Skip to main content

All Questions

Filter by
Sorted by
Tagged with
109 votes
3 answers
21k views

What are examples where a "naive bootstrap" fails?

Suppose I have a set of sample data from an unknown or complex distribution, and I want to perform some inference on a statistic $T$ of the data. My default inclination is to just generate a bunch of ...
raegtin's user avatar
  • 10k
73 votes
5 answers
33k views

Is it true that the percentile bootstrap should never be used?

In the MIT OpenCourseWare notes for 18.05 Introduction to Probability and Statistics, Spring 2014 (currently available here), it states: The bootstrap percentile method is appealing due to its ...
Clarinetist's user avatar
  • 5,027
62 votes
1 answer
35k views

Bootstrap vs. jackknife

Both bootstrap and jackknife methods can be used to estimate bias and standard error of an estimate and mechanisms of both resampling methods are not huge different: sampling with replacement vs. ...
Tu.2's user avatar
  • 2,957
43 votes
3 answers
46k views

What is the meaning of a confidence interval taken from bootstrapped resamples?

I've been looking at numerous questions on this site regarding bootstrapping and confidence intervals, but I'm still confused. Part of the reason for my confusion is probably that I'm not advanced ...
iarwain's user avatar
  • 433
41 votes
2 answers
6k views

Is there a reliable nonparametric confidence interval for the mean of a skewed distribution?

Very skewed distributions such as the log-normal do not result in accurate bootstrap confidence intervals. Here is an example showing that the left and right tail areas are far from the ideal 0.025 ...
Frank Harrell's user avatar
29 votes
2 answers
13k views

How to construct a 95% confidence interval of the difference between medians?

My problem: parallel group randomized trial having a very right-skewed distribution of the primary outcome. I do not want to assume normality and use normal-based 95% CIs (i.e. using 1.96 X SE). I am ...
pmgjones's user avatar
  • 5,811
24 votes
3 answers
47k views

How can I calculate the confidence interval of a mean in a non-normally distributed sample?

How can I calculate the confidence interval of a mean in a non-normally distributed sample? I understand bootstrap methods are commonly used here, but I am open to other options. While I am looking ...
fmark's user avatar
  • 4,987
22 votes
1 answer
11k views

Bootstrap-based confidence interval

While studying bootstrap-based confidence interval, I once read the following statement: If the bootstrap distribution is skewed to the right, the bootstrap-based confidence interval incorporates a ...
user3269's user avatar
  • 5,182
22 votes
4 answers
5k views

Why not always use bootstrap CIs?

I was wondering how bootstrap CIs (and BCa in barticular) perform on normally-distributed data. There seems to be lots of work examining their performance on various types of distributions, but could ...
dragice's user avatar
  • 331
20 votes
5 answers
4k views

Three questions about the article "Ditch p-values. Use Bootstrap confidence intervals instead"

I am not a statistician by training and I was asked by students to explain them an article called "Ditch p-values. Use Bootstrap confidence intervals instead" . The author seems a prominent ...
German Demidov's user avatar
17 votes
2 answers
8k views

Biased bootstrap: is it okay to center the CI around the observed statistic?

This is similar to Bootstrap: estimate is outside of confidence interval I have some data that represents counts of genotypes in a population. I want to estimate genetic diversity using Shannon's ...
ZNK's user avatar
  • 221
17 votes
1 answer
5k views

Non-parametric bootstrap p-values vs confidence intervals

Context This is somewhat similar to this question, but I do not think it is an exact duplicate. When you look for how instructions on how to perform a bootstrap hypothesis test, it is usually stated ...
Erik's user avatar
  • 7,249
16 votes
1 answer
35k views

Why would I want to bootstrap when computing an independent sample t-test? (how to justify, interpret, and report a bootstrapped t-test)

Let's say I have two conditions, and my sample size for the two conditions is extremely low. Let's say I only have 14 observations in the first condition and 11 in the other. I want to use the t-test ...
stat_gurl's user avatar
  • 161
16 votes
2 answers
17k views

Bootstrapping confidence interval from a regression prediction

For homework, I was given data to create/train a predictor that uses lasso regression. I create the predictor and train it using the lasso python library from scikit learn. So now I have this ...
itsSLO's user avatar
  • 393
16 votes
2 answers
3k views

Can we use bootstrap samples that are smaller than original sample?

