The model for estimating the components of the LF
21 was described by
\[Y_{jkl}{=}{\mu}{+}L_{j}{+}V_{k}{+}LV_{jk}{+}E_{jkl}\]
where
Y is the threshold determination at each
individual location; μ is the overall mean value of sensitivity,
which is related to MD by an aggregate constant;
L j is the effect of the examination
locations;
V k is the effect of each visual
field examination
; LV jk is the
interaction of
L j and
V k ; and
E jkl is the experimental error. The integers
j,
k, and
l represent, respectively, the number of considered stimulus
locations with a double determination of threshold
(
j = 1,2, … … … . .
n), the number of examinations (
k = 2), and
the number of determinations of threshold at each considered location
(
l = 2). The LF(Ho) component can be attributed to
V k , the LF(He) component can be attributed
to the interaction term
LV jk , and the
short-term variance across both examinations can be attributed to the
experimental error (
E jkl ) normally
distributed with an expected value of zero, such that
E jkl is not correlated with any other
error terms and is independent of the independent variables
L j ,
V k , and
LV jk .
The mean square estimates (MSE) for
V k and
LV jk were then reduced to their
constituent variances to remove the accompanying error variance
E jkl by the hypothesis
34 \[MSE(V_{k}){=}jl{\sigma}_{k}^{2}{+}l{\sigma}_{jk}^{2}{+}{\sigma}^{2}\]
\[MSE(LV_{jk}){=}l{\sigma}_{jk}^{2}{+}{\sigma}^{2}\]
\[MSE(E_{jkl}){=}{\sigma}^{2}\]
The LF(He) component (σ
jk ) was calculated
by substituting the mean square error of the error termσ
2 from
equation 3 into
equation 2 . The LF(Ho) component
(σ
k ) was calculated in a similar manner by
substituting
equation 2 into
equation 1 .