Unifying Livability and Comparison Theory: Cross-National Time-Series Analysis of Life-Satisfaction

The two major theories of QOL judgment – livability and comparison theories – are tested. The first states that only absolute level of objective variables will affect QOL, whereas the second states that only differences in objective variables will. A 25-year, 8-nation database was developed that allows more powerful tests than previous research. Consistent with previous studies and with livability theory, absolute level of GDP/person had the largest effect on life-satisfaction. Contrary to previous research, a reliable effect was also found for differences in GDP/person and the consumer price index. The length of these effects is 9 or 10 quarters. That is, consumers take into account changes as far back as 2 or 2 1/2 years, in addition to their absolute level of GDP/person.     

A Preliminary Examination of Covitality as Integrated Well-Being in College Students

The emergence of positive psychology has generated increased interest about the correlates of positive psychological functioning. Researchers have identified and studied various positive psychological constructs (e.g., hope, optimism, self-efficacy, gratitude, and life satisfaction) and found them to covary and to be positively associated with optimal human functioning and negatively associated with mental illness. This study of 528 college students examined the co-occurrence of selected positive psychological traits and explored their relations with a proposed second-order latent construct called covitality and with psychological well-being. Structural equation modeling examined each first-order positive psychology construct related to the second-order concept of covitality. Findings supported the second-order latent factor model of covitality, which was also significantly related to indicators of psychological well-being. Implications for theory development related to understanding positive human resources and applications within the context of college student populations are discussed.     

American High School Students’ Perceptions of Determinants of Life Satisfaction

Life satisfaction can be assessed either globally or with regard to satisfaction with specific domains of life. The latter multidimensional approach presumes science has delineated with confidence the specific domains most relevant to evaluating whether the criteria for a good life have been met. This paper shares results of a qualitative study of the perceived determinants of life satisfaction among 30 high school students who were diverse in terms of mental health; 6–10 participants were classified as complete mental health, vulnerable, symptomatic but content, or troubled at two time points separated by a year. Thematic analyses of transcribed individual interviews suggested eight themes that capture the domains of life adolescents perceive influence their happiness. These themes are compared and contrasted to domains included in existing multi-dimensional measures of youth life satisfaction. The factors likely to be particularly salient to students with different levels of mental health are noted.

     

Compensation or Reinforcement? The Stratification of Parental Responses to Children’s Early Ability

Theory and empirical evidence suggest that parents allocate their investments unequally among their children, thus inducing within-family inequality. We investigate whether parents reinforce or compensate for initial ability differences between their children as well as whether these parental responses vary by family socioeconomic status (SES). Using the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) and a twin fixed-effects approach to address unobserved heterogeneity, we find that parental responses to early ability differences between their children do vary by family SES. Contrary to prior findings, we find that advantaged parents provide more cognitive stimulation to higher-ability children, and lower-class parents do not respond to ability differences. No analogous stratification in parental responses to birth weight is found, suggesting that parents’ responses vary across domains of child endowments. The reinforcing responses to early ability by high-SES parents do not, however, led to increases in ability differences among children because parental responses have little effect on children’s later cognitive performance in this twin sample.     

Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms

Competing risks occur in a time-to-event analysis in which a patient can experience one of several types of events. Traditional methods for handling competing risks data presuppose one censoring process, which is assumed to be independent. In a controlled clinical trial, censoring can occur for several reasons: some independent, others dependent. We propose an estimator of the cumulative incidence function in the presence of both independent and dependent censoring mechanisms. We rely on semi-parametric theory to derive an augmented inverse probability of censoring weighted (AIPCW) estimator. We demonstrate the efficiency gained when using the AIPCW estimator compared to a non-augmented estimator via simulations. We then apply our method to evaluate the safety and efficacy of three anti-HIV regimens in a randomized trial conducted by the AIDS Clinical Trial Group, ACTG A5095.     

Estimating nonlinear additive models with nonstationarities and correlated errors

In this paper, we study a nonparametric additive regression model suitable for a wide range of time series applications. Our model includes a periodic component, a deterministic time trend, various component functions of stochastic explanatory variables, and an AR(p) error process that accounts for serial correlation in the regression error. We propose an estimation procedure for the nonparametric component functions and the parameters of the error process based on smooth backfitting and quasimaximum likelihood methods. Our theory establishes convergence rates and the asymptotic normality of our estimators. Moreover, we are able to derive an oracle‐type result for the estimators of the AR parameters: Under fairly mild conditions, the limiting distribution of our parameter estimators is the same as when the nonparametric component functions are known. Finally, we illustrate our estimation procedure by applying it to a sample of climate and ozone data collected on the Antarctic Peninsula.     

Practical procedures to deal with common support problems in matching estimation

This paper assesses the performance of common estimators adjusting for differences in covariates, such as matching and regression, when faced with the so-called common support problems. It also shows how different procedures suggested in the literature affect the properties of such estimators. Based on an empirical Monte Carlo simulation design, a lack of common support is found to increase the root-mean-squared error of all investigated parametric and semiparametric estimators. Dropping observations that are off support usually improves their performance, although the magnitude of the improvement depends on the particular method used.     

Q-LEARNING WITH CENSORED DATA

We develop methodology for a multistage-decision problem with flexible number of stages in which the rewards are survival times that are subject to censoring. We present a novel Q-learning algorithm that is adjusted for censored data and allows a flexible number of stages. We provide finite sample bounds on the generalization error of the policy learned by the algorithm, and show that when the optimal Q-function belongs to the approximation space, the expected survival time for policies obtained by the algorithm converges to that of the optimal policy. We simulate a multistage clinical trial with flexible number of stages and apply the proposed censored-Q-learning algorithm to find individualized treatment regimens. The methodology presented in this paper has implications in the design of personalized medicine trials in cancer and in other life-threatening diseases.     

Generalizing the standardized hazard ratio to multivariate proportional hazards regression,with an application to clinical~genomic studies

The standardized hazard ratio for univariate proportional hazards regression is generalized as a scalar to multivariate proportional hazards regression. Estimators of the standardized log hazard ratio are developed, with corrections for bias and for regression to the mean in high-dimensional analyses. Tests of point and interval null hypotheses and confidence intervals are constructed. Cohort sampling study designs, commonly used in prospective–retrospective clinical genomic studies, are accommodated.