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Full-Text Articles in Physical Sciences and Mathematics

Multi-Arm Randomized Control Trials In Inflammatory Bowel Disease: A Literature Review And An Illustration Of Methods For Analysis, Sahiba Saini Nov 2023

Multi-Arm Randomized Control Trials In Inflammatory Bowel Disease: A Literature Review And An Illustration Of Methods For Analysis, Sahiba Saini

Electronic Thesis and Dissertation Repository

This thesis aimed to review the literature on multiple-arm randomized control trials in inflammatory bowel disease (IBD) and to illustrate how to analyze these trials, focusing on appropriately controlling the type 1 error rates. The literature review found 247 trials published from the inception of each database to April 2014, of which 122 (49%) trials were multiple-arm trials and of those, 59 (48%) trials were on ulcerative colitis and 63 (52%) on Crohn’s disease. A published assessment tool was adopted to assess whether controlling of Type I error rates was needed. Despite the common use of this trial design and …


Parameter Estimation For Normally Distributed Grouped Data And Clustering Single-Cell Rna Sequencing Data Via The Expectation-Maximization Algorithm, Zahra Aghahosseinalishirazi Sep 2023

Parameter Estimation For Normally Distributed Grouped Data And Clustering Single-Cell Rna Sequencing Data Via The Expectation-Maximization Algorithm, Zahra Aghahosseinalishirazi

Electronic Thesis and Dissertation Repository

The Expectation-Maximization (EM) algorithm is an iterative algorithm for finding the maximum likelihood estimates in problems involving missing data or latent variables. The EM algorithm can be applied to problems 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 latent variables. In Chapter 2 of this thesis, we apply the EM algorithm to grouped data, a problem in which incomplete data are evident. Nowadays, data confidentiality is of …


Nonparametric Methods For Analysis And Sizing Of Cluster Randomization Trials With Baseline Measurements, Chengchun Yu Sep 2023

Nonparametric Methods For Analysis And Sizing Of Cluster Randomization Trials With Baseline Measurements, Chengchun Yu

Electronic Thesis and Dissertation Repository

Cluster randomization trials are popular in situations where the intervention needs to be implemented at the cluster level, or logistical, financial and/or ethical reason dictates the choice for randomization at the cluster level, or minimization of contamination is needed. It is very common for cluster trials to take measurements before randomization and again at follow-up, resulting in a clustered pretest-posttest design. For continuous outcomes, the cluster-adjusted analysis of covariance approach can be used to adjust for accidental bias and improve efficiency. However, a direct application of this method is nonsensical if the measures are incompatible with an interval scale, yet …


Modelling Long-Term Security Returns, Xinghan Zhu Aug 2023

Modelling Long-Term Security Returns, Xinghan Zhu

Electronic Thesis and Dissertation Repository

This research focuses on the concerns of Canadian investors regarding portfolio diversification and preparedness for unexpected risks in retirement planning. It models market crashes and two main financial instruments as independent components to simulate clients’ portfolios. Initially exploring single distributions on mutual funds such as Laplace and t distributions, the research finds limited success. Instead, a normal-Weibull spliced distribution is introduced to model log returns. The Geometric Brownian Motion (GBM) model is employed to predict and evaluate returns on common stocks using the Maximum Likelihood Estimator (MLE), assuming that daily log returns follow a normal distribution. Additionally, the Merton Jump …


Addressing The Impact Of Time-Dependent Social Groupings On Animal Survival And Recapture Rates In Mark-Recapture Studies, Alexandru M. Draghici Jun 2023

Addressing The Impact Of Time-Dependent Social Groupings On Animal Survival And Recapture Rates In Mark-Recapture Studies, Alexandru M. Draghici

Electronic Thesis and Dissertation Repository

Mark-recapture (MR) models typically assume that individuals under study have independent survival and recapture outcomes. One such model of interest is known as the Cormack-Jolly-Seber (CJS) model. In this dissertation, we conduct three major research projects focused on studying the impact of violating the independence assumption in MR models along with presenting extensions which relax the independence assumption. In the first project, we conduct a simulation study to address the impact of failing to account for pair-bonded animals having correlated recapture and survival fates on the CJS model. We examined the impact of correlation on the likelihood ratio test (LRT), …


Multiple Endpoints In Randomized Controlled Trials: A Review And An Illustration Of The Global Test, Lindsay Cameron Apr 2023

Multiple Endpoints In Randomized Controlled Trials: A Review And An Illustration Of The Global Test, Lindsay Cameron

Electronic Thesis and Dissertation Repository

A randomized controlled trial is often used to provide high quality evidence regarding treatment interventions. Due to the complex nature of many diseases, trials usually select multiple primary outcomes to capture the efficacy of the interventions. In this thesis, we conducted a literature search to determine the prevalence of the different types of multiple outcomes that have been used in randomized controlled trials. We also reviewed the corresponding statistical methods used to deal with such outcomes. In addition, we described the benefits of using global tests as a statistical method when there are multiple primary outcomes in order to answer …


Nearby Galaxies: Modelling Star Formation Histories And Contamination By Unresolved Background Galaxies, Hadi Papei Jan 2023

Nearby Galaxies: Modelling Star Formation Histories And Contamination By Unresolved Background Galaxies, Hadi Papei

Electronic Thesis and Dissertation Repository

Galaxies are complex systems of stars, gas, dust, and dark matter which evolve over billions of years, and one of the main goals of astrophysics is to understand how these complex systems form and change. Measuring the star formation history of nearby galaxies, in which thousands of stars can be resolved individually, has provided us with a clear picture of their evolutionary history and the evolution of galaxies in general.

In this work, we have developed the first public Python package, SFHPy, to measure star formation histories of nearby galaxies using their colour-magnitude diagrams. In this algorithm, an observed colour-magnitude …