A random-effect regression model for medical follow-up studies

In medical follow-up studies, it is often the case that patients under study are required to visit a clinical centre at prespecified times and the observed information consists only of the numbers of events of interest that have occurred between visits. A major difficulty arising in the analysis of these studies is that actual observation times among the patients are usually different. To deal with this difficulty, observation times are usually assumed to be fixed and grouping techniques are commonly employed. It is well known that analyses which are based on grouping methods may yield conclusions which depend crucially on the actual choice of grouping intervals. Loss to follow-up is another problem that usually occurs in such studies. In this paper we consider a situation in which the different observation times arise from some random effect. A regression-based method for the analysis of the event counts is presented. One of the principal advantages of this approach is the complete absence of any grouping. The merits of this regression-based methodology are illustrated through an analysis of the occurrence rates of nausea in the National Cooperative Gallstone Study.     

Asymptotic behaviour of the mean integrated squared error of kernel density estimators for dependent observations

Let X₁, X₂, … be a strictly stationary sequence of observations, and g be the joint density of (X₁, …, X_d) for some fixed d ? 1. We consider kernel estimators of the density g. The asymptotic behaviour of the mean integrated squared error of the kernel estimators is obtained under an assumption of weak dependence between the observations.     

Stubbornness,Power, and Equilibrium Selection in Repeated Games with Multiple Equilibria

Axelord’s [(1970), Conflict of Interest, Markham Publishers, Chicago] index of conflict in 2 × 2 games with two pure strategy equilibria has the property that a reduction in the cost of holding out corresponds to an increase in conflict. This article takes the opposite view, arguing that if losing becomes less costly, a player is less likely to gamble to win, which means that conflict will be less frequent. This approach leads to a new power index and a new measure of stubbornness, both anchored in strategic reasoning. The win probability defined as power constitutes an equilibrium refinement which differs from Harsanyi and Selten’s [(1988), A General Theory of Equilibrium Selection in Games, MIT Press, Cambridge] refinement. In contrast, Axelrod’s approach focuses on preferences regarding divergences from imaginary outmost rewards that cannot be obtained jointly. The player who is less powerful in an asymmetric one-shot game becomes more powerful in the repeated game, provided he or she values the future sufficiently more than the opponent. This contrasts with the view that repetition induces cooperation, but conforms with the expectation that a more patient player receives a larger share of the pie.      

基于学习的孵化器与创投协同知识创造资源共享研究

将学习因素纳入科技企业孵化器与创投多阶段协同知识创造资源共享的微观机制,建立孵化器与创投多阶段重复主从博弈模型,研究学习因素、税收强度、财政返还、创投股权对维系孵化器与创投协同知识(信息)合作的作用,以及孵化器的最优参与度和双方总的最优投入.研究发现,当孵化器与创投进行知识(信息)协同创造后从创业项目获取收益的比例要高于创投时,孵化器参与到与创投的合作.在满足孵化器与创投合作的条件下,孵化器的最优参与度与政府税收强度和财政返还比例正相关,与创投在创业项目中所占股份负相关.孵化器和创投总的最优投入水平与税收强度、财政返还比例、初始学习因素正相关,与创投在项目中所占股份的比例、博弈阶段长度和市场利率负相关.     

Simple Bounds on the Value of a Reputation

We introduce entropy techniques to study the classical reputation model in which a long‐run player faces a series of short‐run players. The long‐run player's actions are possibly imperfectly observed. We derive explicit lower and upper bounds on the equilibrium payoffs to the long‐run player.     

Estimation for change point of discretely observed ergodic diffusion processes

We treat the change point problem in ergodic diffusion processes from discrete observations. Tonaki et al. (2021a) proposed adaptive tests for detecting changes in the diffusion and drift parameters in ergodic diffusion process models. When any change in the diffusion or drift parameter is detected by this or any other method, the next question to consider is where the change point is located. Therefore, we propose the method to estimate the change point of the parameter for two cases: the case where there is a change in the diffusion parameter, and the case where there is no change in the diffusion parameter but a change in the drift parameter. Furthermore, we present rates of convergence and distributional results of the change point estimators. Some examples and simulation results are also given.     

Modeling immunogenecity data to establish screening bioassays cut point

The response of immunogenecity anti-drug antibody (ADA) generally includes biological and analytical variability. The nature of biological and analytical variations may lead to a variety of symmetric and asymmetric ADA data. As a result, current statistical methods may yield unreliable results because these methods assume special types of symmetric or asymmetric ADA data. In this paper, we survey and compare parametric models that are useful for analyzing a variety of asymmetric data that have rarely been used to calculate assay cut points. These models include symmetric distributions as limiting case; therefore, they are useful in the analysis of a variety of symmetric data. We also investigate two nonparametric approaches that have received little attention in screening cut point calculations. A simulation study was conducted to compare the performance of the methods. We evaluate the methods using four published different types of data, and make recommendations concerning the use of the methods.     

Associations Between Adolescents' Antisocial Behavior,Conflict Management Styles,and Romantic Relationship Breakup: An Observational Study

Adolescents' antisocial behavior and negative conflict management styles are each associated with adverse romantic relationship outcomes, yet little research exists on their associations. We investigated whether adolescents' antisocial behavior was associated with conflict management styles, and whether it predicted breakup 3 months later. In total, 91 adolescent couples (M_age = 16.43, SD = 0.99; 41.2% Hispanic/Latinx) participated in videotaped conflict discussions coded for negotiation, coercion, and avoidance. Actor–partner interdependence models suggest adolescents' antisocial behavior is associated with decreased use of negotiation (couple pattern) and increased use of coercion (actor pattern). No significant associations were found for avoidance. Neither antisocial behavior nor conflict management styles predicted breakup. Findings are discussed in light of the unique developmental importance of adolescents' romantic relationships.     

Natural cubic splines for the analysis of Alzheimer's clinical trials

Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.