I want to use bootstrapping to estimate confidence intervals for estimated parameters from a panel dataset with N=250 firms and T=50 month. The estimation of parameters is computationally expensive (...
Hazhir's user avatar
  • 221
16 votes
4 answers
8k views

Prediction intervals for machine learning algorithms

I want to know if the process described below is valid/acceptable and any justification available. The idea: Supervised learning algorithms don't assume underlying structures/distributions about the ...
kevinykuo's user avatar
  • 641
16 votes
1 answer
4k views

Bootstrap: estimate is outside of confidence interval

I did a bootstrapping with a mixed model (several variables with interaction and one random variable). I got this result (only partial): ...
giordano's user avatar
  • 1,019
13 votes
2 answers
2k views

Obtaining and interpreting bootstrapped confidence intervals from hierarchical data

I'm interested in obtaining a bootstrapped confidence interval on quantity X, when this quantity is measured 10 times in each of 10 individuals. One approach is to obtain the mean per individual, ...
Mike Lawrence's user avatar
13 votes
1 answer
4k views

Calculating confidence intervals via bootstrap on dependent observations

The bootstrap, in its standard form, can be used to calculate confidence intervals of estimated statistics provided that observations are iid. I. Visser et al. in "Confidence Intervals for Hidden ...
Sadeghd's user avatar
  • 423
13 votes
1 answer
190 views

If bootstrap works for $\hat{\alpha}$ and for $\hat{\beta}$, does it work for $\widehat{\alpha\beta}$?

Let $\textbf{X}_1, \dots, \textbf{X}_n$ be an (iid) random sample. From this random sample, we compute $\hat{\alpha}$ (an estimation of a certain parameter $\alpha$). Let $\textbf{Y}_1, \dots, \textbf{...
Albert Paradek's user avatar
12 votes
3 answers
2k views

Do the 2.5th and 97.5th percentile of the theoretical sampling distribution of a statistic always contain the true population parameter?

I am trying to understand the validity of bootstrap percentile confidence intervals and I have stumbled on the following from these slides: Suppose we want to set a 95% confidence interval on $θ$, ...
ado sar's user avatar
  • 471
12 votes
1 answer
20k views

Coverage probabilities of the basic bootstrap confidence Interval

I have the following question for a course I'm working on: Conduct a Monte Carlo study to estimate the coverage probabilities of the standard normal bootstrap confidence interval and the basic ...
TheCloudlessSky's user avatar
12 votes
2 answers
3k views

How can I pool bootstrapped p-values across multiply imputed data sets?

I am concerned with the problem that I would like to bootstrap the p-value for an estimate of $\theta$ from multiply imputed (MI) data, but that it is unclear to me how to combine the p-values across ...
tomka's user avatar
  • 6,604
12 votes
1 answer
2k views

Calculating confidence intervals for mode?

I am looking for references about calculating confidence intervals for mode (in general). Bootstrap may seem to be natural first choice, but as discussed by Romano (1988), standard bootstrap fails for ...
Tim's user avatar
  • 139k
12 votes
0 answers
1k views

Computing a bootstrap confidence interval for the prediction error with the percentile and the BCa method

I have two related questions regarding the computation of a non-parametric bootstrap confidence interval for the prediction error. Setting: I have a sample S from a data population P and a learner L, ...
Gitte's user avatar
  • 825
11 votes
3 answers
10k views

How do we create a confidence interval for the parameter of a permutation test?

Permutation tests are significance tests based on permutation resamples drawn at random from the original data. Permutation resamples are drawn without replacement, in contrast to bootstrap samples, ...
Yorgos's user avatar
  • 6,524
11 votes
2 answers
5k views

How to calculate the confidence interval of the x-intercept in a linear regression?

Since standard error of a linear regression is usually given for the response variable, I'm wondering how to obtain confidence intervals in the other direction - e.g. for an x-intercept. I'm able to ...
Marc in the box's user avatar
11 votes
1 answer
3k views

Using bootstrap to obtain sampling distribution of 1st-percentile

I have a sample (of size 250) from a population. I do not know the distribution of the population. The main question: I want a point estimate of the 1st-percentile of the population, and then I want ...
Richard Hardy's user avatar
11 votes
1 answer
9k views

Confidence interval for the difference of two means using boot package in R

I have two samples, one of size 52, and one of size 31, that are obtained at different times. I'd like to get a 95% bootstrap confidence interval for the difference between the means of the ...
user765195's user avatar
  • 2,215
11 votes
1 answer
1k views

Why does bootstrapping the residuals from a mixed effects model yield anti-conservative confidence intervals?

I typically deal with data where multiple individuals are each measured multiple times in each of 2 or more conditions. I have recently been playing with mixed effects modelling to evaluate evidence ...
Mike Lawrence's user avatar
10 votes
1 answer
3k views

Can bootstrap resampling be used to calculate a confidence interval for the variance of a dataset?

I know that if you re-sample from a data set many times and calculate the mean each time, these means will follow a normal distribution (by the CLT). Thus, you can calculate a confidence interval on ...
casandra's user avatar
  • 623
10 votes
1 answer
4k views

Estimate confidence interval of mean by bootstrap t method or simply by bootstrap?

When estimating the confidence interval of mean, I think both the bootstrap t method and the nonparametric bootstrap method can apply, but the former requires a little more computation. I wonder ...
Tim's user avatar
  • 19.5k
10 votes
2 answers
1k views

Which Bootstrap method is most preferred?

Maybe this question depends on the given data, but is there a "better" bootstrap method than the others? I'm simply using a one variable dataset (that consists of the differences between football ...
Brandon's user avatar
  • 201
10 votes
1 answer
2k views

Bootstrap confidence intervals on parameters or on distribution?

