Sentence examples for bootstrap-confidence interval from inspiring English sources

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We tested the significance of each loading (eigenvector coefficient) by the bootstrap-confidence interval method (Peres-Neto et al. 2003).We performed a generalized linear model (GLM) with negative binomial error (R software, R Development Core Team 2009) to explore the correlation between syconium production in each phase and the principle components (PCs) of the meteorological data.

A bias-corrected bootstrap-confidence interval (CI) of the product of these paths that does not include zero provides evidence of a significant indirect effect of maths anxiety on cognitive reflection through maths knowledge [ 36].

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This will be conducted using moderated linear regression analyses with indirect effects reproduced using Preacher, Curran, and Bauer's [ 110] asymptotic bootstrapped algorithms and the bias-corrected bootstrap confidence interval to assess the statistical significance of the effects [ 111].

The confidence interval was calculated as a bootstrap confidence interval around the mean direction in a von Misses distribution.

The green- and blue-shaded regions code for bootstrap confidence interval and 5%% significance level, respectively.

In the next section, a possible measure of spread for 3-D rotations is introduced and the steps for obtaining a bootstrap confidence interval are outlined.

Resampling of differential travel times was conducted 2000 times, and the 95%% bootstrap confidence interval was used as the estimation error.

The composite record illustrating regional fire occurrence was obtained by averaging data from the 4 sites, with a 95%% bootstrap confidence interval.

We found GAM's to perform as well as nonlinear models with respect to fit and validation statistics; however, when applied to the population of predictor data the bootstrap confidence interval was less efficient than the null model.

The mean reduction in fitness for cured females was 37.18% (95% bootstrap confidence interval  = 34.35%, 39.94%).

In the last month before expiration, adjusted specificity estimated using regression standardization was 99.18% (95% bootstrap confidence interval 98.60 99.57%) (Figure 1).

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