曝露開始から死亡までが超長期の場合の医学統計 -日本の例

Open House, ISM in Tachikawa, 2018.6.15統計数理研究所オープンハウス（立川）、H30.6.15ポスター発

経時データ解析のための自己回帰線型混合効果モデル

Open House, ISM in Tachikawa, 2014.6.13統計数理研究所オープンハウス（立川）、H26.6.13ポスター発

曝露開始から死亡までが超長期の場合の医学統計-英国の例

Open House, ISM in Tachikawa, 2015.6.19統計数理研究所オープンハウス（立川）、H27.6.19ポスター発

女性の方が高くなった米国肺癌死亡率と喫煙指標

Open House, ISM in National Center of Sciences Building, 2019.6.05統計数理研究所オープンハウス（学術総合センター）、R1.6.5ポスター発

曝露開始から死亡までが超長期の場合の医学統計 -米国の例

Open House, ISM in Tachikawa, 2016.6.17統計数理研究所オープンハウス（立川）、H28.6.17ポスター発

COVID-19と学術論文－Science

ISM Online Open House, 2021.6.18統計数理研究所オープンハウス（オンライン開催）、R3.6.18ポスター発

COVID-19と学術論文- 日本

ISM Online Open House, 2020.10.27統計数理研究所オープンハウス（オンライン開催）、R2.10.27ポスター発

Screening method for severe sleep-disordered breathing in hypertensive patients without daytime sleepiness

SummaryThe high prevalence of sleep-disordered breathing (SDB) in hypertensive patients has been well studied. However, regular screening of SDB in these patients is not performed routinely as the diagnostic procedures are both time-consuming and labour-intensive. Overnight portable device screening is useful, but is sometimes not acceptable for asymptomatic SDB patients. We evaluated the usefulness of daytime 30-min recording with a portable recording device during pulse wave velocity (PWV) measurement sessions as a screening method for detection of asymptomatic SDB in hypertensive patients. Eighty-one hypertensive patients underwent 30-min daytime screening session using a Type III portable recording device during PWV measurement. Each screening session was followed by full overnight Level I polysomnography (PSG). The screening session included recordings of airflow (mouth–nose), chest movement, oximetry, and electrocardiography. The correlation coefficient between respiratory disturbance index (RDI) by screening session and apnea–hypopnea index (AHI) by PSG was 0.64. Using AHI ≥30 as diagnostic of severe SDB, 47 of 80 patients had the disorder based on PSG results. Using an RDI cut-off value of 22, the sensitivity and specificity for detection of severe SDB were 86.1% and 64.5%, respectively. Daytime 30-min recording with a portable device for apnea detection during PWV recording is useful for screening of asymptomatic severe SDB in hypertensive patients

Longitudinal data analysis: autoregressive linear mixed effects models

This book provides a new analytical approach for dynamic data repeatedly measured from multiple subjects over time. Random effects account for differences across subjects. Auto-regression in response itself is often used in time series analysis. In longitudinal data analysis, a static mixed effects model is changed into a dynamic one by the introduction of the auto-regression term. Response levels in this model gradually move toward an asymptote or equilibrium which depends on covariates and random effects. The book provides relationships of the autoregressive linear mixed effects models with linear mixed effects models, marginal models, transition models, nonlinear mixed effects models, growth curves, differential equations, and state space representation. State space representation with a modified Kalman filter provides log likelihoods for maximum likelihood estimation, and this representation is suitable for unequally spaced longitudinal data. The extension to multivariate longitudinal data analysis is also provided. Topics in medical fields, such as response-dependent dose modifications, response-dependent dropouts, and randomized controlled trials are discussed. The text is written in plain terms understandable for researchers in other disciplines such as econometrics, sociology, and ecology for the progress of interdisciplinary research