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

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How to bootstrap means of multiple variables in one command? [on hold]

I would like to get the bootstrapped means of multiple variables in a single bootstrapped sample? Can this be done in R. For example, the following command would allow me to get the means of weight ...
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181 views

Interpretation of a 95% confidence interval calculated via bootstrapping?

I've been thinking about what exactly a 95% confidence interval means when it is calculated via bootstrapping. The formal definition of a 95% confidence interval is something like this: "if the ...
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Cost/Benefit of BootStrapping CIs for dependent samples, but unequal number of observations

In the experiment, subjects were equally exposed to two conditions: 100 of condition_a and 100 of condition_b. A pre-determined response criteria created an unequal number of observations. Thus, no ...
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18 views

Bootstrapping on Cronbachs Alpha? - Is it a good idea?

One can calculate a BCa-CI of Cronbachs Alpha, e.g. using the {psy}-Package. Is this generally a good idea? You can read here about a simulation study in this matter. ...
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Generating predicted mean values and CIs across different groups in lme4

I’ve run a mixed-effects model with crossed random effects in glmer and ultimately want to show a bar graph depicting mean predicted values (and associated confidence intervals) across years within ...
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parametric bootstrap on regression

I keep trying to perform parametric bootstrap on simple regression analysis to grasp the concept. The internet is full of tutorials on non-parametric one, but I found no explanation or steps ...
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10 views

Nonparametric bootstrap with the fitdistrplus package

Suppose I use the nonparametric bootstrap to fit a model as so: ...
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8 views

What causes poor convergence in bootdist?

Here's some sample data below. Only about half of the 1001 iterations converge and I'm curious why? ...
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55 views

Post-hoc power size calculation

I have, probably, a simple problem. I've finished analysing the results of an observational prospective study conducted in our unit. In this study I evaluated if a specific biomarker is independently ...
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20 views

Bootstrap procedure with estimates from EM

I'm a little lost on this, but my question is I implemented an EM algorithm to estimate means and variances of normal distribution, but now I need to implement a bootstrap procedure to estimate the ...
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19 views

How to choose the sample size for a pilot study for making a power analysis?

Suppose one would like to test some new hypothesis, for which there are no previous data available. To estimate the needed sample size, one should do a power analysis. Since there are no previous data ...
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17 views

Power analysis for regression with multiple mediators using bootstrapping (PROCESS)

I am currently trying to help a friend of mine with some statistical analyses for her master project, and she has come up with this question, which might be of interest to others (wel'll see) and to ...
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11 views

R: Do I have to use sample-weights for calculations inside a bootstrap function that allready uses sample weights?

I am using the boot function in R to get standard errors for several statistics (I am doing a oaxaca blinder decomposition). My data (EU-SILC) has sample weights (PB040) for every observation. My ...
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46 views

Bootstrapping time series data: Circular block bootstrap

I have some very basic questions on circular block bootstrap applied to time series (dependent data). Let's suppose, I have a time series data like the one below. I know it's non stationary, but for ...
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81 views

Bootstrapping won't always return population statistics - so why say it does?

I've prowled the interwebs and looked at different questions and answers on the site, including this one: here. But nothing that I've found addresses the following problem. Suppose you flip a fair ...
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1answer
34 views

How to test whether a ratio is different from one using bootstrap?

I have a dataset including two groups of individuals. I get the median of a measurement (say weight) for each group, say W1 and W2 for group 1 and 2, and then get the ratio of the medians W1/W2. How ...
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8 views

What are the criteria to choose for a bootstrapping, frequency, forecasting of fitting method to fit demand data?

My goal is to calculate the inventory height of several products. To do so, I have to calculate the probabillity a certain demand occurres. However to determine the distribution based on historical ...
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14 views

Relation between bootstrap mean and parameter value estimated via maximum likelihood

I have an observed data set $O$ and a synthetic model $S(\theta)$ which attempts to describe it. By fixing $\theta$ to different values I can generate $M$ synthetic realizations of the model: $$S_k ...
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23 views

Graph bootstrapped joint CI of two statistics in R

I have estimated a mixed-effects logistic regression with glmer and want to draw a bootstrapped confidence-region for the mean predicted probability for two subgroups of the sample. I have a $1000 ...
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16 views

Is there a resampling method that blends subsampling with the bootstrap?

I apologize if this is an inappropriate question. I thought of it in class the other day, and I couldn't find a specific answer in my textbooks. I am familiar with the two basic techniques for ...
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44 views

Random forest for panel data

I have a dataset with observations from about 50 countries and 20 years. My dependent variable is binary and I was wondering if I could use random forest to do out-of-sample predictions. My problem ...
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18 views

How can I determine the power of a bootstrap confidence interval?

I'm halfway through an exercise for my statistics class, but completely stuck, and unable to find an answer online or from more statistical friends. Simulating n = 6 observations Xi ∼ Poisson(6), we ...
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6 views

accelerating multi-parameter parametric bootstrap distributions

I've now read most of Ephron and Tibrishani's (1993) Introduction to the Bootstrap. Among other things, it highlights the problem of bias in confidence intervals based on bootstrap percentiles. Bias ...
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166 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 ...
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41 views

why am I getting these warnings when running a bootstrap test in R

After I run a boostrap method in R I get the following warnings: ...
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28 views

Can we use normal distribution statistics on frequency distribution outputted by bootstrapping?

If I understand correctly, this is the bootstrapping procedure: Pretend sample is population Repeatedly resample from this pretend-population Calculate the mean of each resample. The output of ...
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How often will sampling distribution of the mean not be normally distributed?

