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Table 4 Variance decomposition of Model 1S

From: Variance component analysis to assess protein quantification in biomarker validation: application to selected reaction monitoring-mass spectrometry

Source of variation DF Adjusted sum of squares
Theoretical concentration and interaction J SS(x + xD|D)=RSS(Model 3S) − RSS(Model 1S)
Two-day measurement and interaction 2(J-1) SS(D + xD|x)=RSS(Model 2S) − RSS(Model 1S)
Interaction (J-1) SS(xD|x, D)=RSS(Model 4S) − RSS(Model 1S)
Residual variation IJR-2 J \( RSS\left(\mathrm{Model}\ 1S\right)=\sum \limits_{ijr}{\left({y}_{ijr}-{\widehat{y}}_{ijr}\right)}^2 \)
Measurement error (R-1)*I*J \( \sum \limits_{ij r}{\left({y}_{ij r}-{\overline{y}}_{ij\bullet}\right)}^2 \)
Lack of fit IJ-2 J \( \sum \limits_{ij r}{\left({\widehat{y}}_{ij r}-{\overline{y}}_{ij\bullet}\right)}^2 \)
  1. DF degrees of freedom, I number of samples, J number of couples of days, R number of digestion-injections -\( {\overline{y}}_{ij\bullet } \): mean of digestion-injection replicate measurements of each sample and each couple of days - \( {\widehat{y}}_{ijr} \): predicted measurements - RSS: residual sum of squares - SS: sum of squares