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All analyses were adjusted for sampling probability (via weights) and cluster effects using the svy procedures in Stata version 10. Measurements for fasting insulin, HOMA-R, triglycerides and PTH were naturally log transformed to normalize distributions.
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Statistical analyses were conducted with Stata 11.0 (Stata Corp LP, College Station, TX USA), using the svy procedure to account for cluster effects and sampling weights from MECs (lung function) and allergy subsamples (allergen sensitisation).
All analytical procedures took account of the multi-stage sampling design by using the svy family of commands in STATA and applying the sampling weights.
Estimates were made using the "svy" (survey commands) functions of the STATA program, which enabled us to incorporate the sampling design and weights into all of our statistical calculations (descriptive OR, logistic regression).
The estimates were made using the "svy" (survey command) functions of the STATA program, which allowed us to incorporate the study design and weights in all our statistical calculations.
The apparent/test based seroprevalence estimates were calculated using the svy command in Stata 9.0 (Stata Corporation, Texas, USA).
All further analyzes were conducted using the svy command.
All analyses were performed by using the SVY suite of SAS 9 (SAS Inc., Cary, NC, USA).
Logistic regression models were then weighted using the "svy: logistic" command in Stata.
All regression analyses were then conducted using the svy command and regress subcommand.
Therefore, the prevalence estimates and their standard errors were weighted using the svy set of commands in Stata.
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