I used polynomial distribution lag (PDL) models to analyze the population of insect. In the PDL model, the record with missing data will be ignored so the observation of dependent variable will be a little different. For example: MODEL (1) Y=A + B + C MODEL (2) Y=D + E + F If there is no missing data, I can use AIC, RMSE, or Total R-Square to compare the model performence. However, in the model (1), the A variable has some missing data so the observation number of Y will be fewer than model (2) Under this situation, is RMSE OK to compare the model performence? Thanks in advance...
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