Advertisement

Linear, Logistic, and Cox Regression for Outcome Prediction with Unpaired Data (20, 55, and 60 Patients)

Chapter
  • 973 Downloads

Abstract

To assess whether linear, logistic and Cox modeling can be used to train clinical data samples to make predictions about groups and individual patients.

Supplementary material

333106_2_En_19_MOESM1_ESM.sav (1 kb)
Coxoutcomeprediction (SAV 1 kb)
333106_2_En_19_MOESM2_ESM.zip (1 kb)
exportcox (XML 4 kb)
333106_2_En_19_MOESM3_ESM.zip (1 kb)
exportlin (XML 2 kb)
333106_2_En_19_MOESM4_ESM.zip (1 kb)
exportlog (XML 3 kb)
333106_2_En_19_MOESM5_ESM.sav (1 kb)
linoutcomeprediction (SAV 1 kb)
333106_2_En_19_MOESM6_ESM.sav (1 kb)
logoutcomeprediction (SAV 1 kb)

Copyright information

© 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

Personalised recommendations