Sentence examples for bootstrap weights were used from inspiring English sources

Bootstrap weights were used for all regression analyses so that the variances take account of the sample design.

Sampling and bootstrap weights were used in all analyses to adjust for sample selection and non-response [ 40].

To ensure data were nationally representative the CHMS required that 500 bootstrap weights be used over the 10 age-sex groups [ 8].

Bootstrap methods, using 500 sets of bootstrap sampling weights, were used to determine 95% CIs around each point estimate.

The CCHS has a complex design including stratification, multiple stages of selection, and unequal selection probabilities [ 29]; therefore, bootstrap repeated replications [ 37] with pooling-adjusted weights were used to calculate variance estimates.

Bootstrap distributions of the estimated weights are used to identify the strength of association between the Wolff et al. categories and TTP, the degree of chlorine substitution and TTP, and to define an 'average weighted quartile sum index' that is associated with TTP.

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 resampling method using 500 bootstrap weights was applied to calculate the variance of regression coefficient estimates and 95% confidence intervals (CIs) (Statistics Canada 2011).

The improved performance of our proposed generalized bootstrap weights over design bootstrap weights is illustrated by means of a simulation study.

Normalized sampling weights and bootstrap variance estimates were used in the analysis.

In all models, individuals were weighted based on their sampling weight in the CCHS, and bootstrapping methods were used to determine 95% confidence intervals around all estimates.