The bootstrap is a resampling method to estimate the sampling distribution of a statistic.

learn more… | top users | synonyms

0
votes
0answers
26 views

Bootstrapped BCa confidence interval of median (R package simpleboot) does not correspond with Wilcox.test p value

I am using R to compare the medians of two groups. Each individual has received a score of between 0 and 100. Both distributions are very skewed. The median of group A (n=33) is 87.8 (IQR 75.1, 100.0) ...
12
votes
3answers
124 views
+50

When is the bootstrap estimate of bias valid?

It is often claimed that bootstrapping can provide an estimate of the bias in an estimator. If $\hat t$ is the estimate for some statistic, and $\tilde t_i$ are the bootstrap replicas (with ...
0
votes
0answers
15 views

Bootstrapping - Variance of Time Series with Micro-level Data

I have micro-level (individuals) time series data and I am able to calculate some aggregate statistic for each time period. The data is not a panel, so each month is a different cross-section of ...
0
votes
0answers
15 views

MC to estimate coverage probability of bootstrap [closed]

I am a novice at R-coding but I am trying to use Monte Carlo to estimate the coverage probability of standard normal bootstrap, basic bootstrap, and bootstrap percentile with bias correction. The MC ...
2
votes
1answer
38 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 ...
8
votes
2answers
269 views

Best suggested textbooks on Bootstrap resampling?

I just wanted to ask which are in your opinion the best available books on bootstrap out there. By this I don't necessarily only mean the one written by its developers. Could you please indicate ...
1
vote
0answers
18 views

Bootstrapping and comparing Gini coefficients

for my dissertation I need to compare the Gini coefficients of 5 different markets with approx. the sample population size. I would like to do bootstrapping to compare the means (instead of ...
2
votes
3answers
127 views

Bootstrap two-sample t test

I'd like to bootstrap a two sample t-test. My DV is some psychological variable. I have two groups (women and men), unequal sizes and I do not assume equal variances. I'm not sure if my code or/and my ...
2
votes
2answers
40 views

Bootstrapping and Kolmogorov-Smirnov

Here is an experiment I did: I bootstrapped a sample $S$ and stored the results as empirical distribution under the name $S_1$. Then I bootstrapped $i=10000$ times in a row the same sample $S$ and ...
1
vote
0answers
25 views

Difference between bootstrap estimations and full data estimations

Good day. I am using an ensemble machine learning algorithm (SuperLearner) to predict XYZ. I'm finding that there is quite a difference between the predicted XYZ when using the full data and the ...
2
votes
0answers
29 views

When to use a bootstrap in MLE

Suppose I have a data set of $n$ observations with the dependent variable sample $\mathbf{Y} \in \mathbb{R}^{n \times k}$, and independent variable sample $\mathbf{X}\in \mathbb{R}^{n \times l}$ such ...
0
votes
1answer
19 views

Which performance measure to report?

I've trained a random forest regression model using boot632 resampling and the caret package. The output of the model tuning process gives a few different performance measures. ...
1
vote
1answer
23 views

What does “randomly permuted” mean in the context of the randomized cluster bootstrap?

I have read, in the context of boostrapping clustered data, Davison and Hinkley (1997), pages 100–102, discussed the randomized cluster bootstrap (‘Strategy 1’) in which clusters are selected by ...
2
votes
0answers
32 views

Bootstrapping to create confidence interval

I have about 50 or so observations of x,y pairs. The relationship I am trying to learn is a quadratic relationship between x and y. While fitting the quadratic, I am also interested in learning ...
4
votes
1answer
77 views

Expected proportion of the sample when bootstrapping

suppose you have a sample of size $N$ that for some reason you want to bootstrap to produce a sample of size $M$. I am trying to produce a closed form solution for the expected proportion of the ...
1
vote
1answer
71 views

Increasing sample size with bootstrap sampling

I'm trying to perform some classification analyses with a relatively small dataset (201 observations, 32 predictors). There are 8 classes in my data with unequal sample sizes ranging from 10 in the ...
1
vote
0answers
25 views

approaches for computing confidence band and prediction band for general regression analysis and predictive models

In linear regression model, the predict in R is able to calculate the confidence band and ...
0
votes
1answer
39 views

How to bootstrap panel data?

