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

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Bootstrapping Kruskal-Wallis test of significance

I am working with a set of 6 variables collected at 4 time periods (I consider each time period as a class in the following). For each time period, I have 82 397 observations. If I plot the mean and ...
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Prediction intervals for forecasts using spectral analysis

I have circadian data which typically have a period of around 24 hours so using spectral analysis seems appropriate. I've used spectrum resampling which is quite robust to changes in period which ...
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2answers
60 views

Logistic regression with bootstrap, how to interpret high standard errors and choose coefficient?

I am attempting to do a logistic regression bootstrap with R. The problem is I get high SE's. I'm not sure what to do about this or what it means. Does it mean that bootstrap does not work well for my ...
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Error propagation over percentile confidence intervals for bootstrapped regression coefficients

I apologize if this is extremely simple or I'm going about this the wrong way or it has been asked before. Please point me in the right direction if so as I might just be searching the wrong question. ...
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39 views

why bootstrap result in overfitting for randomForest prediction?

I am dealing with an imbalanced dataset with the R package randomForest. Some one has suggested that, Bootstrap your data while over-sampling the rare class and under-sampling the typical class. But I ...
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10 views

Differences between cross validation and bootstrapping to estimate the standard error of the AUC of a given ROC curve

I know there's been some discussion on differences between CV and bootstrapping for estimating out-of-sample prediction error of a classifier. For example, in here (Differences between cross ...
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43 views

How to show that stability is improved when using bagging in an unsupervised context?

I have a data set of 200 observations and around 10 continuous variables. I would like to build a graphical model to study dependencies between variables. Unfortunately, my data is not very stable. ...
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17 views

How to properly perform multiple imputations when using cross-validation procedures

I am trying to understand the association of an exposure on an outcome. In a dataset of ~600, approximately half the population does not have a measured exposure. We have predicted their exposure ...
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17 views

How to get the variance of the sample standard distribution? By bootstrapping observed values or by standard deviation distribution statistics

Let $Y(x)\sim\mathcal{N}(0,\sigma(x)),x\in\mathbb{N}$ be a random variable depending on $x$. Let $y_i(x_i),x_i\in\mathbb{N},i\in\{1,...,n\}$ be observed values. I have a model $m_\alpha(x)$ to predict ...
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35 views

Bootstrap confidence intervals for regression and correlation coefficients

Take an example of a linear regression, $Y= \beta X$ where X and Y values are z-score transformed ($\mu$ = 0, $\sigma$ = 1). In this situation the correlation coefficient $r$ equals $\beta$ ...
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20 views

Confidence interval for a mean over hierarchical data

What is a good method for producing confidence intervals when computing a mean over hierarchical data? Specifically, I have the text messages sent by group of people and I want to compute the mean ...
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35 views

confint.merMod: Wald, profile, and boot COMPLETELY disagree

So this is either going to be straight forward or else a huge mess. I am finding that bootstrap CI for my glmer models are really wacky-- in fact, they don't even include the point estimates from the ...
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66 views

Significance/confidence intervals for PCA or factor loadings - how can such be defined?

Current discussions here in SSE made me to reconsider the PCA and FA models and procedures. I got curious how one would determine confidence intervals for the components/factor loadings by assuming ...
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48 views

Using bagged ensemble of regression trees, feature selection based on feature importance

I am working on relating aesthetic scores of given images (about 17k training+validation samples and 280 image features) and getting best result using ensemble of CARTs. Beside achieveing a good ...
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23 views

Picking block length in a block bootstrap

I am using the Mann-Kendall test to assess trends in a data time-series. I believe there is autocorrelation in my data and therefore need to use a block bootstrap to correct for it. I have plotted ...
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38 views

Bootstrapping a t-test in R

I have two groups of individuals (22 in each group), which I compared using a t-test. The difference between groups was non-significant (p = .17). Because the p-value was quite low, my supervisor ...
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31 views

Bootstrapping and comparing mean distributions

Is the following a reasonable approach to assess the statistical significance of the difference between two groups' For each group 1) Subsample with replacement 2) Take the mean of the subsample 3) ...
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2answers
28 views

Bootstrapping a t statistic - Rationale and procedure

I was hoping someone could help me out with this. I've seen similar questions on the forum, but I need to know if I've understood the correct rationale and procedure for bootstrapping for my ...
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37 views

How is bootstrapping used for machine learning?

How does one use bootstrapping in a machine learning context? My typical data analysis pipeline is Split data into 10 folds Train classifier with 9 folds Test classifier with remaining fold Repeat ...
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21 views

R: Coping with bad model fit convergence during bootstrap

I'm running into trouble while checking the robustness of a GLM using the bootstrap procedures in R. Basically I want to check whether the estimated coefficient estimates of an existing GLM that I've ...
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1answer
82 views

Why areny my 95% confidence intervals symetrical around the mean?

I am trying to calculate the 95% confidence intervals around a mean value using a bootstrap procedure, from the mosaic pacakge, to deal with some assumption issues in my data. The code below seems to ...
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5 views

Estimate variance of an arbitrary estimator using cross validation

Ron Kohavi's paper "A Study of Cross-Validation and Boostrap for Accuracy Estimation and Model Selection" explains very well how to compute the variance of the estimated accuracy when using CV (or ...
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16 views

Regarding Bootstrap Hypothesis Test for difference of means, why not absolute differences?

Looking at the Algorithm 16.2 from "Introduction to the Bootstrap, Efron and Tibshirani" I was wondering why isn't the t(.) being tested the absolute difference of the means, instead of the ...
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209 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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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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36 views

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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Nonparametric bootstrap with the fitdistrplus package

Suppose I use the nonparametric bootstrap to fit a model as so: ...
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82 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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28 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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44 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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29 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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69 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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92 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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39 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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10 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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17 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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28 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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17 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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1answer
92 views

Random forest for binary 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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9 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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183 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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55 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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35 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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55 views

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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18 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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29 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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148 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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28 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 ...