Partial Correlations for Removing Interaction Effects from Efficacy Data (64 Patients)



The outcome of cardiovascular research is generally affected by many more factors than a single one, and multiple regression assumes that these factors act independently of one another, but why should they not affect one another. This chapter is to assess whether partial correlation can be used to remove interaction effects from linear data.

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department Medicine Albert Schweitzer HospitalDordrechtThe Netherlands
  2. 2.Academic Medical CenterDepartment Biostatistics and EpidemiologyAmsterdamThe Netherlands

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