Tagged Questions

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

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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 ...
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1answer
16 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 ...
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2answers
92 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 ...
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13 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 ...
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5 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 ...
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0answers
40 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. ...
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32 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
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0answers
26 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. ...
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31 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 ...
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1answer
68 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 ...
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1answer
54 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 ...
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41 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 ...
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10 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 ...
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20 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 ...
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0answers
29 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 ...
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0answers
17 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 ...
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2answers
82 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 ...
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39 views

Bootstrap robust regression

I'd like to do a robust hierarchical regression using bootstrapping because regression diagnostics indicate that assumptions of ordinary regression have been violated. I've made a start using the ...
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14 views

Mediation analysis using Bootstraps

I have used Hayes' plugins (PROCESS and INDIRECT) in SPSS. My result shows that all four paths (a,b,c,and c') are significant i.e. have a p-value of less than 0.05. In all the examples I have ...
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1answer
32 views

Bootstrapping coxph after model averaging

I have selected 7 coxph models using AIC, and did model averaging to obtain model averaged parameter estimates. I wanted to plot the survival curve from the averaged model, and I found someone with my ...
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1answer
186 views

How to interpret variables that are excluded from or included in the lasso model?

I got from other posts that one cannot attribute 'importance' or 'significance' to predictor variables that enter a lasso model because calculating those variables' p-values or standard deviations is ...
1
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1answer
66 views

Power-law fitting and testing

I want to test the distribution that best fit a specific metric (that I call SD) extracted from the source code of systems. I have a guess that they follow a power-law behavior. My sample: 20 ...
3
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1answer
54 views

Bootstrapping Hmisc::rcorrp.cens for paired concordance?

As Frank Harrell says here and other places, it's better to compare two predictive models (Cox proportional hazards in this case) wrt discrimination (C-index) using the paired U-statistic ...
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1answer
51 views

Using Bootstrap to estimate confidence interval of the standard deviation

I am trying to compare two different methods of estimating confidence intervals: a parametric approach that uses the assumption that the sample is t-distributed (i.e. the formulas that are given here: ...
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20 views

Expected survival time: comparisons when measurements are an average over other measurements?

Set up We have a few types of interventions. For each intervention, a failure occurs randomly at some time $t$ after start for each subject. We take $n$ measurements of $t$ using $n$ subjects, and ...
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1answer
56 views

GBM Bootstrap Prediction Interval Code Error

based on code presented in thread: How to find a GBM Prediction Interval I am trying to apply this to my dataset. Below is my full code, and I am having issues with the bootstrap function. ...
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31 views

Implementing the 0.632+ bootstrap method using the Weka Java API

I am trying to implement the 0.632+ bootstrap estimator (as proposed by Efron and Tibshirani 1997) in order to perform certain benchmarks and compare it with other cross-validation methods, such as ...
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27 views

Bootstrap confidence interval for case control data in R

I have a matched case-control data material and am estimating a risk-measure parameter with a certain estimator. I want to use bootstrap methodology to estimate confidence intervals for the parameter ...
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14 views

Extending a bootstrap confidence interval to a larger population with a non-normal distribution

Using Python/SciPy I calculated a bootstrapped CI on my sample. ...
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1answer
39 views

Calculate sample statistics for estimated parameters of a model [duplicate]

How some standard package (eg R, SAS or Excel) calculate Standard error for the estimated parameters for a model. my understanding : While using gradient descent optimization method( as performed ...
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1answer
43 views

Out-Of-Bag estimate in scikit-learn

I am using a bagging model from the Python Scikit-Learn module: ...
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0answers
62 views

Why do my boostrapped CI's (using boot.ci in R) not include the point estimate?

I'm interested in estimating an average treatment effect $$ \operatorname{ATE}\left(A', A''\right) = \mathbb{E}\left( Y\ |\ A'' \right) - \mathbb{E}\left( Y\ |\ A' \right) $$ with a generalized ...
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0answers
14 views

How can I estimate (with confidence intervals) the divergence between two smoothing splines?