Kabacoff 2015 suggests that if we're not willing to assume the sampling distribution of the mean is normally distributed, we should use bootstrapping to estimate the sampling distribution of the mean. ...
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12 views

Bootstrapping and classification tables after multiple imputation

I have used the mice code to do my multiple imputation and it gave me gave me an output for my model as well as a new appended dataset using the "long" code. However, I tried to use this new bigger ...
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25 views

Computing Test Statistics when Measurements have Error

Edited to better represent sources of measurement error I have 2 groups of subjects(say male and female centipedes) that I made measurements on(Average length of the subject's leg). The measurements ...
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109 views

Simulating from Kernel Density Estimate (empirical PDF)

I have a vector X of N=900 observations that are best modeled by a global bandwidth Kernel density estimator (parametric models, ...
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19 views

Bonferroni correction of bootstrap generated p values

I have run a multiple regression analysis with 900 independent variables and bootstrapped this analysis 1000 times, with replacement, to generate bootstrap p values. When I looked at the results, I ...
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32 views

Under what conditions on the experiment does bootstrapping work? [migrated]

For a proof I would like to pretend that the uniform distribution on a finite set of samples from a 'source' eventually becomes the source's distribution a.s. when you keep adding samples. I am not ...
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Time Series data used for estimation

I am new to Time Series analysis, but I have Time Series Data. I am trying to estimate the total number of users of a product that occurred over a three month period. I have one observation of the ...
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Why do we need Bootstrapping?

I'm currently reading Larry Wasserman's "All of Statistics" and puzzled by something he wrote in the chapter about estimating statistical functions of nonparametric models. He wrote "Sometimes ...
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47 views

What is Bootstrapping in statistics? How can I use it to determine error in the mean, variance, kurtosis and skewness of a data set?

From what I understood from searching randomly is that it has something to do with resampling. What does this resampling mean? Is it selecting random data from a distribution or is it getting data ...
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72 views

Why is backward elimination justified when doing multiple regression?

Does it not result in over-fitting? Would my results be more reliable if I added a jack-knife or bootstrap procedure as a part of the analysis?
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13 views

Indicator regressions: standard errors

Hi I am estimating a regression of Y on X where both Y and X are indicator variables, that is, they take values 1 or 0. The model is $Y=\beta*X+\epsilon$ (without constant). I use OLS to estimate the ...
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19 views

How to compare models using bootstrap optimism adjusted prediction error?

Let's say I'm comparing the prediction error of two different models. For illustration purposes we'll use a toy example. I've generated 5 bootstrap samples and fit Model A and Model B to each ...
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28 views

How to deal with missing coefficients while bootstrapping regressions

I'm using R boot() function to perform regression bootstrapping. When boot() resamples my data, can happen that some coefficients are missing, especially in the case of factor variables with many ...
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1answer
52 views

Which samples are used in random forests for calculating variable importance?

Each tree of a random forest is learned on a random bootstrapped sample. Consequently, given that the number of trees is large, it is probable that every observation of a data set is used to form at ...
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21 views

Papers suggesting ML and Bootstrapping can be used together?

Does anybody have any good research papers for me to read on whether using bootstrapping and maximum likelihood estimation together is a good idea, particularly when ML is being used with a relatively ...
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27 views

how to interpret output Bootstrapped t-test in SPSS 18

The final table of results when you perform a boostrapped t-test in SPSS include the statistit "bias" (along with Mean Dif., SE, Sig., and CI 95%). This "bias" change slightly every time that I repeat ...
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36 views

Clustered bootstrap for multilevel data with caret train in R

The clustered bootstrap would be appropriate for assessing predictive performance of a model with multilevel data where, for example, students are nested within schools such that there is a non-zero ...
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23 views

summarize the results of multiple regressions done on different subsamples of the same dataset

I want to estimate how robust is the result of a simple correlation test (Y~bX+c) to changes in the number and identity of the observations selected to perform it. For that, I have repeated such ...
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16 views

Wild bootstrap v Pairs and model-based bootstrap

When calculating the standard errors of coefficient from OLS/Huber/LTS/LMS regression models on a data set showing some levels of heteroskedasticity, Paired and model-based bootstrap give rouhgly ...
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23 views

Bootstrapped Regression Residuals

This relates to using bootstrapping of residuals in regression. I do not understand the point of this procedure, i.e. bootstrapping the errors and then adding the residual back to the predicted ...
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2answers
51 views

Non-parametric tests in big data scenario

Suppose I have two populations A and B , with sizes $n_1$ and $n_2$ respectively, where both $n_1$ and $n_2$ are large (say, above 500). I want to test that the values $x_1, \dots, x_{n_1}$ of A ...
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1answer
46 views

Layman's explanation of bootstrap confidence intervals for a regression with percentile method

First of all, I am not a statistician. I only how to interpret stats and to do them with R, my understanding of the math/formulas behind them is virtually zero. With this said, I am looking for a ...
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59 views

Reporting pseudo p-values for bootstrap-estimated linear regression coefficients

I've just received peer reviews for an applied paper that reported a table of multiple linear regression coefficients. While I reported 95% confidence intervals for these coefficients, a reviewer has ...
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12 views

Why are sampled generated by a Circular Block Bootstrap non-stationary

Generally, samples produced by block bootstrap methods do not produce stationary series, even if the original data generating process is stationary. I can see why a moving block bootstrap or ...