【文章內(nèi)容簡介】 e using Fixedeffects ipdmetan, study(trialid) eform interaction keepall : stcox arm default is to pool coeffs from first interaction term Inclusion of aggregate data ? I don’t have a separate aggregate dataset, so I will create one artificially from my IPD dataset . ** Generate artificial trial subgrouping . gen subgroup = inlist(trialid, 1, 8, 12, 15) . label define subgroup_ 0 Trial group 1 1 Trial group 2 . label values subgroup subgroup_ . ** Run ipdmetan within one of the subgroups。 save the dataset . qui ipdmetan, study(trialid) by(subgroup) nooverall nograph saving() : stcox arm if subgroup==1, strata(sex) (Aside: Contents of ) _use trialid _labels _ES _seES _lci _uci _wgt _NN 1 1 belgium 202 1 8 EORTC 08861 105 1 12 LILLE 163 1 15 GETCB 05CB86 539 Inclusion of aggregate data: Syntax . ipdmetan, study(trialid) eform nooverall ad(, byad) : stcox arm if subgroup==0, strata(sex) Do not pool IPD and aggregate together Aggregate data syntax estimation_mand “byad” = treat IPD amp。 aggregate data as subgroups Trials included from IPD: 7 Patients included: 1333 Trials included from aggregate data: 4 Patients included: 1009 Pooling of main (treatment) effect estimate arm using Fixedeffects trial reference | number | Effect [95% Conf. Interval] % Weight + IPD | LCSG 773 | CAMS | ... | ... Subgroup effect | + Aggregate | belgium | EORTC 08861 | ... | ... Subgroup effect | Tests of effect size = 1: IPD z = p = Aggregate z = p = Inclusion of aggregate data: Screen output Inclusion of aggregate data: Forest plot I P DL C S G 7 7 3C A M SM R C L U 1 1S L O V E N I AG E TC B 0 4 C B 8 6I TA L YK O R E AS u b t o t a l ( I sq u a r e d = 0 . 0 % , p = 0 . 7 4 0 )A g g r e g a t eb e l g i u mE O R TC 0 8 8 6 1L I L L EG E TC B 0 5 C B 8 6S u b t o t a l ( I sq u a r e d = 0 . 0 % , p = 0 . 9 6 4 )r e f e r e n ce n u m b e rt r i a l1 . 1 2 ( 0 . 8 3 , 1 . 5 3 )1 . 0 3 ( 0 . 7 7 , 1 . 3 8 )0 . 9 6 ( 0 . 7 4 , 1 . 2 4 )0 . 8 9 ( 0 . 5 4 , 1 . 4 9 )1 . 1 4 ( 0 . 8 0 , 1 . 6 2 )0 . 6 9 ( 0 . 4 0 , 1 . 2 0 )1 . 1 6 ( 0 . 7 6 , 1 . 7 6 )1 . 0 2 ( 0 . 9 0 , 1 . 1 6 )1 . 4 6 ( 1 . 0 7 , 1 . 9 8 )1 . 6 4 ( 0 . 9 1 , 2 . 9 6 )1 . 5 7 ( 1 . 0 6 , 2 . 3 2 )1 . 4 4 ( 1 . 1 3 , 1 . 8 3 )1 . 4 8 ( 1 . 2 6 , 1 . 7 4 )E f f e ct ( 9 5 % C I )1 8 . 1 81 9 . 9 22 6 . 1 26 . 4 81 3 . 8 55 . 6 99 . 7 61 0 0 . 0 02 8 . 6 17 . 7 91 7 . 5 64 6 . 0 31 0 0 . 0 0W e i g h t%1 4. 2 5Advanced syntax example: non “eclass” estimation mand ipdmetan (u[1,1]/V[1,1]) (1/sqrt(V[1,1])) , study(trialid) eform ad(, byad) lcols(evrate=_d % Event rate) rcols(u[1,1] % oE(o) V[1,1] % V(o)) forest(nooverall nostats nowt) : sts test arm if subgroup==0, mat(u V) Effect estimate amp。 SE not from e(b) – must specify manually Advanced syntax example: columns of data in forestplot ipdmetan (u[1,1]/V[1,1]) (1/sqrt(V[1,1])) , study(trialid) eform ad(, byad) lcols(evrate=_d % Event rate) rcols(u[1,1] % oE(