A note on interval‐censored lifetime data and the constant‐sum condition of oiler,gómez & calle (2004)

Oiler, Gomez & Calle (2004) give a constant sum condition for processes that generate interval‐censored lifetime data. They show that in models satisfying this condition, it is possible to estimate non‐parametrically the lifetime distribution based on a well‐known simplified likelihood. The author shows that this constant‐sum condition is equivalent to the existence of an observation process that is independent of lifetimes and which gives the same probability distribution for the observed data as the underlying true process.     

Models and estimation for systems with recurrent events and usage processes

This paper considers settings where populations of units may experience recurrent events, termed failures for convenience, and where the units are subject to varying levels of usage. We provide joint models for the recurrent events and usage processes, which facilitate analysis of their relationship as well as prediction of failures. Data on usage are often incomplete and we show how to implement maximum likelihood estimation in such cases. Random effects models with linear usage processes and gamma usage processes are considered in some detail. Data on automobile warranty claims are used to illustrate the proposed models and estimation methodology.     

Pseudolikelihood estimation in a class of problems with response-related missing covariates

Many practical situations involve a response variable Y and covariates X , where data on (Y, X ) are incomplete for some portion of a sample of individuals. We consider two general types of pseudolikelihood estimation for problems in which missingness may be response-related. These are typically simpler to implement than ordinary maximum likelihood, which in this context is semiparametric. Asymptotics for the pseudolikelihood methods are presented, and simulations conducted to investigate the methods for an important class of problems involving lifetime data. Our results indicate that for these problems the two methods are effective and comparable with respect to efficiency.     

Evaluation of program success for programs with multiple trials in binary outcomes

A late‐stage clinical development program typically contains multiple trials. Conventionally, the program's success or failure may not be known until the completion of all trials. Nowadays, interim analyses are often used to allow evaluation for early success and/or futility for each individual study by calculating conditional power, predictive power and other indexes. It presents a good opportunity for us to estimate the probability of program success (POPS) for the entire clinical development earlier. The sponsor may abandon the program early if the estimated POPS is very low and therefore permit resource savings and reallocation to other products. We provide a method to calculate probability of success (POS) at an individual study level and also POPS for clinical programs with multiple trials in binary outcomes. Methods for calculating variation and confidence measures of POS and POPS and timing for interim analysis will be discussed and evaluated through simulations. We also illustrate our approaches on historical data retrospectively from a completed clinical program for depression. Copyright © 2015 John Wiley & Sons, Ltd.     

A corrected likelihood method for the proportional hazards model with covariates subject to measurement error

There has been extensive interest in discussing inference methods for survival data when some covariates are subject to measurement error. It is known that standard inferential procedures produce biased estimation if measurement error is not taken into account. With the Cox proportional hazards model a number of methods have been proposed to correct bias induced by measurement error, where the attention centers on utilizing the partial likelihood function. It is also of interest to understand the impact on estimation of the baseline hazard function in settings with mismeasured covariates. In this paper we employ a weakly parametric form for the baseline hazard function and propose simple unbiased estimating functions for estimation of parameters. The proposed method is easy to implement and it reveals the connection between the naive method ignoring measurement error and the corrected method with measurement error accounted for. Simulation studies are carried out to evaluate the performance of the estimators as well as the impact of ignoring measurement error in covariates. As an illustration we apply the proposed methods to analyze a data set arising from the Busselton Health Study [Knuiman, M.W., Cullent, K.J., Bulsara, M.K., Welborn, T.A., Hobbs, M.S.T., 1994. Mortality trends, 1965 to 1989, in Busselton, the site of repeated health surveys and interventions. Austral. J. Public Health 18, 129–135].     

Likelihood ratio procedures and tests of fit in parametric and semiparametric copula models with censored data

Copula models for multivariate lifetimes have become widely used in areas such as biomedicine, finance and insurance. This paper fills some gaps in existing methodology for copula parameters and model assessment. We consider procedures based on likelihood and pseudolikelihood ratio statistics and introduce semiparametric maximum likelihood estimation leading to semiparametric versions. For cases where standard asymptotic approximations do not hold, we propose an efficient simulation technique for obtaining p-values. We apply these methods to tests for a copula model, based on embedding it in a larger copula family. It is shown that the likelihood and pseudolikelihood ratio tests are consistent even when the expanded copula model is misspecified. Power comparisons with two other tests of fit indicate that model expansion provides a convenient, powerful and robust approach. The methods are illustrated on an application concerning the time to loss of vision in the two eyes of an individual.     

The impact of the promise of scholarships and altering school structure on college plans, preparation, and enrollment

The Washington State Achiever (WSA) program was a large-scale educational intervention of scholarships, mentoring, and school redesign designed to encourage students from moderate and low income families to attend college in Washington State. Using a quasi-experimental design based on pre- and post-intervention surveys of high school seniors in program and non-program schools, we find a significant WSA effect on educational outcomes, net of the demographic and socioeconomic composition of students across schools. Across the three intervention high schools, the program is strongly significant in one school, significant after a lag in another school, and not significant in a third. We speculate about the potential reasons for the differential program effect across high schools.     

Designing and facilitating collaboration in R&D: A case study

This case study aims to highlight the strategic decisions and managerial practices in the formation and operation of a co-located research unit within a national laboratory. The empirical evidence is based on interviews with members of the research unit as well as responses from a research environment survey. The findings of the case study suggest specific strategies that are conducive not only for the co-location of research units but also for research management in general. Principal among these are the need to balance increases in diversity and complexity with mechanisms of integration and the use of specific management practices and leadership qualities that support these activities.     

How Academic Achievement,Attitudes, and Behaviors Relate to the Course of Substance Use During Adolescence: A 6‐Year,Multiwave National Longitudinal Study

Self‐report data regarding alcohol, cigarette, and marijuana use were collected biennially from ages 14 to 20 in a nationally representative panel sample of adolescents (N=1,897) from the Monitoring the Future study. Growth curve analyses were performed using hierarchical linear modeling to consider psychosocial background, motivation and school attitudes, and parental and peer influences at age 14 as predictors of concurrent substance use and change in substance use. Results indicated that school misbehavior and peer encouragement of misbehavior were positively associated with substance use at age 14 and with increased use over time; school bonding, school interest, school effort, academic achievement, and parental help with school were negatively associated. The protective effects of positive school attitudes and perceptions of high status connected to academics were stronger for low‐achieving compared with high‐achieving youth. Implications for a developmental perspective on substance use etiology and prevention are discussed.