I have time series data from two independent groups. I want to know whether these groups diverge over time and, if so, when they diverge and for how long. The way I have done this is to estimate ...
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1answer
41 views

Estimating Standard Errors for Markov Transition Probability with Multiple Observations (in R)

I was trying to estimate a Markov transition table from paired transition data, which look something like this: ...
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1answer
36 views

Can I use bootstrapping in this situation?

I'm faced with a situation where there are few observations of a life insurance product in some cells, where the observations are deaths. The problem is that I need to calculate standard deviations ...
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33 views

Need to transform data before running mediation/model with bootstrapping (PROCESS)?

I am reading through Hayes' book on mediation and moderation analysis (2013) which describes the PROCESS macro he created to use bootstrapping in order to arrive to confidence intervals to check the ...
0
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1answer
78 views

Can I Calculate the MSE for a Linear Regression Model using a Bootstrap?

I'm currently reading the book, An Introduction to Statistical Learning, and I'm struggling a little with the bootstrap approach. As far as I understand, I can use a bootstrap in almost all situations ...
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0answers
22 views

Follow-on to “Training with the full dataset after cross-validation” - sequential parameter estimation

Background: Here is the background for the question, both the question itself and the answer given by Dikran Marsupial. Training with the full dataset after cross-validation? It asks about after ...
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53 views

Bootstrapping interaction effects with boot() and the effects package - environment problems?

UPDATE AT BOTTOM - workaround and exciting new roadblock! UPDATE #2: SOLVED. Details at bottom. This is a combination stats/programming question, so I apologize if it should go somewhere else. I'm ...
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1answer
27 views

Evaluating a fixed classifier

I have a classifier that is fixed and wish to evaluate its predictive performance using a test dataset. I'm familiar with the situation (e.g. in k-fold CV) where the data is split and the classifier ...
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0answers
16 views

Calculate standard error in state space model in R

I am estimating a DFM in state space form in R. I have used the function spg from the package BB (optim was not working) and dlm to optimize so now I have the parameters of the filter. I now would ...
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19 views

Batched bootstrap for non-parametric confidence intervals

I am conducting multiple experiments on moderately large datasets that run over several weeks. I would like to construct confidence intervals for my estimators which are a mixture of means and ratio ...
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0answers
8 views

Bootstrapping with random effects in SPSS

I'd like to use bootstrapping in my two-way ANOVA containing two fixed and one random factor. Why is the bootstrapping method not available (greyed out) for models containing a random factor? Thanks! ...
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0answers
45 views

Validating Bootstrapped Probability of Survival Results From Small Sample Size Data

Quite often in industry, due to cost and schedule constraints, decisions must be made on small sample size data. I have 4 cycles-to-failure values resulting from running samples to failure in a ...
2
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0answers
51 views

Bootstrapping some statistics with non-normal data

I am new to bootstrapping. Assume I have some non-normal data, can be any distribution, it doesn't matter, and I want to find a confidence interval for the mean, median and standard deviation. For the ...
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1answer
68 views

Are there problems with arbitrary application of bootstrap?

Suppose I have a statistics (say a price index) and I want to obtain standard errors for it. I have heard that blind application of bootstrap may not be a good practice. If true 1- What could go ...
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2answers
31 views

Confidence bands for difference of time series

Assume that I have two time series $Y_{1t}$ and $Y_{2t}$ that are sampled at the same frequency. Is there a way to quantify the uncertainty in their difference $Y_{1t} - Y_{2t}$? That is, can we get ...
0
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0answers
30 views

Bootstrapping in SAS - PROC LOGISTIC - Next steps ? how to score / perform diagnostics?

My question is as follows. I am referencing the following paper by David Cassell - wherein David talks about bootstrapping techniques in SAS using PROC SURVEYSELECT (many thanks to David - truly a ...
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0answers
50 views

State Space models with Short Time Series

My problem is that I have a state space model that I estimate using the Berndt–Hall–Hall–Hausman (BHHH) algorithm. The state space model is relatively simple in that the hidden part follows a pure ...
2
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1answer
50 views

Relative increase between two pairs of samples

Consider the following samples from four distributions: $a = \{20, 2, 200\} \qquad\qquad c = \{1, 10, 100\}$ $b = \{22, 2.2, 220\} \qquad\quad\:\,d = \{1.2, 12, 120\}$ I would like to say that the ...