Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This study implements a recently proposed score test that could help guide insurance fraud researchers in deciding whether to use a logit or a probit model in predicting insurance fraud probabilities, especially when the occurrence of ones in the dependent variable is much less than zeros. The test is easily implemented in a crop insurance fraud context and seems to be a promising method that could be applicable to analysing and detecting potentially fraudulent claims in various lines of insurance.