In this study, we present a general linear model which blends analysis of variance (ANOVA) and regression when an independent variable has a powerful correlation with the dependent variable and when the independent variables do not interact with other independent variables while predicting the value of the dependent variable. This model is generally applied to balance the effect of comparatively more powerful non interacting variables in order to avoid uncertainty among the independent variables. Data from an observational study with repeated measures (pre-post) were obtained and analysed. The efficiency of the model to determine the differences in means of four treatments before and after adjustment of the field experimental data was discussed. The study was well supported by an empirical example