rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Nonparametric regression and measurement error
  name:
    name part: Maca, Jeffrey Dean
    name part: 1971-
    role:
      role term: creator
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: xx
    date issued: 1997
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xii, 199 leaves : illustrations ; 28 cm.
  abstract: two settings. The first involves nonparametric regression
  abstract: using regression splines in the presence of measurement
  abstract: error. Two different methods for estimating the regression
  abstract: spline are used. The first method is the SIMEX algorithm
  abstract: which artificially adds measurement error in increments of
  abstract: the known or estimated measurement error, and then
  abstract: extrapolates to the case of no measurement error. The second
  abstract: method is a structural approach, whereby one assumes a
  abstract: distribution for the independent variable which depends on
  abstract: estimable parameters. The parameters were estimated using
  abstract: Gibbs sampling. Furthermore, these regression splines were
  abstract: extended to the class of Generalized Linear Models.
  abstract: The second setting involves an application in nutritional
  abstract: epidemiology in which one wants to estimate the long term
  abstract: dietary intake of a specific nutrient for a population.
  abstract: There are two primary instruments for measuring this data.
  abstract: The first instrument is a Food Frequency Questionnaire, which
  abstract: is assumed to measure the dietary intake both with error and
  abstract: with bias. The second instrument is a Food Recall which
  abstract: gives unbiased measurements of the dietary intake, but these
  abstract: measurements are still measured with error. The goal of
  abstract: Calibration Analysis is to use both instruments to identify
  abstract: and possibly correct for the bias of the questionnaire. The
  abstract: calibration analysis is extended to the case where the
  abstract: selection probabilities of the individuals in the study are
  abstract: not all equal.
  note: by Jeffrey Dean Maca.
  note: Vita.
  note: "Major Subject: Statistics".
  note: Issued also on microfiche from University Microfilms Inc.
  note: Includes bibliographical references: pages 71-73.
  note: Ph. D. Texas A&M University 1997.
  subject:
    topic: Major statistics
  identifier: 98-00774 UMI
  identifier: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  record info:
    record content source: TXA
    record creation date: 980406
    record change date: 20190325093500.0
    record identifier: in00001415015