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.
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Showing 1 to 20 of 22 for “"Inverse probability weighting"”.
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Improving applicability of the non-monotone unified estimate for missing data
… power and can cause non-response bias. Inverse probability weighting is one method used to avoid non-response bias. However, when some individuals have partially observed data inverse probability weighting has only a limited ability to use this data. The unified approach (Zhao and Liu, …
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Methods for handling missing data in cohort studies where outcomes are truncated by death
… methods used to handle missing outcomes - inverse probability weighting, multiple imputation and linear increments - is made, focusing particularly on the setting where outcomes are missing due to both dropout and death. We show that when the dropout models are correctly specified for …
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Statistical methods for ChIP-seq and microbiome studies using next-generation DNA sequencing data
… interactions.</p> <p>In Chapter 4, we present an inverse probability weighting approach to causal analysis of the effects of individual microbiome features in presence of continuous confounding variables. In simulated microbiome data, we show inverse probability weighting in marginal models …
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Economic implications of disability prevention : A benefit-cost analysis of targeted occupational health interventions
… propensiteettipisteytys (Propensity Score), ja Inverse Probability Weighting -painotusmenetelmä. Tutkimuksen tulokset osoittavat, että kohdistettujen työterveysinterventioiden yhteiskunnallinen vaikutus on todennäköisesti positiivinen: keskimääräinen hoitovaikutus nettohyötyihin korkean riskin …
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Tecnología y Rendimiento Escolar: ¿Cómo afecta el acceso a computadoras en el hogar?
… selección muestral. Siguiendo la tradición del inverse probability weighting method (IPW) propuesto por (Horvitz & Thompson, 1952) ponderamos por la probabilidad de tener completo el puntaje del examen condicional a los controles (X) bajo el supuesto del cumplimiento del supuesto de MAR. Los …
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Semiparametric Regression Under Left-Truncated and Interval-Censored Competing Risks Data and Missing Cause of Failure
… risks data. Second, we adopt the augmented inverse probability weighting method to deal with both interval censoring and missing event types. We show that the resulting estimates are consistent and double robust. We illustrate this method using data from the East-African International …
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Sufficient Dimension Reduction with Missing Data
… the dissertation focuses on the seminal sliced inverse regression (SIR) approach proposed by Li (1991). We show that missing responses generally affect the validity of the inverse regressions under the mechanism of missing at random. We then propose a simple and effective adjustment with inverse …
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Towards the modulation of the microbiome to control Campylobacter in broiler chickens
… coprophagic behavior. Chapter VI made use of inverse probability weighting modelling to tackle the time-varying confounding in interconnected processes. Methods for bacterial differential abundance that take into account the specific characteristics of microbiome data showed a better …
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Causal Inference and Evidence-Grounded Language Models for Trustworthy Personalized Clinical Decision Support
… that leverages shared representations and inverse probability weighting to model counterfactual outcomes across treatment options. We further develop FUSION, a unified framework combining latent phenotyping, calibrated risk prediction, and causal inference to forecast intraoperative events …
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Towards More Accurate Causal Inference with Instrumental Variables and Mendelian Randomisation Analyses
… and then provide asymptotic guarantees for using inverse probability weighting (IPW) to eliminate selection bias. We argue that in finite samples, IPW may fail to account for selection bias under severe selection even when the selection model is fully known. We demonstrate our findings through …
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Statistical Methods For Two Problems In Cancer Research: Analysis of Rna-Seq Data From Archival Samples and Characterization of Onset of Multiple Primary Cancers
… disease studies, was also properly adjusted by inverse probability weighting scheme. We applied the proposed method to the LFS data, a family cohort collected through pediatric sarcoma patients at MD Anderson Cancer Center from 1944 to 1982. Both internal and external validation studies show …
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Weighting and moment conditions in Bayesian inference
… data. To be more specific, we are referring to probability weights, which are used to adjust for distributional differences between the sample and the population. Sometimes, these differences occur by design; data collectors can choose to implement an unequal probability sampling frame to …
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Fine Particulate Matter, Neuropathologies, & Dementia
… selection into the autopsy cohort through inverse-probability weighting, we estimated that each 1 ug/m3 increase in 10-year average PM2.5 prior to death was associated with a suggestive increase in the odds of higher CERAD score (OR: 1.35 (0.90, 1.90)). There was no association with Braak …
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Obesity and Aggressive Prostate Cancer: Bias and Biology
… the use of marginal structural models (MSM) and inverse probability weighting (IPW) may be able to address such biases. Using data collected on a series of patients referred for prostate biopsy, and found to have PC, we examined the association between BMI, clinical and pathological …
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Care Needs, Social Wellbeing, and Health and Social Services Use in Older Age
… methods including multiple imputation and inverse probability weighting. Results. The review of the literature showed that lower social support, having no spouse, or living alone were associated with higher risk of re-hospitalisation and emergency department visit, with some variation in …
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Beyond Parameter Estimation: Analysis of the Case-Cohort Design in Cox Models
… of coefficients in this design requires weighting of observations. This results in a pseudopartial likelihood, and standard post-estimation methods may not be readily transferable to the case-cohort design. This thesis presents theory and simulation studies for application of estimation …
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Analysis of households? modern energy deprivations beyond connections and access in the Northwest zone of Nigeria
… Applying the generalized propensity score and inverse probability weighting of treatment methods of matching and estimation, the study found that on the basis of connections, access to electricity has limited positive causal effect on the profits of household's non-farm enterprises. However, …
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A new jointly estimated model of young adults’ decisions to leave their parental homes and to choose new residential locations
… which we address through panel gap filling and inverse probability weighting. We then develop separately single-tier models for decisions to remain/leave home and for choices of new residential locations in line with the existing literature. Subsequently, we build a joint model for those choices …
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Workplace injuries, early opioid prescribing, and disability in Washington State
… high-risk indicators shortly after injury. Using inverse probability weighting, we accounted for non-response bias and assigned opioid treatment weights while controlling for injury severity, injury characteristics, comorbidities and sociodemographic characteristics. Cox proportional hazards …
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Essays in Causal and Comparative Econometrics
… analysis. In the first chapter titled 'Stable Probability Weighting for Large-Sample Causal Analysis,' I propose new methods for causal analysis involving "Basu's elephants" (data with extreme selection on observables), which plague many empirical studies in both social and health sciences. I …
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