Original Article

Comparison of the accuracy of multiple regression analysis using four methods to predict the functional independence measure at discharge

Makoto Tokunaga, MD, PhD, Hiroaki Yamanaga, MD, PhD
Jpn J Compr Rehabil Sci 11: 65-72, 2020

Objective: This study aims to compare the accuracy of four methods of multiple regression analysis in predicting the motor functional independence measure (mFIM) at discharge.
Methods: The subjects of this study were 1,064 stroke patients who had been hospitalized in a convalescent rehabilitation hospital. Standard multiple regression analysis (S prediction) with mFIM at discharge as the objective variable, multiple regression analysis with reciprocal number of mFIM at admission as one of the explanatory variables (R prediction), prediction of the effectiveness of mFIM by multiple regression analysis, the conversion to mFIM at discharge (E prediction), and the creation of two multiple regression prediction formulas (S2 prediction) were performed. The absolute values of residuals (actual value minus predicted value) of mFIM at discharge were compared for the four methods.
Results: The absolute value of the residuals was significantly smaller in the R prediction, E prediction, and S2 prediction than that in the S prediction. In addition, the absolute value was found to be significantly smaller in the E prediction and S2 prediction than that in the R prediction.
Conclusion: In multiple regression analysis, the use of E prediction or S2 prediction is recommended because of their high prediction accuracies.

Key words: multiple regression analysis, prediction accuracy, reciprocal number, FIM effectiveness, multiple prediction formulas

Contents (volume 11)