[R-sig-ME] FW: Time-Dependent Negative Binomial Regression

[Amirhossei@@Amirhossei@T@iebi m@iii@g oii r@dboudumc@@i]

Dear responders,

I am a medical doctor and currently working on leveraging big data in healthcare as part of my PhD project in Radboudumc.

Recently, I have processed and cleaned a data for the aim of application of a negative binomial regression. First, I tried to use the function [glm.nb] of package “MASS” in R and I had a problem with ensuring that the model will realize the data are for one unique participant (possible correlations in a group of observations). Then, I realized that I can use [glmmPQL] of package “MASS” or [glmer] of package “lme4” and use the family negative binomial in it’s family link. The question is I wanted to check whether I am on a right path using these functions, in addition I would like to know in which part of the model I can embed the offset (logarithm of the number of days of treatment) also how should I insert the time-constant observations for an id (such as gender and baseline age in the attached excel file)?

My latest try is:

[(glmmPQL (event ~ treatment + offset (log(person.time)) , random= list (id=~1, gender=~1, baseline.age=~1), family= negative.binomial (theta=1.75), data=df ))]

Kind regards and thank you for your time and consideration,

Amir

De informatie in dit bericht is uitsluitend bestemd voor de geadresseerde. Aan dit bericht en de bijlagen kunnen geen rechten worden ontleend. Heeft u deze e-mail onbedoeld ontvangen? Dan verzoeken wij u het te vernietigen en de afzender te informeren. Openbaar maken, kopiëren en verspreiden van deze e-mail of informatie uit deze e-mail is alleen toegestaan met voorafgaande schriftelijke toestemming van de afzender. Het Radboudumc staat geregistreerd bij de Kamer van Koophandel in het handelsregister onder nummer 80262783.

The content of this message is intended solely for the addressee. No rights can be derived from this message or its attachments. If you are not the intended recipient, we kindly request you to delete the message and inform the sender. It is strictly prohibited to disclose, copy or distribute this email or the information inside it, without a written consent from the sender. Radboud university medical center is registered with the Dutch Chamber of Commerce trade register with number 80262783.