Hwan-Jin Yoon

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Results◮ Although model (1) even suggested there was no associationbetween x and y, whereas there was an effect ofbetween-subject.◮ For the case of balanced data, ANOVA(adjusted withcovariate) gives within- and between-subject effects andcombined effect as well.◮ No need two new variables to estimate within- andbetween-subject effects
Results◮ For unbalanced case, model (2) and (3) are the same butmodel (1) and ANOVA give slightly different parameterestimatesParameter Model(1) Model(2) Model(3) ANOVAβ 0 0.610(0.07) 0.647(0.03) 0.647(0.03) 0.645β 1 -0.064(0.08) -0.067(0.08)β W -0.018(0.08) -0.018(0.08) -0.018(0.08)β B -0.429(0.08) -0.423(0.07)β B − β W -0.411(0.11)σγ 2 0.020 0.002 0.002 0.020σε 2 0.007 0.007 0.007 0.007
Page 2: Data StructureSEQ Mutation Current(
Page 6 and 7: Within-Subject Centering◮ The sta
Page 8 and 9: Within-Subject Centering◮ The new
Page 10 and 11: Proposed method◮ Use ANOVA adjust
Page 12 and 13: Results◮ Parameter estimates of m
Page 16: Conclusion◮ For balanced cases, d

Hwan-Jin Yoon

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