Does bootstrapped regression allow for inference? The 2019 Stack Overflow Developer Survey Results Are InObtaining and interpreting bootstrapped confidence intervals from hierarchical dataDistribution of reciprocal of regression coefficientHow to determine if predictor in piece-wise linear regression is significant?Non-technical conditions for validity of nonparametric bootstrap confidence intervalsBootstrapped coefficients for ordinal logistic regression with Rbootstrapped standard error to make inference about difference of meansBootstrapping multivariate multiple variable regressionFor a Fisher Information matrix $I(theta)$ of multiple variables, is it true that $I(theta) = nI_1(theta)$?Bootstrapping to measure the significance of the skewnessBootstrapped confidence interval for the difference in means for paired data
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Does bootstrapped regression allow for inference?
The 2019 Stack Overflow Developer Survey Results Are InObtaining and interpreting bootstrapped confidence intervals from hierarchical dataDistribution of reciprocal of regression coefficientHow to determine if predictor in piece-wise linear regression is significant?Non-technical conditions for validity of nonparametric bootstrap confidence intervalsBootstrapped coefficients for ordinal logistic regression with Rbootstrapped standard error to make inference about difference of meansBootstrapping multivariate multiple variable regressionFor a Fisher Information matrix $I(theta)$ of multiple variables, is it true that $I(theta) = nI_1(theta)$?Bootstrapping to measure the significance of the skewnessBootstrapped confidence interval for the difference in means for paired data
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
$begingroup$
Assuming a linear model of
$$ y = beta_0+beta_1x+epsilon $$
I can construct a bootstrapped confidence interval for the estimate of $beta_1$ by sampling with replacement from all of the $(x_i, y_i)$ pairs from the data.
Is it possible for me to tell if the value of $beta_1$ is significant, without preforming a t-test the data? Or is the bootstrap used more less for inference but more for trying to find the most accurate predictor in this case?
statistical-significance inference bootstrap
$endgroup$
add a comment |
$begingroup$
Assuming a linear model of
$$ y = beta_0+beta_1x+epsilon $$
I can construct a bootstrapped confidence interval for the estimate of $beta_1$ by sampling with replacement from all of the $(x_i, y_i)$ pairs from the data.
Is it possible for me to tell if the value of $beta_1$ is significant, without preforming a t-test the data? Or is the bootstrap used more less for inference but more for trying to find the most accurate predictor in this case?
statistical-significance inference bootstrap
$endgroup$
add a comment |
$begingroup$
Assuming a linear model of
$$ y = beta_0+beta_1x+epsilon $$
I can construct a bootstrapped confidence interval for the estimate of $beta_1$ by sampling with replacement from all of the $(x_i, y_i)$ pairs from the data.
Is it possible for me to tell if the value of $beta_1$ is significant, without preforming a t-test the data? Or is the bootstrap used more less for inference but more for trying to find the most accurate predictor in this case?
statistical-significance inference bootstrap
$endgroup$
Assuming a linear model of
$$ y = beta_0+beta_1x+epsilon $$
I can construct a bootstrapped confidence interval for the estimate of $beta_1$ by sampling with replacement from all of the $(x_i, y_i)$ pairs from the data.
Is it possible for me to tell if the value of $beta_1$ is significant, without preforming a t-test the data? Or is the bootstrap used more less for inference but more for trying to find the most accurate predictor in this case?
statistical-significance inference bootstrap
statistical-significance inference bootstrap
edited yesterday
Richard Hardy
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asked 2 days ago
VastingVasting
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$begingroup$
Is it possible for me to tell if the value of $beta_1$ is
significant, without preforming a t-test the data?
Yes. You could use bootstrap to calculate confidence intervals. Another thing that you could do, is you could take many bootstrap samples from your data, then calculate regression parameters for each of the samples and check how often the parameters calculated on bootstrap samples are greater then zero, where the empirical fraction from bootstrap samples would be equivalent of testing that $beta>0$.
$endgroup$
add a comment |
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$begingroup$
Is it possible for me to tell if the value of $beta_1$ is
significant, without preforming a t-test the data?
Yes. You could use bootstrap to calculate confidence intervals. Another thing that you could do, is you could take many bootstrap samples from your data, then calculate regression parameters for each of the samples and check how often the parameters calculated on bootstrap samples are greater then zero, where the empirical fraction from bootstrap samples would be equivalent of testing that $beta>0$.
$endgroup$
add a comment |
$begingroup$
Is it possible for me to tell if the value of $beta_1$ is
significant, without preforming a t-test the data?
Yes. You could use bootstrap to calculate confidence intervals. Another thing that you could do, is you could take many bootstrap samples from your data, then calculate regression parameters for each of the samples and check how often the parameters calculated on bootstrap samples are greater then zero, where the empirical fraction from bootstrap samples would be equivalent of testing that $beta>0$.
$endgroup$
add a comment |
$begingroup$
Is it possible for me to tell if the value of $beta_1$ is
significant, without preforming a t-test the data?
Yes. You could use bootstrap to calculate confidence intervals. Another thing that you could do, is you could take many bootstrap samples from your data, then calculate regression parameters for each of the samples and check how often the parameters calculated on bootstrap samples are greater then zero, where the empirical fraction from bootstrap samples would be equivalent of testing that $beta>0$.
$endgroup$
Is it possible for me to tell if the value of $beta_1$ is
significant, without preforming a t-test the data?
Yes. You could use bootstrap to calculate confidence intervals. Another thing that you could do, is you could take many bootstrap samples from your data, then calculate regression parameters for each of the samples and check how often the parameters calculated on bootstrap samples are greater then zero, where the empirical fraction from bootstrap samples would be equivalent of testing that $beta>0$.
edited 2 days ago
answered 2 days ago
Tim♦Tim
60k9133228
60k9133228
add a comment |
add a comment |
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-bootstrap, inference, statistical-significance