In a composite sampling procedure initial samples
(increments) are drawn from a lot and physically mixed to
form composite samples. Subsamples are then taken from
these composite samples and tested to determine the lot
quality, usually the lot mean, ux.
Composite sampling procedures typically are employed
with bulk materials, for which high testing costs preclude
estimation of μχ using the arithmetic average of values
from several individually tested increments. Because of
the physical averaging that occurs when increments are
mixed to form composite samples, it is possible to estimate
μχ with specified precision with greater economy
using a composite sampling procedure than using a noncompositing
procedure.
This dissertation extends and interprets the work
of Brown and Fisher on modeling procedures that involve subsampling mixtures of sampled material. Models are
developed for sampling from segmented or nonsegmented
lots, allowing for more than one finite composite, testing
error, within—increment variability, or two subsampling
stages. The result of each model is a formula expressing
the variance of the estimator of ux in terms of model
parameters. Each such formula is contrasted with the
corresponding formula derived from the customarily employed
random effects linear model.
next to an author's name indicates that all files or directories associated with their ETD are accessible from the Virginia Tech campus network only.
![[VT]](http://scholar.lib.vt.edu/images/ETD-db/restricted.gif)
