago I encountered another case of such instability, where indeed the reason was multicollinearity, which led me to add some remarks
to Chapter 7 (p. 91) of the manual. This is in the manual which is (since a few minutes ago) available at
<a href="http://www.stats.ox.ac.uk/~snijders/siena/RSiena_Manual.pdf">http://www.stats.ox.ac.uk/~snijders/siena/RSiena_Manual.pdf</a>, not yet the manual that is included in the package.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">By the way (2<sup>nd</sup>), this topic really is more appropriate for the Stocnet/Siena yahoo discussion group (it’s a fine line indeed, but if my diagnosis
is correct this is not about programming), therefore I copy my reply to the Stocnet/Siena group.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Please let us know what you’ll find out.
<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Best wishes,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Tom<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">================================================================<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Tom A.B. Snijders<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Professor of Statistics in the Social Sciences<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Department of Politics and Department of Statistics<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Nuffield College<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">University of Oxford<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">tel. +44-01865-278599<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:10.0pt;font-family:"Tahoma","sans-serif"">From:</span></b><span lang="EN-US" style="font-size:10.0pt;font-family:"Tahoma","sans-serif""> rsiena-help-bounces@r-forge.wu-wien.ac.at [mailto:rsiena-help-bounces@r-forge.wu-wien.ac.at]
<b>On Behalf Of </b>Nate Doogan<br>
<b>Sent:</b> 18 September 2011 14:41<br>
<b>To:</b> rsiena-help@r-forge.wu-wien.ac.at<br>
<b>Subject:</b> [Rsiena-help] Standard Error Estimates<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Hi group.<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">I will paste two result excerpts. Both are results of the same model on the same data with the same precision parameters (at least those that I know of). I chose to use five phase two sub phases, and 1000 phase three iterations in both
estimations.<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">Here's number one:<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 11. eval RSB alter -1.1657 ( 0.6275 ) 0.0023 </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 12. eval RSB ego -2.5752 ( 1.2052 ) 0.0188 </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 13. eval same RSB -0.8655 ( 0.7055 ) 0.0462 </span><o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New"">Behavior Dynamics</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 14. rate rate RSB period 1 1.4035 ( 0.1899 ) -0.0589 </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 15. eval behavior RSB linear shape -1.0667 ( 0.1923 ) -0.0408 </span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 16. eval behavior RSB average similarity 0.8539 ( 0.3881 ) 0.0015 </span><o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">Here's number two:<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 11. eval RSB alter -1.1412 ( 1.9588 ) 0.0015</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 12. eval RSB ego -2.6017 ( 2.6454 ) -0.0682</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 13. eval same RSB -0.8478 ( 2.1887 ) 0.0587</span><o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New"">Behavior Dynamics</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 14. rate rate RSB period 1 1.4049 ( 0.1531 ) -0.0373</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 15. eval behavior RSB linear shape -1.0670 ( 0.2532 ) 0.0160</span><o:p></o:p></p>
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<p class="MsoNormal"><span style="font-family:"Courier New""> 16. eval behavior RSB average similarity 0.8468 ( 0.7681 ) -0.0453</span><o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">The only difference is that I asked for the simulated nets in number two (returnDeps=T). In my opinion, the parameter estimates of these two fits are acceptably close. I don't believe that the standard errors are, however. My decision to
reject would vary in these estimates for effects 11, 12, and 16. Is it likely that my data is odd in that way? Or is there a software parameter that will allow me to perhaps trade some time for some precision in the estimation of standard errors?<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><br clear="all">
Nathan Doogan<o:p></o:p></p>
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<p class="MsoNormal">Doctoral Student<o:p></o:p></p>
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<p class="MsoNormal">The Ohio State University<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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