Print  Close

A Joint Normal-Ordinal(Probit) Model for Ordinal and Continuous Longitudinal Data

Abstract Number:

1948 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Margaux Delporte (1), Geert Molenberghs (2), Steffen Fieuws (3), Geert Verbeke (4)

Institutions:

(1) KU Leuven, N/A, (2) Universiteit Hasselt & Katholieke Universiteit Leuven, N/A, (3) Biostatistical Centre, N/A, (4) I-Biostat, N/A

Co-Author(s):

Geert Molenberghs  
Universiteit Hasselt & Katholieke Universiteit Leuven
Steffen Fieuws  
Biostatistical Centre
Geert Verbeke  
I-Biostat

First Author:

Margaux Delporte  
KU Leuven

Presenting Author:

Margaux Delporte  
KU Leuven

Abstract Text:

In biomedical studies, continuous and ordinal longitudinal variables are frequently encountered. In many of these studies it is of interest to estimate the effect of one of these longitudinal variables on the other. Time dependent covariates have however several limitations; they can for example not be applied when the data is not collected at fixed intervals. The issues can be circumvented by implementing joint models. In a joint model, both variables are modeled with a random-effects model, and the random effects are allowed to correlate. We propose a normal-ordinal(probit) joint model. First, we derive closed-form formulas to estimate the manifest correlations between the responses as observed. In addition, we derive the marginal model, where the interpretation is no longer conditional on the random effects. As a consequence, we can make predictions for a subvector of one response conditional on the other response and potentially a subvector of the history of the response . Next, we extend the approach to a high-dimensional case with more than two ordinal and/or continuous longitudinal variables. The methodology will be presented by means of a case study.

Keywords:

Longitudinal data analysis|Joint model|Random effects model|Time dependent effects|Probit link|

Sponsors:

Biometrics Section

Tracks:

Longitudinal/Correlated Data

Can this be considered for alternate subtype?

Yes

Are you interested in volunteering to serve as a session chair?

No

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

I understand