Rank ANCOVA is a bad idea?












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I am currently working on a project looking at the best way to handle missing data (such as quality of life) due to death. One approach is to use categories/ranks for the outcome, where death is the worst category. One approach that my colleagues wish to consider is rank ANCOVA. However I am pleased to say that they also wish to consider proportional odds models and continuation ratio models.



I found an R help page that says “This [rank ANCOVA] has been shown to yield unreliable analyses. Use the more formal proportional odds ordinal logistic model. This is a generalization of the Wilcoxon-Mann-Whitney-Kruskal-Wallis statistic. This is implemented in the rms package and elsewhere”.



My question is this: Could anyone tell me where this has been shown? In particular the part about rank ancova being unreliable?










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    3












    $begingroup$


    I am currently working on a project looking at the best way to handle missing data (such as quality of life) due to death. One approach is to use categories/ranks for the outcome, where death is the worst category. One approach that my colleagues wish to consider is rank ANCOVA. However I am pleased to say that they also wish to consider proportional odds models and continuation ratio models.



    I found an R help page that says “This [rank ANCOVA] has been shown to yield unreliable analyses. Use the more formal proportional odds ordinal logistic model. This is a generalization of the Wilcoxon-Mann-Whitney-Kruskal-Wallis statistic. This is implemented in the rms package and elsewhere”.



    My question is this: Could anyone tell me where this has been shown? In particular the part about rank ancova being unreliable?










    share|cite|improve this question







    New contributor




    Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







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      3












      3








      3


      1



      $begingroup$


      I am currently working on a project looking at the best way to handle missing data (such as quality of life) due to death. One approach is to use categories/ranks for the outcome, where death is the worst category. One approach that my colleagues wish to consider is rank ANCOVA. However I am pleased to say that they also wish to consider proportional odds models and continuation ratio models.



      I found an R help page that says “This [rank ANCOVA] has been shown to yield unreliable analyses. Use the more formal proportional odds ordinal logistic model. This is a generalization of the Wilcoxon-Mann-Whitney-Kruskal-Wallis statistic. This is implemented in the rms package and elsewhere”.



      My question is this: Could anyone tell me where this has been shown? In particular the part about rank ancova being unreliable?










      share|cite|improve this question







      New contributor




      Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I am currently working on a project looking at the best way to handle missing data (such as quality of life) due to death. One approach is to use categories/ranks for the outcome, where death is the worst category. One approach that my colleagues wish to consider is rank ANCOVA. However I am pleased to say that they also wish to consider proportional odds models and continuation ratio models.



      I found an R help page that says “This [rank ANCOVA] has been shown to yield unreliable analyses. Use the more formal proportional odds ordinal logistic model. This is a generalization of the Wilcoxon-Mann-Whitney-Kruskal-Wallis statistic. This is implemented in the rms package and elsewhere”.



      My question is this: Could anyone tell me where this has been shown? In particular the part about rank ancova being unreliable?







      regression nonparametric






      share|cite|improve this question







      New contributor




      Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|cite|improve this question







      New contributor




      Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









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      share|cite|improve this question






      New contributor




      Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      asked 14 hours ago









      Dan JacksonDan Jackson

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      New contributor




      Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      New contributor





      Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






      Dan Jackson is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






















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          This paper may be a good one demonstrating problems with rank transform anova: https://www.tandfonline.com/doi/abs/10.1080/01621459.1995.10476644
          https://www.jstor.org/stable/2291530?seq=1#metadata_info_tab_contents



          Just transforming data with ranks and using ordinary regression/anova/ancova, in cases other than the k-sample problem, i.e., attempting to use this when adjusting for covariates or assessing interactions, is not fully based on good statistical principles, and results are hard to interpret.






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            $begingroup$

            This paper may be a good one demonstrating problems with rank transform anova: https://www.tandfonline.com/doi/abs/10.1080/01621459.1995.10476644
            https://www.jstor.org/stable/2291530?seq=1#metadata_info_tab_contents



            Just transforming data with ranks and using ordinary regression/anova/ancova, in cases other than the k-sample problem, i.e., attempting to use this when adjusting for covariates or assessing interactions, is not fully based on good statistical principles, and results are hard to interpret.






            share|cite|improve this answer









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              4












              $begingroup$

              This paper may be a good one demonstrating problems with rank transform anova: https://www.tandfonline.com/doi/abs/10.1080/01621459.1995.10476644
              https://www.jstor.org/stable/2291530?seq=1#metadata_info_tab_contents



              Just transforming data with ranks and using ordinary regression/anova/ancova, in cases other than the k-sample problem, i.e., attempting to use this when adjusting for covariates or assessing interactions, is not fully based on good statistical principles, and results are hard to interpret.






              share|cite|improve this answer









              $endgroup$
















                4












                4








                4





                $begingroup$

                This paper may be a good one demonstrating problems with rank transform anova: https://www.tandfonline.com/doi/abs/10.1080/01621459.1995.10476644
                https://www.jstor.org/stable/2291530?seq=1#metadata_info_tab_contents



                Just transforming data with ranks and using ordinary regression/anova/ancova, in cases other than the k-sample problem, i.e., attempting to use this when adjusting for covariates or assessing interactions, is not fully based on good statistical principles, and results are hard to interpret.






                share|cite|improve this answer









                $endgroup$



                This paper may be a good one demonstrating problems with rank transform anova: https://www.tandfonline.com/doi/abs/10.1080/01621459.1995.10476644
                https://www.jstor.org/stable/2291530?seq=1#metadata_info_tab_contents



                Just transforming data with ranks and using ordinary regression/anova/ancova, in cases other than the k-sample problem, i.e., attempting to use this when adjusting for covariates or assessing interactions, is not fully based on good statistical principles, and results are hard to interpret.







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered 13 hours ago









                Frank HarrellFrank Harrell

                55.4k3108244




                55.4k3108244






















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