Page 214 - Quantitative Data Analysis

Quantitative Data Analysis
Simply Explained Using SPSS

Rotation Options

PCA Rotations - Orthogonal Verse Oblique solutions
The number of components extracted in PCA is the number of
observed variables. It produces unique solution. An orthogonal
(uncorrelated) solution is one in which components remain
uncorrelated and when components in PCA are correlated that
solution is called oblique solutions. In certain situations, oblique
solutions provide clearer and easily interpreted results than
orthogonal. The rotations choice is depend upon the research
interest and interpretability. Sometimes orthogonal (uncorrelated)
loadings will be a little hard to interpret, in such case researcher can
use rotation method such that loadings make more sense. Varimax
is the common rotation method that maximizes the sum of squared
loadings for each component. Jensen (1980) said “Rotation is quite
analogous to taking a picture of the same object from a different
angle. For example, we may go up in a helicopter and take an aerial
photograph of the Grand Canyon, and we can also take a shot from
the floor of the canyon, looking through it lengthwise, or from any
other angle. There is no one "really correct" view of the Grand
Canyon. Each shot better highlights some aspects more than others,
and we gain a better impression of the Grand Canyon from several
viewpoints than from any single one. Yet certain views will give a
more informative overall picture than others, depending on the
particular viewer's interest. But no matter what the angle from
which you photograph the Grand Canyon, you cannot make it look
like the rolling hills of Devonshire, or Victoria Falls, or the Himalayas.
Changing the angle of viewing does not create something that's not
already there; it may merely expose it more clearly, although at the
expense of perhaps obscuring some other feature.”
Components/Factors Retaining criteria

The Theory and Applications of Statistical Inferences 198