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Confidence intervals for these were based on binomial statistics.
Logistic regression was applied to determine the detection probability of analyte at a particular concentration, and calculations based on binomial statistics developed to aid prediction of the degree of replication required to achieve a particular level of sensitivity.
We supply two additional scripts to i) estimate the bisulfite conversion rate using the appropriate experimental data, and ii) associate a p-value, based on binomial statistics, to each of the extracted methylation levels, as well as a procedure to control the false discovery rate.
For low-level calibration, it is better to eliminate all Ct values in a replicate group for any standard concentration that shows non-detects reasonably attributable (over 1% probability based on binomial statistics) to sampling effects, than to eliminate only the non-detects.
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When comparing the various statistics, we show that those based on binomial over-representation and Fisher's exact test performs almost equally good and better than the others.
The statistical analysis was based on binomial likelihoods with a logit link function.
We calculated summary statistics for diagnostic accuracy and triage advice with 95% confidence intervals based on binomial distribution using Stata/MP 13.0.
A rationale for the appropriate choice of p, based on Binomial Probability is also presented.
The logit models are based on binomial distributions (z-scores, generalized linear mixed model, GLMM).
In [15], the authors present a fault-tolerant broadcast algorithm for hypercubes based on binomial trees.
Confidence intervals were calculated based on binomial and multinomial tests of accuracy.
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