Regression modeling

#1
Hello everyone, I am a student in agricultural genetic engineering, and I am working on presenting a research paper about the genetic relationship between efficiency of feed intake and diseases.
This paper presents a lot of statistical information which is quite hard for me to process quickly, so I would like to post a quote from the paper regarding regression analysis, if anyone can explain it to me, it will be of great help, the quote is: "The BCS (Body Condition Score) on a scale of 1 (emaciated) to 5 (obese) was assessed monthly by different scorers. Before calculating phenotypes for weekly REI (Residual Energy Intake), we predicted weekly cow individual BCS values. Therefore, we used random regression modeling, which is a useful prediction technique to fill up weeks without actual observations to increase the number of observations"
I would like to understand what is meant by "to fill up weeks without actual observations to increase the number of observations"
I look forward for your replies.
 

Karabiner

TS Contributor
#2
Could you post the reference, or even a link to that paper?
It looks like it refers to some missing data imputation technique,
but maybe they just mean "we used a multilevel random effects
model where observations are 'nested' within cows and does
not require that a cow has no missing observations".

With kind regards

Karabiner
 
#3

Karabiner

TS Contributor
#4
I have no access to this, I'm afraid. Maybe they added some more information on multilevel "random effects model" in their paper?
 
#5
I have no access to this, I'm afraid. Maybe they added some more information on multilevel "random effects model" in their paper?
Actually this study is full of statistical analysis, they used many models, I don’t know if I can share the paper with you here due to copyright (I can share if it’s not illegal), yes I think there is many informations and usage of multi level models. I just wanted to understand how they are being used for the purpose of the study