While the standard addition method is effective in reducing the interference of most matrix effects on the analyte signal, it cannot correct for the translational matrix effects. These effects are caused by other substances present in the unknown sample that are often independent of the analyte concentration. They are commonly referred to as background and can impact the intercept of the regression line without affecting the slope. This results in bias towards the unknown concentration. In other words, standard addition will not correct for these backgrounds or other spectral interferences.
Analysts also needs to evaluate the precision of the determined unknown concentration by calculating for the standard deviation, . Lower  indicates greater precision of the measurements. The value of  is given by 
where the calculation involves the following variables:
* standard deviation of the residuals,  
* absolute value of the slope of the least-squares line, 
* y-intercept of the linear curve, 
* number of standards, 
* average measurement of the standards, 
* concentrations of the standards, 
* average concentration of the standards,