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It seems that on some its subrange your dependent variable is constant or is exactly linearly dependent on predictor(s). Let's have two correlated variables, X and Y (Y is dependent). The scatterplot is on the left.  

Let's return, as example, on the first ("constant") possibility. Recode all Y values from lowest to -0.5 to a single value -1 (see picture in the centre). Regress Y on X and plot residuals scatter, that is, rotate the central picture so that the prediction line is horizontal now. Does it resemble your picture?

It seems that on some its subrange your dependent variable is constant or is exactly linearly dependent on the predictor(s). Let's have two correlated variables, X and Y (Y is dependent). The scatterplot is on the left. 

Let's return, as example, on the first ("constant") possibility. Recode all Y values from lowest to -0.5 to a single value -1 (see picture in the centre). Regress Y on X and plot residuals scatter, that is, rotate the central picture so that the prediction line is horizontal now. Does it resemble your picture?

I seems that on some its subrange your dependent variable is constant or is exactly linearly dependent on predictor(s). Let's have two correlated variables, X and Y (Y is dependent). The scatterplot is on the left.

Then recode all Y values from lowest to -0.5 to a single value -1 (see picture in the centre). Finally, regress Y on X and plot residuals scatter, that is, rotate the central picture so that the prediction line is horizontal. Does it resemble your picture?

It seems that on some its subrange your dependent variable is constant or is exactly linearly dependent on predictor(s). Let's have two correlated variables, X and Y (Y is dependent). The scatterplot is on the left. 

Let's return, as example, on the first ("constant") possibility. Recode all Y values from lowest to -0.5 to a single value -1 (see picture in the centre). Regress Y on X and plot residuals scatter, that is, rotate the central picture so that the prediction line is horizontal now. Does it resemble your picture?

I seems that on some its subrange your dependent variable is constant or is exactly linearly dependent on predictor(s). Let's have two correlated variables, X and Y (Y is dependent). The scatterplot is on the left.

Then recode all Y values from lowest to -1.5 to a single value -1 (see picture in the centre). Finally, regress Y on X and plot residuals scatter, that is, rotate the central picture so that the prediction line is horizontal. Does it resemble your picture?

I seems that on some its subrange your dependent variable is constant or is exactly linearly dependent on predictor(s). Let's have two correlated variables, X and Y (Y is dependent). The scatterplot is on the left.

Then recode all Y values from lowest to -0.5 to a single value -1 (see picture in the centre). Finally, regress Y on X and plot residuals scatter, that is, rotate the central picture so that the prediction line is horizontal. Does it resemble your picture?