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We completed all analyses using Stata 13.1 (StataCorp, College Station, USA); we used the 'roctab' command for analysis of the individual AUCs, and 'roccomp' for the comparison of the PHQ-9 and the PHQ-2.
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Adjustment for clustering was performed with standard STATA commands for analysis of survey data.
STATA inbuilt commands for survival analysis were used to do the analysis under the frequentist approach.
Although Specman comes with a selection of tools and commands for the analysis of a verification environment, it lacks an easy-to-use solution that lets users fully explore a design.
Imputations and analyses of imputed datasets were performed in Stata using user-written program ice for imputations and Stata mi and xtgee commands for primary analysis models.
It is also possible to save just the commands for the analysis steps taken as a workflow, which can be applied to another dataset or shared with other users.
In Supplementary Materials document, we used two different data types as examples (see examples 1 and 2 in Supplementary Materials for the detailed operation flows) to present the metan command for the meta-analysis of prognostic test accuracy.
The user-written commands for meta-analysis (Harris et al. 2008) were downloaded from within Stata.
Data were entered into a Microsoft Excel spreadsheet and then transferred to Stata version 13.0 for analysis using survey commands to adjust for the two-stage cluster sampling design.
For analysis of affected men/women, the FBAT command 'setafftrait' was used.
We believe that for those who know how to execute simple commands in R, canvasDB will considerably reduce the time for analysis compared with most other systems.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com