Internal: Helper for infer()
Collection of various functions that compute an inferential quantity.
MeanResample(.first_resample)
SdResample(.first_resample, .resample_method, .n)
BiasResample(.first_resample, .resample_method, .n)
StandardCIResample(
.first_resample,
.bias_corrected,
.dist = c("z", "t"),
.df = c("type1", "type2"),
.resample_method,
.n,
.probs
)
PercentilCIResample(.first_resample, .probs)
BasicCIResample(.first_resample, .bias_corrected, .probs)
TStatCIResample(
.first_resample,
.second_resample,
.bias_corrected,
.resample_method,
.resample_method2,
.n,
.probs
)
BcCIResample(.first_resample, .probs)
BcaCIResample(.object, .first_resample, .probs).first_resample |
A list containing the |
.resample_method |
Character string. The resampling method to use. One of: "none", "bootstrap" or "jackknife". Defaults to "none". |
.n |
Integer. The number of observations of the original data. |
.bias_corrected |
Logical. Should the standard and the tStat
confidence interval be bias-corrected using the bootstrapped bias estimate?
If |
.dist |
Character string. The distribution to use for the critical value. One of "t" for Student's t-distribution or "z" for the standard normal distribution. Defaults to "z". |
.df |
Character string. The method for obtaining the degrees of freedom. Choices are "type1" and "type2". Defaults to "type1" . |
.probs |
A vector of probabilities. |
.second_resample |
A list containing |
.resample_method2 |
Character string. The resampling method to use when resampling
from a resample. One of: "none", "bootstrap" or "jackknife". For
"bootstrap" the number of draws is provided via |
.object |
An R object of class cSEMResults resulting from a call to |
Implementation and termionology of the confidence intervals is based on Hesterberg (2015) and Davison and Hinkley (1997).
Davison AC, Hinkley DV (1997).
Bootstrap Methods and their Application.
Cambridge University Press.
doi: 10.1017/cbo9780511802843, https://doi.org/10.1017/cbo9780511802843.
Hesterberg TC (2015).
“What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum.”
The American Statistician, 69(4), 371–386.
doi: 10.1080/00031305.2015.1089789, https://doi.org/10.1080/00031305.2015.1089789.
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