Excuse what may be an obvious question about bootstrapping. I got sucked in the Bayesian world early and never really explored bootstrapping as much as I should have. I ran across an analysis in ...
Aengus's user avatar
  • 906
9 votes
2 answers
15k views

Understanding bootstrap method for confidence interval of correlation coefficients

Please correct me where I'm wrong: My understanding of bootstrapping is that it is a way to estimate the distribution of some statistic (mean, standard error, Pearson's correlation coeff, etc), given ...
Emily Chen's user avatar
9 votes
1 answer
249 views

Using the bootstrap estimates to compute the acceleration parameter for BCa bootstrap CI

I have noticed different software use different method of calculating the acceleration parameter, $a$, for computing the bias-corrected and accelerated (BCa) bootstrap confidence interval (CI). In ...
Noah's user avatar
  • 34.1k
9 votes
1 answer
1k views

Bootstrapping a sample from a finite population

Can someone point me to some reference for theory on bootstrapping a sample took from a population of known size? I am used to use Bootstrap to calculate confidence intervals of a sample when the ...
Inox's user avatar
  • 191
9 votes
1 answer
373 views

Multiple comparisons correction for dependent comparisons

In this blog post the authors discuss simultaneously estimating quantiles, and constructing a simultaneous confidence envelope for the estimation which covers the whole quantile function. They do this ...
crf's user avatar
  • 309
9 votes
1 answer
572 views

Restricting minimum subgroup size in a bootstrap resampling study - why is this approach wrong?

I'm currently doing a simple re-sampling study where I compare different methods for generating the confidence interval for linear regression models. I'm trying to follow Burton et. al's (2006) ...
Max Gordon's user avatar
  • 5,946
9 votes
1 answer
772 views

95% confidence intervals on prediction of censored binomial model estimated using mle2 / maximum-likelihood

I am working on a problem in which I have multiple pairs of currently living males i that each have a presumed paternal ancestor ...
Tom Wenseleers's user avatar
9 votes
0 answers
214 views

Efficient nonparametric estimation of confidence intervals and p-values for nonlinear regression

I'm estimating parameters for a complex, "implicit" nonlinear model $f(\mathbf{x}, \boldsymbol{\theta})$. It's "implicit" in the sense that I don't have an explicit formula for $f$: its value is the ...
DeltaIV's user avatar
  • 18.1k
8 votes
2 answers
655 views

Strange pattern in standard deviation confidence interval estimation via bootstrapping

I wanted to estimate confidence interval for standard deviation for some data. R code looks like follows: ...
user16's user avatar
  • 145
8 votes
3 answers
4k views

Calculate accelerated bootstrap interval in R

I am trying to to calculate bootstrap confidence interval on an index calculated from a vector of values, and if the index is significantly greater than 0 in R. For example, the vector of length 6: <...
slicer's user avatar
  • 603
8 votes
2 answers
619 views

What are good references on calculating confidence intervals using subsampling or the delete-d jackknife?

I searched for references on using subsampling or the delete-d jackknife to calculate confidence intervals but wasn't able to find much. Could someone please offer more reference on using subsampling ...
Tianyang Li's user avatar
8 votes
1 answer
346 views

What is the confidence interval of a p-value?

The $p$-value is used to report how strongly we can presume against an hypothesis. As is clear, this $p$ value is itself estimated from data and if new data where collected in the same conditions, the ...
Denis Cousineau's user avatar
7 votes
3 answers
2k views

Bootstrap confidence interval on heavy tailed distribution

I read from Wikipedia: ... if one performs a naive bootstrap on the sample mean when the underlying population lacks a finite variance (for example, a power law distribution), then the ...
Eric Kim's user avatar
  • 1,041
7 votes
1 answer
1k views

Why (mathematically) is the parametric bootstrap usually better than the empirical one?

As I know from experience, the parametric bootstrap performs better in terms of coverage probability for confidence intervals then the empirical bootstrap. Of course, this makes sense because you put ...
BootstrapBill's user avatar
7 votes
3 answers
3k views

Why are my bootstrap confidence intervals for regression coefficients consistently wider than standard confidence intervals?

I am very new to statistics and analytics. I have some basic undergrad stats and am now studying O'Reily's Practical Statistics for Data Science. I have been doing some bootstrapping exercises on home ...
Marty's user avatar
  • 73
7 votes
1 answer
6k views

Bias-corrected percentile confidence intervals

I'm trying to estimate bias-corrected percentile (BCP) confidence intervals in R on a vector from a simple for loop used for resampling. I am primarily looking for help implementing the calculation on ...
jCeradini's user avatar
7 votes
2 answers
2k views

Using bootstrap for glm coefficients variance estimation (in R)

I am fitting a GLM model (in R), and would like to get an estimation of the variability of the coefficients estimated by the model. If I understand it correctly the method to use in such a case is ...
Tal Galili's user avatar
  • 21.7k

1
2 3 4 5
8