Dears helpers,

I have a question not specially about R, but about statistical modelling. This is the problem, I want to conduct a regression analysis to explain the causes of students fail in an exam. I have two variables the score obtain at the exam and the categorical variable coding 0 in case of fail and 1 in case of success, on a panel data. I am interest to know what made a student who usually succeed start to fail. So I have two possibilty : linear regression analysis with the score or a probit model with the fail indicator. 

In my view, the result will be similary. but is there any difference? what the advantage off choosing one the two approaches ? 

Sincerly

 
Justin BEM
Elève Ingénieur Statisticien Economiste
BP 294 Yaoundé.
Tél (00237)9597295.


      
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