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Tables 1 and 2 show the results of using the bootstrap method to calculate the 95% confidence interval for the fading parameter in both normal and Clayton copula-based estimators in ρ p =0.9.
FALCON uses a bootstrap method to calculate the statistical significance of a given nestedness score, since the true null distributions of the test statistics are not known.
We used the bootstrap method to calculate the standard error of the coefficient of estimate of β, as described previously (22, 23).
This procedure is combined with the bootstrap method to calculate the average trapped time for successful events, as shown in Figure 4 b.
To assess the significance of these LRTs we used a nonparametric bootstrap method to calculate false discovery rates (FDR) for our data [ 11] (Methods).
Specifically, we re-estimated the baseline model (Poisson regression) using an additional year of data in the period after reform; only propensity score matched counties in control states; bootstrap method to calculate standard errors (in fixed and, separately, random effects models); and negative binomial and linear regression models.
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We use bootstrap methods to calculate cluster-robust standard errors (Efron 1979).
We used bootstrap methods to calculate 95% confidence intervals (CIs) for the mean costs of surgery for ruptured AAA, nonruptured AAA and AAA where the patient died within 30 days by applying a cost-trimming rule that the Danish National Board of Health uses in calculating national DRG tariffs.
We performed bootstrapping method to calculate a 95% confidence interval of the c-statistics of each model.
In addition, a bootstrapping method to calculate confidence intervals and a randomization method to test the statistical significance of the integration are available for both indices.
In this paper, we introduce an R package (PHENIX: PHENotypic Integration indeX), in which we provide functions to estimate a size-controlled phenotypic integration index, a bootstrapping method to calculate confidence intervals, and a randomization method to simulate null distributions and test the statistical significance of the integration.
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