I have carried out a linear regression. I have plotted the residuals against the predicted values from that model:

As there is a distinct pattern in the residuals, it appears linear regression is not a suitable model. I have carried out several other linear regressions lately with different data, and I have repeatedly seen this pattern in the residuals.

Does this pattern provide information on what model would be best to use? Should an interaction term be added? Is there a predictor missing? Should a non-linear model be used? Or instead, does this particular pattern in the residuals actually not provide any indicators as to what model to use?

I have carried out a linear regression. This is the form of the model:

bounded (0-1) response variable ~ factor1 (2 levels) + factor2 (5 levels) + interaction between factor1:factor2 + factor3 (2 levels)

Sample size is about 350.

I have plotted the residuals against the predicted values from that model:

As there is a distinct pattern in the residuals, it appears linear regression is not a suitable model. I have carried out several other linear regressions lately with different data, and I have repeatedly seen this pattern in the residuals.

Does this pattern provide information on what model would be best to use? Should an interaction term be added? Is there a predictor missing? Should a non-linear model be used? Or instead, does this particular pattern in the residuals actually not provide any indicators as to what model to use?