Random Intercept Models for Both Outcome and Predictor Categories (55 Patients)



Generalized linear mixed models are suitable for analyzing data with multiple categorical variables, both outcome and exposure variables. Do random intercept versions of these models provide better sensitivity of testing than fixed intercept models.

Supplementary material

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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

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