← Search

Data · dataset · 2016

Data from: On the variety of methods for calculating confidence intervals by bootstrapping

Listed in DataCite

1.

Description

Researchers often want to place a confidence interval around estimated parameter values calculated from a sample. This is commonly implemented by bootstrapping.

There are several different frequently used bootstrapping methods for this purpose. 2. Here we demonstrate that authors of recent papers frequently do not specify the method they have used and that different methods can produce markedly different confidence intervals for the same sample and parameter estimate. 3. We encourage authors to be more explicit about the method they use (and number of bootstrap resamples used). 4.

Read the rest (1 more)

We recommend the bias corrected and accelerated method as giving generally good performance; although researchers should be warned that coverage of bootstrap confidence intervals is characteristically less than the specified nominal level, and confidence interval evaluation by any method can be unreliable for small samples in some situations.

Links

Topics

Stated by source
Mathematics
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
DataCite10.5061/dryad.r390f14 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · DataCiteconnector:datacite@1.0.0/data/attributes/rightsList
byte_sizesource · DataCiteconnector:datacite@1.0.0
concepts[field].fos:mathematicssource · DataCiteconnector:datacite@1.0.0
concepts[field].local:field:mathematics-statisticsmapping · DataCitevocabulary-mapper@1.0.0keywords['Statistics']
descriptionsource · DataCiteconnector:datacite@1.0.0/data/attributes/descriptions
licensesource · DataCiteconnector:datacite@1.0.0/data/attributes/rightsList
publication_datesource · DataCiteconnector:datacite@1.0.0/data/attributes/dates
titlesource · DataCiteconnector:datacite@1.0.0/data/attributes/titles/0/title
version_labelsource · DataCiteconnector:datacite@1.0.0