I'm fitting some machine learning algorithms (e.g. SVM) on my panel data. It's taking too long for my entire dataset, so I'm considering generating smaller samples from bootstrapping then fit the SVM ...
1
vote
1answer
49 views

Bootstrap glm and extract pvalue

I am running a glm model using bootstrap, I can extract the coefficient mean and the confidence intervals for all the factors in my model. But how can I get the pvalue from there? Model: ...
0
votes
0answers
46 views

What is bootstrapping

The bootstrap is a resampling method to estimate the sampling distribution of a statistic. This is what the tag description says on this website. I am a layman, can someone please help me understand ...
1
vote
0answers
43 views

Rate of convergence of the coverage probability of bootstrap confidence intervals

I was wondering if someone knows good books or references that deal with this subject : "The rate of convergence of the coverage probability of bootstrap confidence intervals" Many thanks for your ...
1
vote
0answers
39 views

Bootstrapping with bootstrap sample greater than original sample

My original sample has 350 observations drawn randomly from a population of 60,000 people. My independent variable is Default, with 35 observations with value of ...
0
votes
0answers
8 views

Romer and Romer Replication

I am currently trying to replicate "The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks" The paper and the dataset is available here: ...
4
votes
0answers
30 views

Rank deficient bootstrap resamples

Despite years of stat courses I'm afraid I may still not completely understand bootstrapping. My question here relates to nonparametric boostrapping of regression models. As i understand it you draw ...
0
votes
0answers
29 views

How to use/interpret bootstrapping?

I am working on an stochastic optimization problem. Now I have come across the idea of using Monte Carlo sampling approach to solve it. I need the empirical distribution or the true distribution of ...
1
vote
0answers
12 views

Normality violations in multiple regression - report bootstrapped CIs, p values & t values?

I have analysed some data for a research project using multiple linear regression. However, normality assumptions for this method were not met in my data (and could not be resolved using ...
0
votes
0answers
22 views

Latent Class Analysis — 0.632+ Bootstrap vs. Bayesian LCA and Empirical Bootstrapping?

I am working on a project that involves the use of latent class analysis (LCA) and have been thinking about how best to perform variable selection (with relatively high-dimensional data [approximately ...
1
vote
1answer
42 views

How to deal with bootstrap replicates that fail to converge?

I'm using a wild bootstrap to explore the confidence intervals of a nonlinear regression mixed-effects model (specifically one that was solved using nlmer). The ...
0
votes
0answers
13 views

When should we use the parametric bootstrap, or the non-parametric bootstrap?

I would like to know when would we use the parametric bootstrap, but not the non-parametric, and vice-versa? The only reason I could was when the statistic we're interested in has some nuisance ...
0
votes
0answers
11 views

Why do we usually use a Likelihood ratio statistic when using bootstrap?

The examples I'm reading of uses of bootstrap (in A.C. Davidson book about bootstrap, chap.4) always use the likelihood ratio. Is there any reason for it? Why not use any another statistic, since when ...
0
votes
1answer
26 views

Bootstrap significance test

I'm using the bootstrap method to test my experiment results for significance. I have two sets (say A & B) of 50 grades, for which I want to test whether their means are significantly different. ...
0
votes
0answers
50 views

Nonparametric bootstrap of one-sample Kolmogorov-Smirnov goodness of fit test

I'm fitting a Weibull distribution to some forestry data and I want to perform a test of whether or not there is sufficient evidence to indicate that the data does not come from a Weibull ...
2
votes
1answer
52 views

Inconsistent outcomes of boostraped hypothesis tests on max and median

I am trying to make an hypothesis test using bootstrapping. I compute a quantity Q from a sample set (the exact calculation should not be relevant, but let's say ...
0
votes
0answers
21 views

