# Tagged Questions

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

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### Test for comparing highly skewed charge data

I'm looking into comparing charge/cost (economics) data among paired samples (i.e pre vs post). The sample size is about ~150 paired samples, where charge/cost is highly skewed with a long tail. I'm ...
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### bootstrap p value in STATA

I have create a matrix with bootstrap estimation of the ATT. First I extract a sample using bsample command with cluster , then I estimate the propensity score ,and the ATT using the psmatch2 (with ...
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### Bootstrapping test set?

Let's say I have a classification problem with a small and fixed test set. If I train a classifier and report the accuracy on this test set, I know that this estimate has a high variance. Does it make ...
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### Comparing Result of Permutation and bootstrapping

I am trying to verify the correlation between two parameters using bootstrap/permutation methods(classical example!). What i understand is that both permutation and bootstrap method involves ...
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### measuring errors of bias, dispersion and outlier rate

I fit different models to a sample of data using Bayesian statistics. I have obtained for each data point in the sample a posterior probability distribution. Assuming I know the true answers for the ...
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### Is bootstrap approach is reserved for specific data?

Currently, I am working on historic climate variable data of precipitation and temperature. I want to resample my data to find out variability in precipitation and temperature. But I read from ...
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### Bootstrapping a Kernel Density: Help in interpreting R code

I found this excellent code snippet online which gives the code for boostrapping a kernel density estimate to get confidence bands. Now, I am not that well versed in R, and would like to know what's ...
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### explanation of a timeseries bootstrap to a layperson

I am trying to explain the output of a time-series bootstrap to someone who knows nothing about them. I recently learned about them myself and wanted to make sure my explanation was correct. Is this ...
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### Bootstrap vs Standard Estimation

Suppose I have an estimate (say an OLS coefficient), I can obtain its standard error using the standard OLS formula. I can also use nonparametric bootstrap and compute the standard error. My question ...
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### Making use of SEs of parameter estimates when making group comparisons

I have a bunch of behavioural data and collapsed every individual participant's responses into a single parameter (threshold of a psychometric function but that's not really important) for which I ...
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### Since we use Bootsrap to approximate the SE, can we use Bootstrap to find prediction errors?

Instead of using Cross-validation, or K-fold Cross-validation, can we use Bootstrap to generate random samples and use one of them as test set, and others as training set?
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### R, glmer(), plot bootstrapped CI in graph

Using the glmer() function in the LME4-library in R I computed logistic models, of the form: Y ~ cat1 * cont1 + (1|Subject) where, obviously, Y is the binomial outcome variable (0 or 1), cat1 is a ...
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### Generating bootstrapped samples for gene expression time series

I have multiple gene expression profiles, measured at 23 time points with one measurement per time point (there's two at the start, but that's irrelevant for the rest of the question). Due to the ...
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### Level of Mutual Information Among Bootstrap Samples vs. Delete-50% Jackknife Samples

Q: I wondered if anyone could offer a mathematical proof or similar, that, on average, delete-50% jackknife samples are not inherently more “independent,” in terms of information content, than ...
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### Random forest block observations bootstrap samples / OOB observations

I would like to use random forest regression for prediction of schizophrenia-related continuous measures from genetic data. However, I have siblings in my data which would still be problematic with ...
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### Is it legitimate to use bootstrap to estimate regression parameter with hypothetical sample data?

Consider a simple OLS model: $$y = \beta_0 + \beta_1x_1 + \beta_2x_2 +\epsilon$$ Suppose $x_2$ is dummy variable which has value either 1 or 0 and the model is successfully fitted with collected ...
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### Bootstrap comparison of group means instead of ANOVA/tukeyHSD

I have several groups (~30, >100 data points per group) and would like to see if there are differences between the group means and where. Both ANOVA and Kruskal-Wallace say yes and I'd like to see the ...
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### optimism-corrected regression coefficients using Frank Harrell's method?

I used a regularized (LASSO) cox regression to estimate relapse times of patients and used Frank Harrell's bootstrapping method to obtain an optimism-corrected performance estimate of my model. I am ...
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### Bootstrap in meta-analysis

I am conducting a network meta-analysis of clinical trials on cardioprotective drugs in patients undergoing chemotherapy (see PROSPERO protocol CRD42015029915), and I was wondering whether it would ...
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### error propagation on the median

Suppose to have a set of exact data $x_i, i=1,\dots,N$ and to calculate its median value $m$. Then, a sound way to estimate the error $\delta m$ on $m$ would be bootstrapping. (I think...) But what ...
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### How to determine if sampling is representative/similiar to my population

Let say for whatever reason I have obtained a sample of an initial population. (ie. we have paired case:controls on a set of confounders). I wish to compare how representative my sampled (or let me ...
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### Significance of differences using bootstrapping

I have a matrix that I divide into 4 quadrants: Upper left, upper right, lower left, lower right. I want to know whether the ratio of the lower quadrants is significantly difference from the ratio of ...
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### Measure relationship between continuous variable & unbalanced binary variable

I am trying to select variables for modelling a binary variable (whether a person will repay a loan) using various continuous variables about them - age, income, years of education, etc. I'd like to ...
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### Scalable Random Forest For Massive Data

My problem is simple. I want to train a dataset using random forest on a huge dataset (with $n$ rows). Let's assume I can only fit $b < n$ rows in memory at a time. Model Choice I see several ...
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### Covariance between non symmetrical matrices with a unidirectional composition

I am trying to explain variation in why some researchers go to certain places and not others by analyzing how many articles scientists from one publish about another location. My matrix is ...
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### Which proportions are particularly high or low - compare confidence intervals, or logistic regression?

I have a large database of binary decisions (accept or reject), broken down by state of the applicant, so that for each state I can calculate a proportion of positive decisions. e.g. ...
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### Glmnet — Confidence Interval in Regression

In general, my question is how to estimate some prediction intervals in the case of penalized linear models (in particular, I think about the glmnet R package). I understood that the introduction of a ...