Bootstrap MF CI

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Description

Estimates bootstrap confidence intervals for the mitigated fraction.

Usage

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  MFBoot(formula, data, compare = c("con", "vac"), b = 100,
    B = 100, alpha = 0.05, hpd = TRUE, bca = FALSE,
    return.boot = FALSE, trace.it = FALSE)

Arguments

formula

Formula of the form y ~ x, where y is a continuous response and x is a factor with two levels

data

Data frame

compare

Text vector stating the factor levels - compare[1] is the control or reference group to which compare[2] is compared

b

Number of bootstrap samples to take with each cycle

B

Number of cycles, giving the total number of samples = B * b

alpha

Complement of the confidence level

hpd

Estimate highest density intervals? Default TRUE.

bca

Estimate BCa intervals? Default FALSE.

return.boot

Save the bootstrap sample of the MF statistic? Default FALSE.

trace.it

Verbose tracking of the cycles? Default FALSE.

Details

Resamples the data and produces bootstrap confidence intervals. Equal tailed intervals are estimated by the percentile method. Highest density intervals are estimated by selecting the shortest of all possible intervals. For BCa intervals, see Efron and Tibshirani section 14.3.

Value

a mfboot-class data object

Author(s)

David Siev david.siev@aphis.usda.gov

References

Siev D. (2005). An estimator of intervention effect on disease severity. Journal of Modern Applied Statistical Methods. 4:500–508

Efron B, Tibshirani RJ. An Introduction to the Bootstrap. Chapman and Hall, New York, 1993.

See Also

mfboot-class

Examples

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MFBoot(lesion~group, calflung)

# 10000 bootstrap samples
# 95% confidence interval
#
# Comparing vac to con
#                 observed median  lower  upper
# Equal Tailed        0.44 0.4464 0.1360 0.7056
# Highest Density     0.44 0.4464 0.1456 0.7088