I am comparing two models. One is nested in the other. The nested one is the null model and the other one is the alternate model. The log likelihood score of the null is lnL0 and for alternate is lnL1. The difference in the number of parameters in these models is the degree of freedom, df.

I am looking for the P value by looking up in the chi square table with the df and 2*(lnL1 - lnL0),

my doubt is, should I take absolute difference between lnL1 and lnL0 or i should subtract lnL0 from lnL1.

if I subtract lnL0 from lnL1, in few cases I m getting negative number, how should I deal with such cases where 2*(lnL1 - lnL0) < 0 ?

As the null model is nested inside the alternate one, log likelihood score of the alternate should always be bigger than null. So, how come I am getting -ve value in some of my cases, Does it mean that I am doing something wrong?

By the way I am not calculating the log likelihood scores my myself. I am using the positive selection package PAML, which calculates the log likelihood score of the respective models.

It would really be a great help if somebody can clarify my doubts.

Thanking you.