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A resampling method using 500 bootstrap weights was applied to calculate the variance of regression coefficient estimates and 95% confidence intervals (CIs) (Statistics Canada 2011).
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Sampling and bootstrap weights were applied to make the data nationally representative.
Both the sample and bootstrap weights were applied in Stata v12.0 prior to analysis [ 11].
In addition, bootstrap weights were applied to take into account of the CHMS's complex, multi-stage sampling design.
To account for the stratified survey sampling design, normalized sampling weights were applied to prevalence estimates and bootstrap weights were applied to variance calculations, using data provided by Statistics Canada.
A total of 500 bootstrap weights were applied since the sample was allocated over 10 age-sex groups, and it was estimated that 500 units per group was required to produce national estimates, for a total of 5,000 reporting units.
No correction for internal weights was applied.
Variance estimates (not shown) of descriptive statistics were calculated using 1000 bootstrap weights and sampling weights were applied to longitudinal analysis [ 20].
CCHS sample weights were applied, estimated prevalence rates were bootstrapped, and 95% confidence intervals (95% CI's) were reported.
CCHS sample weights were applied and the results of the regression modeling were bootstrapped.
Sample weights are applied.
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