The Pedagogical Life of Edible Verge Gardens in Sydney: Urban Agriculture for the Urban Food Imaginary.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2018

EFL Teacher Values and Identity in Tertiary Education in Japan

資料・研究ノー

Perils and Prospects of Using Aggregate Area Level Socioeconomic Information as a Proxy for Individual Level Socioeconomic Confounders in Instrumental Variables Regression

A frequent concern in making statistical inference for causal effects of a policy or treatment based on observational studies is that there are unmeasured confounding variables. The instrumental variable method is an approach to estimating a causal relationship in the presence of unmeasured confounding variables. A valid instrumental variable needs to be independent of the unmeasured confounding variables. It is important to control for the confounding variable if it is correlated with the instrument. In health services research, socioeconomic status variables are often considered as confounding variables. In recent studies, distance to a specialty care center has been used as an instrument for the effect of specialty care vs. general care. Because the instrument may be correlated with socioeconomic status variables, it is important that socioeconomic status variables are controlled for in the instrumental variables regression. However, health data sets often lack individual socioeconomic information but contain area average socioeconomic information from the US Census, e.g., average income or education level in a county. We study the effects on the bias of the two stage least squares estimates in instrumental variables regression when using an area-level variable as a controlled confounding variable that may be correlated with the instrument. We propose the aggregated instrumental variables regression using the concept of Wald’s method of grouping, provided the assumption that the grouping is independent of the errors. We present simulation results and an application to a study of perinatal care for premature infants

Strong Control of the Familywise Error Rate in Observational Studies that Discover Effect Modification by Exploratory Methods

An effect modifier is a pretreatment covariate that affects the magnitude of the treatment effect or its stability. When there is effect modification, an overall test that ignores an effect modifier may be more sensitive to unmeasured bias than a test that combines results from subgroups defined by the effect modifier. If there is effect modification, one would like to identify specific subgroups for which there is evidence of effect that is insensitive to small or moderate biases. In this paper, we propose an exploratory method for discovering effect modification, and combine it with a confirmatory method of simultaneous inference that strongly controls the familywise error rate in a sensitivity analysis, despite the fact that the groups being compared are defined empirically. A new form of matching, strength-k matching, permits a search through more than k covariates for effect modifiers, in such a way that no pairs are lost, provided that at most k covariates are selected to group the pairs. In a strength-k match, each set of k covariates is exactly balanced, although a set of more than k covariates may exhibit imbalance. We apply the proposed method to study the effects of the earthquake that struck Chile in 2010

Strong asymmetry in near-fault ground velocity during an oblique strike-slip earthquake revealed by waveform particle motions and dynamic rupture simulations

The 2022 Mw 7.0 Chihshang (Taiwan) earthquake, captured by almost a dozen near-fault strong-motion seismometers, high-rate GPS and satellite data, offers a rare opportunity to examine dynamic fault rupture in detail. Using dynamic rupture simulations, we investigate the particle motions recorded at near-fault strong-motion and 1 Hz GPS stations surrounding the main asperity. Some of these stations were as close as 250 m from the fault trace as determined by sub-pixel correlation of Sentinel-2 images. Our model reproduces the observed strong asymmetry in the ground motions on either side of the fault rupture, which results from along-dip spatial variability in rake angle on the steeply dipping fault (70°) at shallow depth (2 km). Observed near-fault, pulse-like fault-parallel ground velocity larger than fault-normal velocity can be explained by a model with a sub-shear rupture speed, which may be due to shallow rupture propagation within low-velocity material and to free surface reflections. In addition, we estimate a slip-weakening distance Dc of ~0.7-0.9m from strong-motion seismogram recorded at Station F073, which is located ~250 m from the fault rupture, and the results of dynamic rupture modeling. The inferred Dc is similar to other empirically derived estimates found for crustal earthquakes. These results have important implications for near-fault ground-motion hazard

Adapting and responding to a pandemic: Patient and family advisory councils in children\u27s hospitals during COVID-19

This mixed-methods study investigated the effects of the COVID-19 pandemic on Patient and Family Advisory Councils (PFACs) within children’s hospitals in the United States. Specifically, the study sought to understand how PFACs adapted operations as a result of the COVID-19 pandemic, how patient and family advisors (PFAs) were engaged in the response to COVID-19, and the intersection of the COVID-19 pandemic with PFAC diversity, equity, and inclusion. The study consisted of a survey distributed to 228 children’s hospitals, with a 73% response rate, and in-depth interviews with selected survey respondents (n=12). While COVID-19 temporarily disrupted PFAC operations and forced rapid adaptations, most children’s hospital PFACs transitioned successfully to virtual meetings, with 86% reporting that their PFAC met at least once from March to December 2020 and 84% indicating that their PFAC planned to meet as frequently or more frequently than before the pandemic. The majority of respondents (72%) reported that attendance at virtual PFAC meetings was the same as or better than with in-person meetings. Interview participants reported benefits associated with virtual meetings, including the potential ability to recruit and engage PFAs who better reflected the diversity of the patients and families served by the hospitals. Children’s hospitals are well-positioned to be leaders in the field, contributing to the development of new approaches, lessons learned, and best practices moving forward. This is especially true as hospitals continue to navigate the evolving realities of the COVID-19 pandemic, and as PFACs address challenges associated with maintaining diverse, equitable, and inclusive councils. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens

Surrogate Markers for Time-Varying Treatments and Outcomes

BACKGROUND: A surrogate marker is a variable commonly used in clinical trials to guide treatment decisions when the outcome of ultimate interest is not available. A good surrogate marker is one where the treatment effect on the surrogate is a strong predictor of the effect of treatment on the outcome. We review the situation when there is one treatment delivered at baseline, one surrogate measured at one later time point, and one ultimate outcome of interest and discuss new issues arising when variables are time-varying. METHODS: Most of the literature on surrogate markers has only considered simple settings with one treatment, one surrogate, and one outcome of interest at a fixed time point. However, more complicated time-varying settings are common in practice. In this article, we describe the unique challenges in two settings, time-varying treatments and time-varying surrogates, while relating the ideas back to the causal-effects and causal-association paradigms. CONCLUSION: In addition to discussing and extending popular notions of surrogacy to time-varying settings, we give examples illustrating that one can be misled by not taking into account time-varying information about the surrogate or treatment. We hope this article has provided some motivation for future work on estimation and inference in such settings