Linear regressions that use the OLS method assume that X is a fixed variable, but it is usually random. That means that you are supposed to have decided on which values of x are going to be used before you went out and collected the data.
This isn’t a problem is you are doing the regression to predict values of Y from X. But, if you want to know about the true slope (the beta estimate) of Y and X then this becomes a problem and OLS regression probably shouldn’t be used. However, it may not be too big of an issue if all you are interested in is whether the slope is 0 or not (just be aware that because there is now error associated with both Y and X, rather than just Y, the OLS slope will be biased towards zero). If you want to compare slope estimates with other values then you should definitely use a model type 2 regression (just means that both X and Y are random) technique.
Some methods include major axis (MA) regression, ranged MA regression, reduced major axis (RMA)/standard major axis (SMA), slope range method.
I used the textbook Quinn and Keough (2002) Experimental design and data analysis for biologists. Cambridge University Press.
This isn’t a problem is you are doing the regression to predict values of Y from X. But, if you want to know about the true slope (the beta estimate) of Y and X then this becomes a problem and OLS regression probably shouldn’t be used. However, it may not be too big of an issue if all you are interested in is whether the slope is 0 or not (just be aware that because there is now error associated with both Y and X, rather than just Y, the OLS slope will be biased towards zero). If you want to compare slope estimates with other values then you should definitely use a model type 2 regression (just means that both X and Y are random) technique.
Some methods include major axis (MA) regression, ranged MA regression, reduced major axis (RMA)/standard major axis (SMA), slope range method.
I used the textbook Quinn and Keough (2002) Experimental design and data analysis for biologists. Cambridge University Press.