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Then we calculated the frequencies of selection of each mutation in the 200 bootstrap samples under the conditions mentioned above (prevalence between 10%and90%0% and a p-value < 0.01 in univariable analysis).
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The log-likelihood values obtained for the bootstrapped samples evaluated under the HGT model ranged from −43.2 to −49.6, and are much lower than the log-likelihood values when assuming the HGT model for the original tree (−6.35).
The 95% confidence intervals (CIs) were calculated using the bootstrapping procedure (n = 1,000 bootstrap samples) for area under the receiver-operator characteristic curve estimations and the differences between model areas under the receiver-operator characteristic curve.
P-values were calculated by taking 2000 stratified bootstrap samples; bAUC, area under the receiver operating characteristic curve; PDAC, pancreatic ductal adenocarcinoma.
The possibility of overestimation of the area under the curve was assessed by applying the model to 200 bootstrap samples of the data and computing the area under the curve for each.
Under the bootstrap sampling, the total frequencies of the grouped data have a multinomial distribution.
The bootstrap samples are twice the number of measurements.
In 100 bootstrap samples we repeated the analyses and, by evaluating the diagnostic model performance in the bootstrap samples and in the original data, obtained a shrinkage factor to adjust regression coefficients and areas under the curve for overoptimism.
In 200 bootstrap samples of the 30-day data, 94% of the samples showed a cost advantage for enoxaparin.
The bootstrapping procedure involved computing regression coefficients for 10 000 bootstrap samples of the validation animals.
We took one thousand bootstrap samples from the original data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com