Simulation studies to assess the power of set testing methods for microbiome data

With advances in sequencing methods, the study of the microbiome has greatly increased. Microbiome data, in the form of an OTU or ASV count table, can be used to identify specific ASVs that function differently across treatment conditions. Such analysis is deemed differential abundance analysis. ASVs are grouped by their taxonomic rank, and ASVs sharing the same rank have similar biological traits. By studying groups or sets of ASVs, and identifying if the set is differentially abundant, the biological interpretation of a microbiome study is enhanced. We review current approaches in set testing methods and apply them to a microbiome data set from a 2017 study. We propose a new set testing method based on an existing Poisson hurdle model, and compare performance across all methods through a model based simulation study. We find that under certain conditions, our proposed model outperforms existing approaches. We discuss the limitations of our model and conclude that more simulation studies, specifically non-parametric simulation studies, are needed to better compare across possible methods

Promoting motor skills in low-income, ethnic children: The Physical Activity in Linguistically Diverse Communities (PALDC) nonrandomized trial

This study reports the long-term effects of a professional learning program for classroom teachers on fundamental motor skill (FMS) proficiency of primary school students from ethnically diverse backgrounds. Design: A cluster non-randomized trial using a nested cross-sectional design. Methods: The study was conducted in 8 primary schools located in disadvantaged and culturally diverse areas in Sydney, Australia. The intervention used an action learning framework, with each school developing and implementing an action plan for enhancing the teaching of FMS in their school. School teams comprised 4-5 teachers and were supported by a member of the research team. The primary outcome was total proficiency score for 7 FMS (run, jump, catch, throw, kick, leap, side gallop). Outcome data were analyzed using mixed effects models. Results: Eight-hundred and sixty-two students (82% response rate) were assessed at baseline in 2006 and 830 (82%) at follow-up in 2010. Compared with students in the control schools, there was a significantly greater increase in total motor skill proficiency among children in the intervention schools at follow-up (adjusted difference = 5.2 components, 95%CI [1.65, 8.75]; p. = 0.01) and in four of the seven motor skills. Conclusions: Training classroom teachers to develop and implement units of work based around individual FMS is a promising strategy for increasing FMS among ethnically diverse children over an extended period of time

Dark sectors 2016 Workshop: community report

This report, based on the Dark Sectors workshop at SLAC in April 2016, summarizes the scientific importance of searches for dark sector dark matter and forces at masses beneath the weak-scale, the status of this broad international field, the important milestones motivating future exploration, and promising experimental opportunities to reach these milestones over the next 5-10 years

Simulation studies to assess the power of set testing methods for microbiome data

With advances in sequencing methods, the study of the microbiome has greatly increased. Microbiome data, in the form of an OTU or ASV count table, can be used to identify specific ASVs that function differently across treatment conditions. Such analysis is deemed differential abundance analysis. ASVs are grouped by their taxonomic rank, and ASVs sharing the same rank have similar biological traits. By studying groups or sets of ASVs, and identifying if the set is differentially abundant, the biological interpretation of a microbiome study is enhanced. We review current approaches in set testing methods and apply them to a microbiome data set from a 2017 study. We propose a new set testing method based on an existing Poisson hurdle model, and compare performance across all methods through a model based simulation study. We find that under certain conditions, our proposed model outperforms existing approaches. We discuss the limitations of our model and conclude that more simulation studies, specifically non-parametric simulation studies, are needed to better compare across possible methods.</p

Statistical methodologies for designing new trials with network meta-analysis

Network meta-analysis (NMA) is a statistical methodology that is used to combine results from clinical trials. NMA enables estimation of comparative effects of treatments that are observed directly or indirectly, which allows researchers to better understand an existing evidence base and can aid in the design of future trials. While there is thorough literature on both implementing NMA and borrowing information from an existing NMA to plan new trials, methodology for specific applications that occur often in practice are lacking. The research throughout this dissertation focuses on how to design new trials using NMA under several of these scenarios. In Chapter 2, we consider how to design a new single two-arm trial when an existing network is disconnected in nature. In Chapter 3, we propose a method that allows researchers to design a new two-arm trial when said trial is motivated by the results of an existing NMA. In Chapter 4, we propose a method that allows researchers to leverage an existing network of trials to plan a new, three-arm multi-centered trial. We provide applications of all methods using a network of real trials, and evaluate the performance of our methods through extensive simulation studies. The methods developed here can increase the power of a newly planned trial, which not only decreases costs for researchers, but helps to maximize the value of an existing evidence base

Moving Mountains: Surviving the Migration to LibGuides 2.0

In the summer of 2014, Northwestern University Library began the process to migrate their library guides to LibGuides 2.0. With over 500 published guides and 88 active guide authors, upgrading to the new system required careful planning and collaboration with partners from across the library. In this presentation, we will discuss the steps we took to manage the migration process and the methods we used (and are still using) to learn about best practices working with LibGuides 2.0. Our process includes usability testing, system analytics, guide management, asset maintenance, and staff training and support throughout the migration. We will share lessons we’ve learned and our plans for future user testing and guide management