A “brer rabbit” case for reverse mandated benefits

Reverse mandated benefits is a government-mandated policy that requires employees to provide their employers with benefits that workers would not provide otherwise. Of course, only those benefits would be mandated that are worth more to employers than they cost, as determined by political authorities. My case for such a policy argues that it is at least as sensible as policies mandating that employers provide benefits to their employees that would not be provided otherwise.     

A Non-parametric Frailty Model for Temporally Clustered Multivariate Failure Times

Abstract A model is introduced here for multivariate failure time data arising from heterogenous populations. In particular, we consider a situation in which the failure times of individual subjects are often temporally clustered, so that many failures occur during a relatively short age interval. The clustering is modelled by assuming that the subjects can be divided into ‘internally homogenous’ latent classes, each such class being then described by a time‐dependent frailty profile function. As an example, we reanalysed the dental caries data presented earlier in Härkänen et al. [Scand. J. Statist. 27 (2000) 577], as it turned out that our earlier model could not adequately describe the observed clustering.     

Intertemporal choice under timing risk: An experimental approach

This paper investigates how individuals evaluate delayed outcomes with risky realization times. Under the discounted expected utility (DEU) model, such evaluations depend only on intertemporal preferences. We obtain several testable hypotheses using the DEU model as a benchmark and test these hypotheses in three experiments. In general, our results show that the DEU model is a poor predictor of intertemporal choice behavior under timing risk. We found that individuals are averse to timing risk and that they evaluate timing lotteries in a rank-dependent fashion. The main driver of timing risk aversion is nothing but probabilistic risk aversion that stems from the nonlinear treatment of probabilities.     

Which Wald statistic? Choosing a parameterization of the Wald statistic to maximize power in k-sample generalized estimating equations

The Wald statistic is known to vary under reparameterization. This raises the question: which parameterization should be chosen, in order to optimize power of the Wald statistic? We specifically consider k-sample tests of generalized linear models (GLMs) and generalized estimating equations (GEEs) in which the alternative hypothesis contains only two parameters. An example is presented in which such an alternative hypothesis is of interest. Amongst a general class of parameterizations, we find the parameterization that maximizes power via analysis of the non-centrality parameter, and show how the effect on power of reparameterization depends on sampling design and the differences in variance across samples. There is no single parameterization with optimal power across all alternatives. The Wald statistic commonly used under the canonical parameterization is optimal in some instances but it performs very poorly in others. We demonstrate results by example and by simulation, and describe their implications for likelihood ratio statistics and score statistics. We conclude that due to poor power properties, the routine use of score statistics and Wald statistics under the canonical parameterization for GEEs is a questionable practice.     

Beheimatungsprozesse begleiten — ein Werkstattbericht

Supporting processes of belonging in supervision and coachingThe contemporary employee has to cope with frequent changes. Not only does he lose his familiar environment, he also has to find ways to familiarize himself with new places and to develop a fresh sense of belonging. This process can be understood and facilitated by interpreting the German concept of “Heimat“ as something we have to create ourselves. First experiences demonstrate the usefulness of this approach in coaching processes.     

Expected sample moments of concomitants of selected order statistics

In this paper, the task of determining expected values of sample moments, where the sample members have been selected based on noisy information, is considered. This task is a recurring problem in the theory of evolution strategies. Exact expressions for expected values of sums of products of concomitants of selected order statistics are derived. Then, using Edgeworth and Cornish-Fisher approximations, explicit results that depend on coefficients that can be determined numerically are obtained. While the results are exact only for normal populations, it is shown experimentally that including skewness and kurtosis in the calculations can yield greatly improved results for other distributions.     

Physician-nurse migration to the United States: regional and health status origins in relation to legislation and policy

This article examines the origins of physicians and nurses who were admitted as permanent immigrants to the US from 1962-1979. Data are mainly from the Immigration and Naturalization Service. Countries used in the developmental analysis are only those whose population was estimated at 1 million or more as of mid-1979, encompassing 99% of the physicians and 97% of the nurses. Life expectancy at birth is the criterion used to differentiate origin countries by developmental dimension of health status. During the study period, health workers constituted about 30% of immigrants admitted to the US; of these, nurses and physicians constituted 72-82% throughout the study period. The period 1962-1979 has 4 distinct phases, marked by important legislative and/or policy changes; 1) 1962-1965, when the McCarran-Walter Act prevailed; 2) ending in 1968, the 2nd phase covers the transition mandated under the 1965 Immigration Act, which encouraged physician immigration; 3) the 3rd phase, 1969-1976, covers the transition to the 1976 Immigration and Nationality Act amendments; and 4) the 4th stage is 1977-1979. Results show that 1) under the McCarran-Walter Act, North America became the dominant physician source; 2) from 1966-1968, Asia attained dominance as the physician source and became even more predominant after 1968; 3) North America produced relatively few physicians in the early 1970s; 4) Europe produced substantially fewer physicians in the 1970s than in the 1960s; 5) South America, Africa, and Oceania were the lowest contributors of physicians; 6) during the McCarran-Walter years, North America and Europe produced almost 90% of nurses admitted into the US; 7) the 1965 Immigration Act and its aftermath resulted in Asia becoming the dominant source of nurses; 8) prior to the 1965 Immigration Act, Canada generated 20% of the aggregate number of physicians; 9) the Philippines surpassed Canada during the transition and India led after the transition; and 10) Canada supplied 30% of the nurses up through the transition, with the Philippines in the lead 1969-1979. Low health status countries were a relatively minor nurse source. Health status at the origin was a far less significant determinant of physician immigration than that of nurses. English language high and low health status country groups produced substantially more physician and nurse immigrants that their corresponding non-English language counterparts. The US attracted more physicians and nurses from less developed countries than more developed countries after 1968.     

Child health,breast-feeding,and survival in Malaysia: a random-effects logit approach

This study examines the possibility that estimation of the effect of breast-feeding on infant survival is affected by selection bias, in that children who are healthier at birth may be more likely to be breast-fed. Data are from the 1976 Malaysian Family Life Survey. "Ordinary logit models for breast-feeding and survival are estimated, and the results suggest that selection is indeed present. For example, children of higher birth weight appear to be more likely to be breast-fed and likely to survive. In addition, weight at birth and the duration of breast-feeding appear to be linked." Using birth weight as an indicator for the child's health, the authors conclude that "the direct influence of breast-feeding on survival remains of overwhelming importance even after corrections for selection bias are made."