Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

Improved Monte Carlo inference for models with additive error

Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density estimates from simulated realizations of the model. Unfortunately, the bias inherent in density estimation can cause bias in the resulting log-likelihood estimate that alters the location of its maximizer. In this paper a methodology for radically reducing this bias is developed for models with an additive error component. An illustrative example involving a stochastic model of molecular fragmentation and measurement is given.     

Using a computer simulation game to teach family time use concepts

A computer simulation game designed to give students insights into family time use concepts has been used in an introductory family resource management class at Ohio State University and other universities. The game allows for planning for time use changes over the family life cycle. The game can give students insights into economic and sociological models of time use. It is possible that future versions of the game could be used in family counseling.His research interests include derivation of optimal decision-making rules for families and family financial management.Her research interests include financial management over the life course including financial ratios, baby boomers, and retirement. She received her Ph.D. in 1993 from The Ohio State University in Family Resource Management.His research interests include the time trade-offs made between couples, financial planning over the life cycle, and the interaction of time and money between families and their home-based businesses. He received his Ph.D. in 1993 from The Ohio State University in Family Resource Management.     

Intra-industry diversification effects under firm-specific contingencies on the demand side

How do firm-specific, demand-related factors influence the relationship between intra-industry diversification (IID) and performance? Recent findings regarding the performance effects of IID depict a complex picture with curvilinear relationships and several contingencies. However, firm-specific contingencies on the demand side have remained unexplored. We analyze how IID relates to firm performance (market share) in the German automotive industry using panel data between 1999 and 2008. We specifically focus on a firm's high-quality brand image as a demand-side contingency. We find support for our hypotheses of complex curvilinear relationships as well as for moderating effects of brand quality. Our results have significant theoretical implications for the IID literature.     

The relationship between presenteeism and job satisfaction: A mediated moderation model using work engagement and perceived organizational support

Research on presenteeism has largely focused on its prevalence, determinants and consequences on the health of both employees and organizations. To date, few studies have examined the influence of presenteeism on workers’ attitudinal and motivational responses. Based on the Effort–Recovery Theory, this study evaluates the mediating effect of work engagement in the relationship between presenteeism and job satisfaction. Building on previous work, this study also proposes to consider perceived organizational support as a moderator of the work engagement–job satisfaction relationship. Presented in the form of a mediated moderation model, the results of bootstrapped regression analyses show three main results. First, presenteeism is negatively associated with work engagement and job satisfaction. Secondly, work engagement is one of the factors through which presenteeism influences job satisfaction. Thirdly, perceived organizational support moderates the association between work engagement and job satisfaction so that, at a low level of work engagement, feeling supported by the organization makes a difference on job satisfaction. Overall, this research is part of the limited number of studies that have focused on the interplay existing between presenteeism and its consequences in terms of job attitudes.     

A Multivariate Model for Repeated Failure Time Measurements

A parametric multivariate failure time distribution is derived from a frailty-type model with a particular frailty distribution. It covers as special cases certain distributions which have been used for multivariate survival data in recent years. Some properties of the distribution are derived: its marginal and conditional distributions lie within the parametric family, and association between the component variates can be positive or, to a limited extent, negative. The simple closed form of the survivor function is useful for right-censored data, as occur commonly in survival analysis, and for calculating uniform residuals. Also featured is the distribution of ratios of paired failure times. The model is applied to data from the literature     

Going to Pieces: Paul Monette and the Fragments of the Tribe

Author of the highly acclaimed Borrowed Time: An AIDS Memoir (1988) and winner of the 1992 National Book Award for his autobiography Becoming a Man: Half a Life Story, Paul Monette died of complications from AIDS in Los Angeles on February 12, 1995. His most recent work, Last Watch of the Night: Essays Too Personal and Otherwise (1994), is his third volume in a trilogy of autobiographical writing on growing up gay, coming-out, and living with AIDS. A graduate of Phillips Academy and Yale University, Monette received a number of awards for his writing and his work as an outspoken voice in the battle against AIDS, including the National Book Award, three Lambda Literary awards, the PEN Center West Freedom to Write Award, and three honorary doctorate degrees, from Wesleyan University, the City University of New York, and the State University of New York at Oswego. A memorial service was held for Monette on Sunday, February 19, 1995, at the Directors Guild of America on Sunset Boulevard in Los Angeles. Paul Monette was 49.     

The missing bridge: How immigrant networks keep Americans out of dirty jobs

Immigrants are over half of the new entrants in occupations in southwestern labor markets that range from farmworker to janitor to engineering professor. This paper explains how the availability of immigrant workers changes employment practices in ways that push and pull Americans out of jobs which remain "dirty" or unattractive to U.S. workers. An immigrant network that eventually takes over an enterprise's jobs can begin by accident or design. Accidental immigrant takeovers begin with pioneer workers who persist in high turnover jobs such as seasonal farmworker. These workers offer to bring their friends and relatives to fill vacancies as they occur. Takeovers by design sometimes follow a strike in which immigrants are recruited to be strikebreakers. After immigrants dominate the workforce, the language and culture of the workplace change in ways that make American workers feel out-of-place. Employers feel under no compulsion to upgrade dirty jobs as long as immigrant workers are available, so the technology and productivity of immigrant-enclave jobs tend to be frozen, guaranteeing that dirty jobs get less and less attractive to Americans. Indeed, industries dependent on immigrant workers often turn protectionist when they realize that even low immigrant wages are not sufficient to ensure their survival in the global marketplace. In this way, Americans lose out in several ways: They must compete directly with immigrant workers in the labor market, and then pay higher prices for the goods produced by immigrant workers because the industries preserved by them demand protection from imports. This paper will explore the manner in which immigrant networks displace Americans from dirty jobs and how the availability of immigrant workers can preserve sunset industries which turn protectionist. Examples from fruit and vegetable agriculture, garments, and shoes will be discussed.     

An extension of ebloc to valued graphs

In this paper we show how the algorithm EBLOC can be extended to deal with valued data directly. The technique is then applied to Sampson's (1969) monastery data and comparisons are made with the original EBLOC algorithm.