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Because the assumption of normality of the sampling distribution of the indirect effect may be violated, we followed Preacher's recommendation to use a bootstrap technique to correct the bias and to increase the confidence interval of estimates of the indirect effect [ 56].
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The Probability Density Function (PDF) of those coefficients was calculated using a bootstrap technique.
The 95% CIs for the SRMraw were calculated using a bootstrap technique.
We obtained confidence intervals for the PERR adjusted hazard ratio using a bootstrap technique.
The uncertainty in the GAMs for efficacy endpoints was quantified using a bootstrap technique.
These descriptive statistics have all been weighted to the total Ontario population, and are presented with 95% confidence intervals generated using a bootstrap technique.
Parameter estimates of relevant variables and interaction terms were then averaged across data sets by using a bootstrap technique (SAS macro)[ 14].
The difference in the AUCs between the models was tested using a bootstrap technique [ 25, 26] that takes into account the correlation between the areas that is induced by the paired nature of the data.
Statistical uncertainty was estimated using a bootstrap technique with 500 re-samples, where each re-sample was made up of two parts: 1) the treatment database was re-sampled with replacement and, 2) both our "best guesses" for p t in the period from 1971 to 1990, and the cessation rate for all years were sampled from gamma distributions.
Standard errors for the observed N positive and observed N negative were estimated using a bootstrap technique to generate many sets of simulated data to which the negative binomial function was fitted and the standard error calculated for the simulated N positive and the simulated N negative for each AUDIT score.
Different age models, CAM and MAM-3, were used to establish palaeodose and the robustness of these age models was tested using a bootstrapping technique.
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