Grouped GEE Analysis for Longitudinal Data

Generalized estimating equation (GEE) is widely adopted for regression modeling for longitudinal data, taking account of potential correlations within the same subjects. Although the standard GEE assumes common regression coefficients among all the subjects, such assumption is not realistic when there are potential heterogeneity in regression coefficients among subjects. In this paper, we develop a flexible and interpretable approach, called grouped GEE analysis, to modeling longitudinal data with allowing heterogeneity in regression coefficients. The proposed method assumes that the subjects are divided into a finite number of groups and subjects within the same group share the same regression coefficient. We provide a simple algorithm for grouping subjects and estimating the regression coefficients simultaneously, and show asymptotic properties of the proposed estimator. The number of groups can be determined by the cross validation with averaging method. We demonstrate the proposed method through simulation studies and an application to a real dataset.Comment: 64 page

Potential Biases of the Transmission Risks of COVID-19 estimated by Contact Tracing Surveys in Japan

Introduction: Contact tracing surveys are being conducted to identify and isolate close contacts of an identified patient to reduce the spread of coronavirus disease (COVID-19). However, the estimates of risk indexes based on information obtained from the surveys and normally used in practice can have biases comparing with true magnitude of risks of infection and spread.Method: We evaluated whether the estimates of the risk indexes obtained from information of the active epidemiological surveillance, contact tracing surveys in Japan, are suitable for quantitative assessment of the risk factors of COVID-19, using pseudo data via a simulation study. We discussed two types of risks considered in the issue of infectious disease, the probability of infection and that of spreading, and the estimates of these risks.Results and Discussion: A naive method to estimate the risks of infection and spreading of COVID-19 is to calculate the ratio of infected patients to close contacts and the ratio of patients who infected others to all the confirmed patients, respectively. However, these estimates could possibly have significant biases and result in being ineffective for both the exploration and the quantitative assessment of the risk factors in the following ordinary cases: a person contacts closely with many confirmed patients, or a confirmed patient contact closely with many people. Then, some steps are needed to reduce such possible biases for the estimation the risks of both the infection and spreading of COVID-19

Geochemical study of ultramafic rocks from Latowu area of North Kolaka, Southeast Sulawesi and its implication for CO2 sequestration

Geochemistry of ultramafic rocks in the Latowu Area of North Kolaka Regency, Southeast Sulawesi has been investigated with the aim at deciphering of mineral characteristics, chemical composition and their potential use as carbon dioxide storage. Mineralogy was characterized by both scanning electron microscopy (SEM) and X-ray diffractometry (XRD); whereas bulk rock and mineral chemistry were analyzed by means of X-ray fluorescence spectrometry (XRF) and Electron probe microanalyzer (EPMA) respectively. Results of analyses show that lizardite is predominant serpentine mineral present, followed by chrysotile and trace amount of magnetite. Remnants of olivine and pyroxene were detected in some samples but they have been pseudomorphicly replaced by serpentine. Serpentinization of Latowu ultramafic rocks has led to decrease in grain size and density. Lizardite is characterized by fine grained particles with higher in iron. The higher Mg and Fe of the rocks indicate a suitability as feed materials for carbon dioxide sequestration. Mineral and chemical properties of ultramafic rocks have significant role in evaluating the feasibility of mineral carbonation

Practice of Open Sharing at Yamaguchi Center for Arts and Media [YCAM]

Yamaguchi Center for Arts and Media [YCAM] (herein after "YCAM") is an art center focused on media technology. It produces artwork incorporating media technology, develops media technology, archives related information, and provides education. YCAM has open shared its achievements from some of its projects. “Open share” means to publish an achievement so that a third party can utilize it freely within a certain extent. In this paper, introduction of open sharing at YCAM and the practice of implementing open sharing will be described and discussed