Fundamental Issues with Influence weighted resampling for bootstrapped predictions

I have a large database 1mill+ from which it is known that there are many influential points and outliers. I am interested in generating a series of predictions from subsets (1,000+) of the data and ...
0
votes
1answer
31 views

Correlation coefficient significance based on bootstrap distribution

There is data $x$ and $y$ which does not come from two dimensional normal distribution. However I would like to perform correlation coefficient test. For this purpose I have created the bootstrap ...
2
votes
2answers
114 views

Logistic Regression sample size & bootstrapping

The data for this example can be retrieved here so that you can reproduce these estimates. It is the low birth weight dataset- http://www.umass.edu/statdata/statdata/data/ There are 59 1's and 130 ...
0
votes
0answers
28 views

P value distribution skew & hypothesis testing

On this page it says ...if HA holds, the p-values have a distribution for which values near 0 are more likely than values near 1. However the p-values may have a distribution that is not ...
0
votes
0answers
9 views

Reporting sensitivity/specificity using a random process?

I'm using a method that involves cross-validation to make predictions on my dataset. As it splits the data randomly, I will end up with different results (I believe this is an example of a stochastic ...
1
vote
0answers
47 views

Bootstrapping a bootstrap

One of the criticisms of using a bootstrap procedure is that the results are not reproducible in the sense that you may come to a different conclusions when you re-run the bootstrap analysis again. ...
1
vote
0answers
40 views

attenuation percentage and confidence interval

I made a logistic regression model 1 (not fully adjusted) and model 2 (fully adjusted; model 1 + covariate A) with Stata. I am trying to calculate the attenuation percentages between OR. I used the ...
2
votes
0answers
27 views

How to determine a probability that 100% of confidence intervals from a bootstrap contain the true mean

Say I take 500 bootstraps of a population and calculate 95% confidence intervals (CIs) for each sample. I would expect that 95% of the bootstrap sample CIs to contain the true population mean. ...
1
vote
0answers
36 views

How to test a claim about a confidence interval (real case)

I need to test a claim made by a company stating that 95% of the cases (passangers per day, peak hour) are processed in 40 minutes or less. 1 - I assume I must collect a passanger sample but how ...
3
votes
1answer
83 views

Bootstrapping the data to set up a prior

I am using a Gaussian model with a conjugate Normal-Inverse-Wishart (NIW) prior, as described here. The advantage of this approach is that the marginal likelihood $p(y)$, which is what I am interested ...
0
votes
1answer
60 views

When to use bootstapping in regression analyses?

When I run a regression analysis in SPSS, one of my predictor variables just fails to reach significance, p = .06. When I apply bootstrapping, the output tells me the predictor has a significant ...
0
votes
0answers
106 views

How to interpret the results of bootstrapping and Monte Carlo simulation utilised to test lasso logistic regression results?

My situation: sample size: 116 binary outcome (32 events) number predictors: 42 (both continuous and categorical) predictors did not come from the top of my head; their choice was based on the ...
0
votes
0answers
17 views

Estimating cutoff point for sampling using bootstrapping

I'd like to determine a cutoff point for plot sampling. So far, I've sampled intensively and collected fecal pellet data for 13 forested stands. Each stand has 50 plots and the mean pellets per ...
0
votes
0answers
35 views

Looking for a better post-hoc analysis

I'm a PhD student in Neuroscience, with a master degree in Psychology and I use R for my statistical analyses. As you know, in NHST usually post-hoc analysis in continuous data are essentially ...
0
votes
0answers
51 views

lmer4, p-values, confidence intervals and bootstrapping

I have a mixed linear model made with lmer in R and find that my qq-plot looks rather much like the symbol of a famous superhero. My x-parameters are all factors but I have tried all transformations I ...
1
vote
0answers
19 views

SPSS Bootstrapping Medians - Two Groups Over Time

I am evaluating the effects of two different teaching methods for chest compressions during CPR over time. I have four sets of data: a control and study group compressions per minute on the first day ...
3
votes
2answers
95 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 ...