Age Is But a Number? An Exploration of Age Differences in Episodic Volunteering

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Age has long been understood as a strong demographic determinant of volunteering. However, to date, limited literature...     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

Product partition latent variable model for multiple change-point detection in multivariate data

The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets.     

The restructuring of career paths in large service sector organizations:'delayering', upskilling and polarisation1

Drawing on detailed case studies of four large service sector organizations this paper finds little evidence of training provision that links skills development with incremental career progression. Past policies of ‘delayering’ have opened up a ‘gap’ in the job ladder and this has both increased the organizational costs of formal training and reduced the likelihood of informal on‐the‐job training being seen as the basis for promotion to the next level. Managers are thus faced with the challenge of how to establish a new set of premises upon which to strengthen the workforce's loyalty and commitment to the organization, in the context of problems of high staff turnover and low job satisfaction. What we find is a greater emphasis on certificated training provision. However, in the absence of a transparent career path employers rely on more intensive techniques of appraisal and selection of workers for a ‘winner‐takes‐all’ career path. Given the importance of skills acquisition as an important building block of the ‘learning society’, our findings suggest that policymakers in Britain cannot rely solely upon the employer to bridge the skill gap evident in large service sector organizations.     

Frustration in Infancy: Implications for Emotion Regulation,Physiological Processes,and Temperament

A study sample of 162 six‐month‐old children was selected from a larger sample of 346 infants on the basis of parents' report of their infants' temperament and a laboratory assessment of temperament. Infants were classified as easily frustrated and less easily frustrated and compared on a number of emotion regulation, physiology, and temperament measures. Results indicated that male and female infants were equally likely to be classified as frustrated and less easily frustrated; however, male infants were less able to regulate physiologically. Easily frustrated infants used different emotion regulation strategies and were observed to be less attentive and more active than less easily frustrated infants when observed in the laboratory. These infants were also characterized by their parents as more active, less attentive, and more distressed to novelty. Infants classified as easily frustrated were more reactive physiologically and less able to regulate physiological reactivity than their less easily frustrated counterparts. It is hypothesized that this cluster of characteristics may constitute a unique temperamental type that may have implications for other types of behavioral functioning. Limitations of the study are that observations are based on a single brief assessment of the infant, modest effect sizes were found, and the study is cross‐sectional.     

Testing the Effects of Collectively Expected Durations of Migration: The Naturalization of Mexicans and Cubans

This study tests a hypothesis that Mexican foreign‐born immigrants who came to the United States for economic reasons naturalize less often than Cubans who immigrate for political reasons. It uses information from the Panel Study of Income Dynamics, Latino Sample, a national sample of 7,453 respondents from the 1989 Latino National Political Survey (LNPS) and the 1990 Panel Study of Income Dynamics (PSID). Ordinal logistic regression is used to examine the hypothesis. The results indicate that while more Mexicans plan to apply or have applied for naturalization, proportionately more Cubans than Mexicans have naturalized. Cuban political immigrants who came to the United States during the first half of the 1960s naturalize more often than their Mexican counterparts. However, the effect of ethnic identity on naturalization is mediated by a number of other predictors of naturalization such as gender, race, urban residence, socioeconomic status and acculturation.