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LOG-COX Online

Course dedicated to Logistic Regression and Cox Regression

To request registration or for information

Goals:

To enable participants to construct and interpret logistic regression and proportional hazards regression models of the Cox model.

Techniques presented:

Logistic regression and Cox proportional hazards regression model.

 

Cost:

The cost of the entire LOG-COX Online course (3 sessions, for a total of 9 hours) is 450 Euros (excluding VAT) per participant.

Tutorials:

There are exercises for each of the topics covered.

 

Prerequisites:

Attendance to the course is preparatorySURV Online(or calendar) or have knowledge of the topics covered in it.

 

Duration:

Online course lasting 9 hours, divided into 3 sessions of 3 hours each

Frequency:

Our online courses are delivered in live mode in order to guarantee the maximuminteractionand collaboration betweenprofessorAndparticipants. For this reason, the presence of the participants in all lessons is considered essential.

In case of absence from a lesson, the Training Staff will send the learner the points and exercises covered during the skipped lesson.

If you miss more than one lesson, the Training Staff reserves the right not to send the student the certificate of participation.

Certificate of attendance:

At the end of the course the certificate of participation will be issued.

Topics that will be addressed for each session:

First session (3 hours)

Logistic Regression

  • Introduction

  • Scatterplot

  • Binary logistic regression

  • Interpretation of a logistic model

  • Examples and exercises

Second session (3 hours)

The Cox proportional hazards regression model

  • Multivariate survival analysis

  • Cox model

  • Cox proportional hazards model

  • Risk measures

  • Examples and exercises

Third session (3 hours)

The Cox proportional hazards regression model

  • Methods for verifying Proportional Hazard

  • Selection of variables

  • Model with dependent time variable

  • Problems of multivariate analysis

  • Summary exercises

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