I'm studying a model which has large datasets of empirical data and analysis available. In the particular dataset that I consideted (with a few a priori expectations) I tried out a simple linear regression on the multivariable model. I found that the R2 was very low and the t values were mostly insignificant. There was no major Multicollinearity in the model as well. Empirically, the a priori expectations I had were quite strong, that is, the regression should have resulted in a stronger fit and significant explanatory variables, yet the results state otherwise. What could be the possible reasons for low t values depsite strong empirically proved relationship between the regressors and regressand? Does it have anything to do with the sample size? I have a sample of 400, which seems quite enough for a simple regression analysis.