Model selection for Lévy measures in diffusion processes with jumps from discrete observations

We deal with parametric inference and selection problems for jump components in discretely observed diffusion processes with jumps. We prepare several competing parametric models for the Lévy measure that might be misspecified, and select the best model from the aspect of information criteria. We construct quasi-information criteria (QIC), which are approximations of the information criteria based on continuous observations.     

Threshold Estimation for Stochastic Processes with Small Noise

Consider a process satisfying a stochastic differential equation with unknown drift parameter, and suppose that discrete observations are given. It is known that a simple least squares estimator (LSE) can be consistent but numerically unstable in the sense of large standard deviations under finite samples when the noise process has jumps. We propose a filter to cut large shocks from data and construct the same LSE from data selected by the filter. The proposed estimator can be asymptotically equivalent to the usual LSE, whose asymptotic distribution strongly depends on the noise process. However, in numerical study, it looked asymptotically normal in an example where filter was chosen suitably, and the noise was a Lévy process. We will try to justify this phenomenon mathematically, under certain restricted assumptions.     

Simple Formulae for Evaluating the Potential Impact of Confounding Bias

Unmeasured confounding is a common problem in observational studies. This article presents simple formulae that can set the bounds of the confounding risk ratio under three standard populations of the exposed, unexposed, and total groups. The bounds are derived by considering the confounding risk ratio as a function of the prevalence of a covariate, and can be constructed using only information about either the exposure–confounder or the disease–confounder relationship. The formulae can be extended to the confounding odds ratio in case–control studies, and the confounding risk difference is discussed. The application of these formulae is demonstrated using an example in which estimation may suffer from bias due to population stratification. The formulae can help to provide a realistic picture of the potential impact of bias due to confounding.     

Monte-Carlo Sensitivity Analysis for Controlled Direct Effects Using Marginal Structural Models in the Presence of Confounded Mediators

In randomized trials, investigators are frequently interested in estimating the direct effect of a treatment on an outcome that is not relayed by intermediate variables, in addition to the usual intention-to-treat (ITT) effect. Even if the ITT effect is not confounded due to randomization, the direct effect is not identified when unmeasured variables affect the intermediate and outcome variables. Although the unmeasured variables cannot be adjusted for in the models, it is still important to evaluate the potential bias of these variables quantitatively. This article proposes a sensitivity analysis method for controlled direct effects using a marginal structural model that is an extension of the sensitivity analysis method of unmeasured confounding introduced in the context of observational studies. The proposed method is illustrated using a randomized trial of depression.     

从公共哲学的视野看日本和平宪法

战后日本,三种公共哲学最具有影响力,它们是立宪主义的民主主义与和平主义,经济发展和新民族主义.和平宪法存在天皇制等历史局限性和问题.和平宪法的现实主义因素有:对本国政府和军队的怀疑主义,原子弹受害经验,国家主权的自主限制,新国民原理等,和平宪法维护了日本战后60年没有发动过战争,防止了军国主义的复活,保持了"和平国家"的形象,战后的民主主义与和平主义没有国民的精力和国家资源使用到军事方面等是不容忽视的重要事实.     

Threshold selection in jump-discriminant filter for discretely observed jump processes

Threshold estimation is one of the useful techniques in the inference for jump-type stochastic processes from discrete observations. In this method, a jump-discriminant filter is used to infer the continuous part and the jump part separately. Although there are several choices for the filter, statistics constructed via filters are often sensitive to the choice. This paper presents some numerical procedures for selecting a suitable filter based on observations.     

Sexual abuse and juvenile delinquency

Case records were reviewed of 214 young women admitted to a Juvenile Classification Home in Japan for delinquent behaviour between 1983 and 1987. In 10 cases there were reports of a history of sexual abuse and these were 3 times more likely to be admitted to a Detention Home than other cases. All 10 women came from disrupted and economically disadvantaged family backgrounds. Most were depressed with low self-esteem. Five women were physically abused prior to sexual abuse, but behavioural problems were only concurrent and consequent to the sexual abuse. Most of the women were not believed by their mothers at the time of disclosure. Those women who were later believed by their mothers were more likely to return home (with the perpetrators no longer present) and less likely to continue to be victims of sexual abuse.     

An Approach for Estimating Causal Effects in Randomized Trials with Noncompliance

We developed methods for estimating the causal risk difference and causal risk ratio in randomized trials with noncompliance. The developed estimator is unbiased under the assumption that biases due to noncompliance are identical between both treatment arms. The biases are defined as the difference or ratio between the expectations of potential outcomes for a group that received the test treatment and that for the control group in each randomly assigned group. Although the instrumental variable estimator yields an unbiased estimate under a sharp null hypothesis but may yield a biased estimate under a non-null hypothesis, the bias of the developed estimator does not depend on whether this hypothesis holds. Then the estimate of the causal effect from the developed estimator may have a smaller bias than that from the instrumental variable estimator when the treatment effect exists. There is not yet a standard method for coping with noncompliance, and thus it is important to evaluate estimates under different assumptions. The developed estimator can serve this purpose. Its application to a field trial for coronary heart disease is provided.     

Perspectives of South African caregivers in receipt of Child Support Grants: Implications for family strengthening interventions

Cash transfers have delivered measurable benefits for poor and vulnerable children in low‐ and middle‐income countries. However, on its own, a cash transfer is insufficient to promote holistic child well‐being. In the quest for appropriate complementary family support services, known as ‘cash plus’ programing, this qualitative study sought to explore the perspectives of a group of South African caregivers, all of whom were in receipt of a Child Support Grant (CSG), in relation to their own caregiving and family functioning. Critical areas of support to families were identified to further scale up the already positive impacts of the CSG, such as mental health services, social supports for caregivers, decreasing levels of poverty and growing caregiving knowledge and skills. Key conclusions are that improving the quality and integration of public services and developing culturally appropriate and evidence‐based family strengthening programmes are critical to complement and boost the positive impacts of the CSG.