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Logistic regression was performed using the ROBUST command in STATA to adjust for our sampling scheme and clustering of cases within households.
In addition, robust estimation methods were used, using the "robust" command in STATA [ 61], to control for clustering resulting from the inclusion of multiple observations per country in the study [ 73].
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Standard errors account for clustering at the hospital level using the "robust cluster" command.
This method is robust for unbalanced data, and by using the 'cbind' command to calculate the germination proportions we weighted the sample sizes (number of seeds and seedlings per patch).
The marginal regression models were fitted in STATA [ 12] using the xtgee command with an identity link function (link (iden)) and the robust standard errors option.
24, 25 Regressions were estimated using the xtreg command in Stata 12.1 (StataCorp, College Station, Tex) with specifications to provide robust standard errors that accounted for clustering of patient data within hospitals.
32 We estimated standard errors that were robust to a general form of heteroskedasticity and clustering by physician, and reported partial F statistics for the association of instruments and the exposure (using the Stata command ivreg2 and option gmm2).
The analysis was performed using the MCM command UAMCM.
We analysed the imputed data using the micombine command [ 29].
The time measurement was obtained using the Unix command 'time'time
Weighting was applied using the 'ccode' command in TNT.
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