http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Nonparametric regression and measurement error
xii, 199 leaves : illustrations ; 28 cm.
two settings. The first involves nonparametric regression
using regression splines in the presence of measurement
error. Two different methods for estimating the regression
spline are used. The first method is the SIMEX algorithm
which artificially adds measurement error in increments of
the known or estimated measurement error, and then
extrapolates to the case of no measurement error. The second
method is a structural approach, whereby one assumes a
distribution for the independent variable which depends on
estimable parameters. The parameters were estimated using
Gibbs sampling. Furthermore, these regression splines were
extended to the class of Generalized Linear Models.
The second setting involves an application in nutritional
epidemiology in which one wants to estimate the long term
dietary intake of a specific nutrient for a population.
There are two primary instruments for measuring this data.
The first instrument is a Food Frequency Questionnaire, which
is assumed to measure the dietary intake both with error and
with bias. The second instrument is a Food Recall which
gives unbiased measurements of the dietary intake, but these
measurements are still measured with error. The goal of
Calibration Analysis is to use both instruments to identify
and possibly correct for the bias of the questionnaire. The
calibration analysis is extended to the case where the
selection probabilities of the individuals in the study are
Issued also on microfiche from University Microfilms Inc.
Includes bibliographical references: pages 71-73.