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mathstatnerd
mathstatnerd
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Say I fit a multivariate model in R lm(Y~X1 + X2 + X3) and get a certain output for an ANOVA table.

Why does the ANOVA table ( using anova() ) for the model lm(Y ~ X1 + X3 + X2) produce a different values for the Sum of Squares in the X3 row than in the (as well as the X2 row)first model?

I know the order matters, but could you explain further on how changing the order changes the Sum of Squares and corresponding p-value for X3?

Say I fit a multivariate model in R lm(Y~X1 + X2 + X3) and get a certain output for an ANOVA table.

Why does the ANOVA table for the model lm(Y ~ X1 + X3 + X2) produce a different values for the Sum of Squares in the X3 row than in the (as well as the X2 row)?

I know the order matters, but could you explain further on how changing the order changes the Sum of Squares and corresponding p-value for X3?

Say I fit a multivariate model in R lm(Y~X1 + X2 + X3) and get a certain output for an ANOVA table.

Why does the ANOVA table ( using anova() ) for the model lm(Y ~ X1 + X3 + X2) produce different values for the Sum of Squares in the X3 row than in the first model?

I know the order matters, but could you explain further on how changing the order changes the Sum of Squares and corresponding p-value for X3?

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mathstatnerd
mathstatnerd
  • 1
  • 1

In an Anova table in Multivariate regression, why does changing the order of the covariates change the (Reg) Sum of Squares and p-value?

Say I fit a multivariate model in R lm(Y~X1 + X2 + X3) and get a certain output for an ANOVA table.

Why does the ANOVA table for the model lm(Y ~ X1 + X3 + X2) produce a different values for the Sum of Squares in the X3 row than in the (as well as the X2 row)?

I know the order matters, but could you explain further on how changing the order changes the Sum of Squares and corresponding p-value for X3?