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From |
"Li, Elena (Zhonghe)" <zli@hsph.harvard.edu> |

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

Subject |
st: RE: RE: two-parts model bootstrap using XTGEE |

Date |
Tue, 4 Dec 2012 04:53:08 +0000 |

Thank you Tim. If it were bootstrapping from one model, I know how to get the marginal effect - I assume that was what you meant? And I think I have the formula to get the marginal effects for the two parts - but we need the p value for this difference in difference of p0*p1 that I don't know how to get without bootstrapping. Best, Zhonghe ________________________________________ From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of tshmak [tshmak@hku.hk] Sent: Monday, December 03, 2012 10:11 PM To: statalist@hsphsun2.harvard.edu Subject: st: RE: two-parts model bootstrap using XTGEE Dear Zhonghe, Instead of writing the program the way you wrote below, I think you should consider using the command -margins-. That would simplify your program a lot and let's see if you still get the same problem. Best, Tim -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Li, Elena (Zhonghe) Sent: 04 December 2012 03:12 To: statalist@hsphsun2.harvard.edu Subject: st: two-parts model bootstrap using XTGEE Hi We are fitting a two-parts model on health care cost using longitudinal data. Part1 is modeling whether there is any cost, and Part2 is modeling the cost when if there is a cost. The goal is to bootstrap the difference in difference (post_pilot) in terms of the p0*p1 (the predicted probability of having cost * the predicted cost). I am a SAS user and tried to put the following Stata program together. The models converged the first time but when the replication starts the modeling does not converge: "convergence not achieved an error occurred when bootstrap executed tempa, posting missing values" Can you please help? Thank you. Zhonghe Li _____________________________________________________________ sort member qtr by member qtr: drop if _n~=1 egen memberid=group(member) egen practice=group(pcp) gen newid=memberid xtset newid qtr generate sample=(1-missing(havecost, logcost, female, aet, uhc, ant, Qtr_months, age1-age4, qtr, health, post, pilot, post_pilot)) keep if sample matrix define results = (1,2,3) capture program drop tempa program define tempa, rclass xtgee havecost i.female aet uhc ant Qtr_months age1-age4 qtr health i.post i.pilot i.post_pilot, family(binomial) link(logit) corr(ar 1) gen truepost=post gen truepilot=pilot gen true_post_pilot=post_pilot replace post=0 replace pilot=0 replace post_pilot=0 predict pre_control_p1 replace pilot=1 predict pre_pilot_p1 replace post=1 replace post_pilot=1 predict post_pilot_p1 replace pilot=0 replace post_pilot=0 predict post_control_p1 replace post=truepost replace pilot=truepilot replace post_pilot=true_post_pilot xtgee logcost female aet uhc ant Qtr_months age1-age4 qtr health post pilot post_pilot if logcost>0, family(gamma) link(log) corr(ar 1) vce(robust) replace post=0 replace pilot=0 replace post_pilot=0 predict pre_control_p2, mu replace pilot=1 predict pre_pilot_p2, mu replace post=1 replace post_pilot=1 predict post_pilot_p2, mu replace pilot=0 replace post_pilot=0 predict post_control_p2, mu drop post pilot post_pilot rename truepost post rename truepilot pilot rename true_post_pilot post_pilot gen phat_pre_control=pre_control_p1*pre_control_p2 gen phat_pre_pilot=pre_pilot_p1*pre_pilot_p2 gen phat_post_pilot=post_pilot_p1*post_pilot_p2 gen phat_post_control=post_control_p1*post_control_p2 gen diff_pilot=phat_post_pilot-phat_pre_pilot gen diff_control=phat_post_control-phat_pre_control gen diff_in_diff=diff_pilot-diff_control summ diff_pilot return scalar m_diff_pilot = r(mean) local var1 = r(mean) summ diff_control return scalar m_diff_control = r(mean) local var2 = r(mean) summ diff_in_diff return scalar m_diff_in_diff = r(mean) local var3 = r(mean) matrix define temp=(`var1',`var2',`var3') matrix define results = results \ temp matrix list results quietly: drop diff* pre_* post_control_p1 post_control_p2 post_pilot_p1 post_pilot_p2 phat* *quietly: scalar drop _all xtset,clear end bootstrap mean_diff_pilot=r(m_diff_pilot) mean_diff_control=r(m_diff_control) mean_diff_in_diff=r(m_diff_in_diff), noisily strata(pilot) cluster(memberid) idcluster(newid) group(qtr) reps(100) seed(1234567) : tempa svmat results, names(diff) outsheet twopartdiff* using diff.csv, comma replace * * 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/ * * 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/ * * 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/

**Follow-Ups**:**st: RE: RE: RE: two-parts model bootstrap using XTGEE***From:*tshmak <tshmak@hku.hk>

**References**:**st: two-parts model bootstrap using XTGEE***From:*"Li, Elena (Zhonghe)" <zli@hsph.harvard.edu>

**st: RE: two-parts model bootstrap using XTGEE***From:*tshmak <tshmak@hku.hk>

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