Covariates and Random Effects in a Gamma Process Model with Application to Degradation and Failure

The gamma process is a natural model for degradation processes in which deterioration is supposed to take place gradually over time in a sequence of tiny increments. When units or individuals are observed over time it is often apparent that they degrade at different rates, even though no differences in treatment or environment are present. Thus, in applying gamma-process models to such data, it is necessary to allow for such unexplained differences. In the present paper this is accomplished by constructing a tractable gamma-process model incorporating a random effect. The model is fitted to some data on crack growth and corresponding goodness-of-fit tests are carried out. Prediction calculations for failure times defined in terms of degradation level passages are developed and illustrated.     

The Maltreatment of Children: A Review of Theories and Research

This article reviews the literature pertaining to the causes of child maltreatment. The review discusses 68 articles from various disciplines and organizes them into four predominant theories; psychodynamic, social learning, social psychological, and sociological. Research evidence supporting each of the theories is described and critiqued.     

Perceived discrimination,traditional practices,and depressive symptoms among American Indians in the upper midwest

American Indian adults are thought to experience significant depressive symptoms at rates several times higher than adults in the general population, yet we know very little about factors associated with depressive symptoms among this under studied group. Many researchers have argued that depressive symptoms are associated with conflicts between American Indian traditional cultural values, practices, and beliefs and those of the majority culture. This report, based on a sample 287 American Indian adults from the upper Midwest, takes into account two measures of cultural effects: perceived discrimination, as one indicator of culture conflict, and traditional practices, as a measure of cultural identification. The results indicate that discrimination is strongly associated with depressive symptoms among American Indian adults and that engaging in traditional practices is negatively related to depressive symptoms. Moreover, interaction effects between perceived discrimination and traditional practices indicate that engaging in traditional practices buffers the negative effects of discrimination among those who regularly participate in them.     

Semiparametric Inference Methods for General Time Scale Models

In this paper we consider semiparametric inference methods for the time scale parameters in general time scale models (Oakes, 1995, Duchesne and Lawless, 2000). We use the results of Robins and Tsiatis (1992) and Lin and Ying (1995) to derive a rank-based estimator that is more efficient and robust than the traditional minimum coefficient of variation (min CV) estimator of Kordonsky and Gerstbakh (1993) for many underlying models. Moreover, our estimator can readily handle censored samples, which is not the case with the min CV method.     

Knowledge, Consequences, and Experience: The Social Construction of Environmental Problems

Perhaps one of the most obvious yet difficult questions confronting sociologists concerned with large-scale environmental problems is an epistemological one: How do we know what we know about the state of the environment? This paper explores the realist and constructionist approaches to environmental-social problems and finds both inadequate as currently formulated. A case is made for a phenomenological constructionism that moves beyond relativism and simple definitional constructionism by exploring how we actually experience the world. This approach recognizes the existence of a natural world independent of our constructions, yet suggests that our knowledge of it is always mediated, indirect, and pragmatically motivated.     

NEGOTIATING CONTINUITY: Family and Religious Socialization for Second-Generation Asian Americans

This article examines second-generation Asian Americans' explanations of the significant influences on their own religious identities. Data include interviews (N = 73) with college-aged Asian Americans from different religious traditions and ethnic backgrounds. Respondents viewed families as the most significant influence on current religiosity. Mothers and fathers were mentioned most often, followed by extended kin, siblings, and relatives, who acted as what we call "reinforcers,""substitutes," or "contrasts" to the roles that parents played in religious socialization. These roles occurred along two religious configurations within families: heterogeneous or homogeneous degrees of religious commitment and religious affiliation. Directions for future research and contributions to the religious transmission literature follow.     

Social welfare functions that satisfy Pareto,anonymity, and neutrality,but not independence of irrelevant alternatives

In the presence of Pareto, non-dictatorship, full domain, and transitivity, an extremely weak independence condition disallows both anonymity and neutrality.     

Newsvendor Problems with Demand Shocks and Unknown Demand Distributions

In today's competitive market, demand volume and even the underlying demand distribution can change quickly for a newsvendor seller. We refer to sudden changes in demand distribution as demand shocks. When a newsvendor seller has limited demand distribution information and also experiences underlying demand shocks, the majority of existing methods for newsvendor problems may not work well since they either require demand distribution information or assume stationary demand distribution. We present a new, robust, and effective machine learning algorithm for newsvendor problems with demand shocks but without any demand distribution information. The algorithm needs only an approximate estimate of the lower and upper bounds of demand range; no other knowledge such as demand mean, variance, or distribution type is necessary. We establish the theoretical bounds that determine this machine learning algorithm's performance in handling demand shocks. Computational experiments show that this algorithm outperforms the traditional approaches in a variety of situations including large and frequent shocks of the demand mean. The method can also be used as a meta‐algorithm by incorporating other traditional approaches as experts. Working together, the original algorithm and the extended meta‐algorithm can help manufacturers and retailers better adapt their production and inventory control decisions in dynamic environments where demand information is limited and demand shocks are frequent      

Ordinal independence in nonlinear utility theory

Individual behavior under uncertainty is characterized using a new axiom, ordinal independence, which is a weakened form of the von Neumann-Morgenstern independence axiom It states that if two distributions share a tail in common, then this tail can be modified without altering the individual's preference between these distributions. Preference is determined by the tail on which the distributions differ. This axiom implies an appealing and simple functional form for a numerical representation of preferences. It generalizes the form of anticipated utility, and it explains some well-known forms of behavior, such as the Friedman-Savage paradox, that anticipated utility cannot.