Thanks for help and time.

Guyom

- Thread starter Gbouvet
- Start date

Thanks for help and time.

Guyom

thanks

well data are collected from same visit (per subject) or, if not, we added the biological values obtained at the closer data from the visit (per subject). here is an example of the data for two patients.

Statut clinique size weight BMI Glycemia Saturation % CRP (mg/L) VEMS % etc...

P002-V01

P002-V02

P002-V03

P002-V04

P002-V05

P002-V06

P003-V01

P003-V02

P003-V03

P003-V04

P003-V05

P003-V06

P003-V07

where V01, V02 are visit number per subject. For each visit and each patient, we have Saturation (O2), FEV1 (%), CRP etc... we have numeric or character, nominal versus continue etc...

Which could be the more interesting test : Time Serie, Multivariate approach, Univariate Split-Plot Approach and Mixed Model Approach ?

thanks

Statut clinique size weight BMI Glycemia Saturation % CRP (mg/L) VEMS % etc...

P002-V01

P002-V02

P002-V03

P002-V04

P002-V05

P002-V06

P003-V01

P003-V02

P003-V03

P003-V04

P003-V05

P003-V06

P003-V07

where V01, V02 are visit number per subject. For each visit and each patient, we have Saturation (O2), FEV1 (%), CRP etc... we have numeric or character, nominal versus continue etc...

Which could be the more interesting test : Time Serie, Multivariate approach, Univariate Split-Plot Approach and Mixed Model Approach ?

thanks

Last edited:

Do you have an a priori plan of which variables should be co-linear or are you going to run models with 10-20 dependent variables? Is there any relationships among 2+ variables. Is multi-collinear a threat? If you just look at X1 vs. X2; X1 vs X3;...;X9 vs. X10, for say 10 variables that is ~ 45 models and your familywise error rate is going to be pretty high. So is this a free for all or is there background knowledge to guide the process.

I am assuming values are correlated with each other (covariance structure, say P0001's first visit value is correlated with second visit data, etc.?

Yes, Values can be correlated to each other i mean intra-patient. As an example, if there is a increase of inflammation due to an infection, pulmonary capacity and BMI can decrease.

Another approach besides multi-level models is generalized linear regression. These are not typically novice analytics, that take a little bit more thought.