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  • Regression calibration and maximum likelihood inference for measurement error models

    Creator:
    Monleon-Moscardo, Vicente J.
    Abstract:
    Regression calibration inference seeks to estimate regression models with measurement error in explanatory variables by replacing the mismeasured variable by its conditional expectation, given a surrogate variable, in an estimation procedure that would have been used if the true variable were available. This study examines the effect of the uncertainty...
    Resource Type:
    Dissertation
    Full Text:
    November 22, 2005. Title: Regression Calibration and Maximum Likelihood Inference for Measurement Error

  • The presence and characterization of measurement error in forestry

    Creator:
    Canavan, Sean Joseph
    Abstract:
    Measurement error (ME) is a component of any study involving the use of actual measurements, but is often not recognized or is ignored. The consequences of MEs on estimates of tree and stand attributes and the parameters and predictions of forest models can be varied and severe, including the presence...
    Resource Type:
    Dissertation

  • Semiparametric maximum likelihood for regression with measurement error

    Creator:
    Suh, Eun-Young
    Abstract:
    Semiparametric maximum likelihood analysis allows inference in errors-invariables models with small loss of efficiency relative to full likelihood analysis but with significantly weakened assumptions. In addition, since no distributional assumptions are made for the nuisance parameters, the analysis more nearly parallels that for usual regression. These highly desirable features and...
    Resource Type:
    Dissertation
    Full Text:
    measurement error AN ABSTRACT OF THE DISSERTATION OF Eun-Young Suh for the degree of Doctor of Philosophy

  • Modeling Density Dependence in the Presence of Measurement Error

    Creator:
    Payton, Quinn
    Abstract:
    Density dependence is an ecological concept concerning the mechanisms of change in the size of a population. The inability to census ecological populations confounds approaches to identify and quantify the level of density dependence. Statistical tests which ignore the presence of measurement error tend to result in misspeci fied type...
    Resource Type:
    Dissertation
    Full Text:
    Dependence in the Presence of Measurement Error Abstract approved: Paul A. Murtaugh Virginia M. Lesser

  • Application and computation of likelihood methods for regression with measurement error

    Creator:
    Higdon, Roger
    Abstract:
    This thesis advocates the use of maximum likelihood analysis for generalized regression models with measurement error in a single explanatory variable. This will be done first by presenting a computational algorithm and the numerical details for carrying out this algorithm on a wide variety of models. The computational methods will...
    Resource Type:
    Dissertation
    Full Text:
    Repression with Measurement Error AN ABSTRACT OF THE THESIS OF Roger Higdon for the degree of Doctor of

  • Statistical aspects of two measurement problems : defining taxonomic richness and testing with unanchored responses

    Creator:
    Ritter, Kerry
    Abstract:
    Statisticians often focus on sampling or experimental design and data analysis while paying less attention to how the response is measured. However, the ideas of statistics may be applied to measurement problems with fruitful results. By examining the errors of measured responses, we may gain insight into the limitations of...
    Resource Type:
    Dissertation
    Full Text:
    several linear models to describe measurement error resulting from unanchored responses across successive

  • Measurement and analysis of soft error vulnerability of low-voltage logic and memory circuits

    Creator:
    Pawlowski, Robert
    Abstract:
    Scaling the supply voltage into the sub/near-threshold domain is one of the most effective methods for improving the energy efficiency of next-generation electronic microsystems. Unfortunately, the relationship between low-voltage operation and radiation-induced soft error rate is not widely known, as little research has been previously performed and reported for soft-error...
    Resource Type:
    Dissertation
    Full Text:
    Measurement and Analysis of Soft Error Vulnerability of Low

  • Analysis of epidemiological data with covariate errors

    Creator:
    Delongchamp, Robert
    Abstract:
    In regression analysis, random errors in an explanatory variable cause the usual estimates of its regression coefficient to be biased. Although this problem has been studied for many years, routine methods have not emerged. This thesis investigates some aspects of this problem in the setting of analysis of epidemiological data....
    Resource Type:
    Dissertation
    Full Text:
    . Measurement Error Models and Estimation Methods 5 2.1 Class of Models 8 2.1.1 Distribution of x 8 2.1.2

  • College student novice spreadsheet reasoning and errors

    Creator:
    Hoag, James A.
    Abstract:
    The spreadsheet has become a common technology tool and is now a predominant form of end-user programming. Some of the same features that make spreadsheets excellent tools for ad-hoc development can introduce errors into the final product. Although a variety of research has been performed investigating methods to detect errors...
    Resource Type:
    Dissertation
    Full Text:
    on the nature of spreadsheet errors, spreadsheet error measurement, spreadsheet conceptual issues

  • The Function-Human Error Design Method (FHEDM)

    Creator:
    Soria Zurita, Nicolás F.
    Abstract:
    This research presents a methodology to identify and analyze human-system interactions, and their potential failure modes using a functional decomposition approach during the early system design stage. The fundamental research contribution of this work is the development of a framework to identify associations between physical user-product interactions, generic human errors...
    Resource Type:
    Dissertation
    Full Text:
    . Title: The Function-Human Error Design Method (FHEDM) Abstract approved: Irem Y. Tumer H. Onan Demirel