Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 43 for “"missingness"”.
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Missing Responses in Generalized Linear Mixed Models Where the Missingness is Nonignorable
Missing data are common in many clinical studies. In this thesis, we review methods for analyzing incomplete data using generalized linear mixed models (GLMMs). GLMMs are widely used in clustered and longitudinal data analyses, where random effects are used to model subject or cluster specific …
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Using the Fraction of Missing Information (FMI) in Selecting Auxiliary Variables to Impute Missingness in Confirmatory Factor Analysis (CFA)
… missing data were designed with two levels of missingness (15% and 30%) and two missingness mechanisms to assess their impact on parameter estimate bias, gain in efficiency, and power. In the simulation study, factorial ANOVAs were conducted to assess the design factors and their interactions’ …
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Bayesian approach to inference and variable selection for misclassified and under-reported response models.
Response partial missingness is a problem in studies conducted in a variety of disciplines. We investigate the impact ignoring response partial missingness has on determining a subset of significant covariates in non-linear regression. In particular, we consider non-differential misclassification …
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Missing data and multiple imputation: A sampling study with the SAGA cohort
… of the data and imposing different levels of missingness, i.e. 5%, 10%, 25%, 50% and 75%. The same missingness pattern from the whole data was used to create the missingness on five covariates under the Missing at random (MAR) mechanism. Here the percentage bias and coverage was compared. A …
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To Tolerate or To Impute Missing Values in V2X Communications Data?
… framework has been developed to induce missingness over V2X communication data with different missing ratios, mechanisms, and distributions. This framework provides a comprehensive benchmark resembling missingness over V2X communication data. The proposed methods are compared with some …
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Novel Statistical Methods for Multiple-variant Genetic Association Studies with Related Individuals
… for genome-wide association studies. Genotype missingness commonly arises due to limitations in genotyping technologies. Imputation of the missing values in genotype usually improves quality of the data used in the subsequent association test and thus increases power. Complex correlations, …
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The association of food insecurity and disordered eating behaviors among youth and young adults with diabetes: the SEARCH For Diabetes in Youth Study.
… for Epidemiologic Studies Depression Scale; missingness: 36%), income (missingness: 24%), highest level of parent education (missingness: 3%), and body mass index (missingness: 36%). Results: Participants were on average approximately 22 ± 5 years, 55% female, 69% non-Hispanic White, and had …
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Parameter Estimation for Normally Distributed Grouped Data and Clustering Single-Cell RNA Sequencing Data via the Expectation-Maximization Algorithm
… consisting of evidently incomplete data or missingness situations, such as truncated distributions, censored or grouped observations, and also to problems in which the missingness of the data is not natural or evident, such as mixed-effects models, mixture models, log-linear models, and …
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Operationalizing Reliable Machine Learning: From Data Collection to Model Presentation
… of such systems. For example, nonrandom data missingness, biased algorithmic optimization objectives, or model presentation strategies that incorrectly impact user trust can all cause models to fail in practice. In this thesis, guided by such observations and prior work on pipeline-awareness …
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Dynamic models for time-varying outcomes: An application to the 2015-2017 patient cohort on antiretroviral therapy at Luderitz hospital, Namibia
… outcomes of patients, while accounting for data missingness and measurement error using dynamic models, with application to a cohort of 154 adult patients initiated on ART between January 2015 and December 2017 at the Luderitz hospital. The outcome variable of this study was viral load which was …
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Generative modeling of the tumor microenvironment : deconvolution, completion, and integration
… assumptions such as paired observations, fixed missingness patterns, or predefined feature correspondences. This dissertation develops generative modeling methods for each of these three problems. We introduce BayesTME, a Bayesian framework for deconvolving aggregated spatial transcriptomics …
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Identifying and Understanding Examinee Behaviors in Item Response Data that Compromise Psychometric Quality
… data in terms of subgroups and in terms of missingness levels respectively to evaluate the sensitivity of item response theory (IRT) indicators to response characteristics that can compromise psychometric quality; we also validated a diagnostic classification model (DCM) aiming to diagnose …
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Three essays in the application of obesity economics to intervention evaluation and food access
… loss programs. Most previous studies ignore missingness in the CEA of weight loss programs, but this could result in biased results. Comparing two sample selections reveals that the analysis is sensitive not only to the missingness mechanism, but also which outcome is considered, and the …
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Kidnappings by violent political groups: Explaining between-group and within-group variations
… above, this thesis also examined patterns of missingness in perpetrators’ identity among the GTD kidnappings. This is a necessary step to assess the potential sampling bias caused by the systematic exclusion of GTD kidnappings without information on perpetrators’ identity in the analyses of …
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Using phenotyped but ungenotyped relatives in genetic association tests
… random (MAR), or not missing at\ random (NMAR) missingness mechanism. For quantitative and binary outcomes, we observe biased effect estimates in data sets that exclude subjects with MAR genotypes and in data sets that include imputed NMAR genotypes. For most situations, power increases when …
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Using generative modelling in healthcare
… We shall assess their performance under various missingness scenarios via accordingly designed experiments and simulation studies. We shall proceed via introducing our method on GANs’ inversion and evaluate its performance in a newly suggested manner. Finally, we shall conclude this thesis with …
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Analyzing Incomplete Longitudinal Binary Data Using Approximate Likelihood Methods
Nonignorable missingness in the outcome variable complicates the longitudinal data analysis, as it is necessary to incorporate the missing data model into the observed data likelihood function. We investigate two approximate likelihood methods, bivariate pseudo-likelihood (BPL) of Sinha et al. …
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Evidence of absence : the progressives and strategic non-voting in the house, 1907-1925
… of the 68th. This evidence of non-random missingness can help resolve the puzzle of the Progressives, and inform historical study of Congress.
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