I am running regression analysis on Python and want to figure out which model explains the variance in the dependent variable better, the pooled OLS or fixed effects model (because my independent variable of interest has a low t-stat in pool OLS and a high t-stat in fixed effects). According to tutorials, it can be referred to by the f-stat in the regression summary. However, in my case, fixed effects models return nan for the f statistic and its p-value.
Can someone suggest what could be a reason for not getting a valid value for f stat and how to overcome that issue?