Does bootstrapped regression allow for inference?Obtaining and interpreting bootstrapped confidence intervals from hierarchical dataDistribution of reciprocal of regression coefficientNon-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 regressionBootstrapping to measure the significance of the skewnessBootstrapped confidence interval for the difference in means for paired dataAre observations independent in bootstrapped resamples?Bootstrapping Prediction Errors

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Does bootstrapped regression allow for inference?


Obtaining and interpreting bootstrapped confidence intervals from hierarchical dataDistribution of reciprocal of regression coefficientNon-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 regressionBootstrapping to measure the significance of the skewnessBootstrapped confidence interval for the difference in means for paired dataAre observations independent in bootstrapped resamples?Bootstrapping Prediction Errors






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1












$begingroup$


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?










share|cite|improve this question









$endgroup$


















    1












    $begingroup$


    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?










    share|cite|improve this question









    $endgroup$














      1












      1








      1





      $begingroup$


      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?










      share|cite|improve this question









      $endgroup$




      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?







      bootstrap






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked 4 hours ago









      VastingVasting

      305




      305




















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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 $beta>0$.






          share|cite|improve this answer











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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 $beta>0$.






            share|cite|improve this answer











            $endgroup$

















              4












              $begingroup$


              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 $beta>0$.






              share|cite|improve this answer











              $endgroup$















                4












                4








                4





                $begingroup$


                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 $beta>0$.






                share|cite|improve this answer











                $endgroup$




                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 $beta>0$.







                share|cite|improve this answer














                share|cite|improve this answer



                share|cite|improve this answer








                edited 4 hours ago

























                answered 4 hours ago









                TimTim

                59.9k9132225




                59.9k9132225



























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