Development of Sample Size Formulas for Least Square Regression-Based Consistency Evaluation of Quantitative Indicators
Objective To develop and verify the sample size formulas for quantitative data consistency e-valuation based on the least square regression method.Methods According to the principle of least square regres-sion-based quantitative consistency evaluation,statistical inference,and formula derivation,we developed the for-mulas for calculating sample size based on regression constant and regression coefficient.Furthermore,the accuracy of the formulas was verified by the data of three examples,and the results were compared with those of the sample size formula established based on the Bland-Altman(BA)method.Results The sample size formulas for regres-sion-based quantitative consistency evaluation were deduced,and the accuracy of the formulas was verified by three examples.In addition,the results obtained with this formula had differences compared with those of the sample size formula established based on the BA method.Furthermore,consistent conclusions could be obtained by regression analysis and BA analysis with the sample size calculated with the regression method.However,with the sample size calculated based on the BA method,the consistency conclusion of regression analysis and BA analysis was some-times not valid.Conclusion A sample size formula for quantitative consistency evaluation based on the regression method was proposed for the first time,which provided methodological support for the research in this field.
least square regressionconsistency evaluationsample sizeformulaquantitative indicator
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