cSEM (version 0.3.1)

inference_helper: Internal: Helper for infer()

Description

Collection of various functions that compute an inferential quantity.

Usage

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)

Arguments

.first_resample

A list containing the .R resamples based on the original data obtained by resamplecSEMResults().

.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 TRUE the confidence interval for some estimated parameter theta is centered at 2*theta - theta*_hat, where theta*_hat is the average over all .R bootstrap estimates of theta. Defaults to TRUE

.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 .R2 resamples for each of the .R resamples of the first run.

.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 .R2. Currently, resampling from each resample is only required for the studentized confidence intervall ("CI_t_interval") computed by the infer() function. Defaults to "none".

.object

An R object of class cSEMResults resulting from a call to csem().

Details

Implementation and termionology of the confidence intervals is based on Hesterberg2015;textualcSEM and Davison1997;textualcSEM.

References