Reduced major axis regression

• The sum of the products of vertical and horizontal distances of the m1 and m2 is minimised.

• Limitations:

  • As before after log transformation but
  • " Range and domain are the same" restriction is less strict.

Previous slide

Next slide

Back to first slide

View graphic version

Reduced major axis regression

aka ordinary least products regression, geometric mean regression, standardised principal component regression

The sum of the products of vertical and horizontal distances of the m1 and m2 is minimised.

Limitations:
As before after log transformation but

" Range and domain are the same" restriction is less strict.