The empirical Bayes estimators of the parameter of the Poisson distribution with a conjugate gamma prior under Stein's loss function

For the hierarchical Poisson and gamma model, we calculate the Bayes posterior estimator of the parameter of the Poisson distribution under Stein's loss function which penalizes gross overestimation and gross underestimation equally and the corresponding Posterior Expected Stein's Loss (PESL). We also obtain the Bayes posterior estimator of the parameter under the squared error loss and the corresponding PESL. Moreover, we obtain the empirical Bayes estimators of the parameter of the Poisson distribution with a conjugate gamma prior by two methods. In numerical simulations, we have illustrated: The two inequalities of the Bayes posterior estimators and the PESLs; the moment estimators and the Maximum Likelihood Estimators (MLEs) are consistent estimators of the hyperparameters; the goodness-of-fit of the model to the simulated data. The numerical results indicate that the MLEs are better than the moment estimators when estimating the hyperparameters. Finally, we exploit the attendance data on 314 high school juniors from two urban high schools to illustrate our theoretical studies.     

How Moroccan‐Dutch parents learn in communities of practice: Evaluating a bottom‐up parenting programme

Research shows that top‐down‐designed parenting programmes do not always meet the needs of postmigration parents. Bottom‐up programmes by migrant organizations hold a promise to fill this gap; however, research about these programmes and appropriate evaluation methodologies is scarce. Drawing upon Wenger's ( 2010 ) “communities of practice,” this paper explores an alternative perspective on parenting programme evaluation. Findings are presented from a study looking into social learning processes of postmigration parents who participated in a bottom‐up programme about raising teenagers in urban areas. Using an ethnographically inspired method combined with a preprogramme and postprogramme design, 115 Moroccan‐Dutch mothers and fathers from 15 programme groups participated. Results show that the programme provided a social learning space in which parents used themselves as resources to learn collectively about parenting. Moreover, parents consciously engaged in learning interactions across learning spaces stretched into their social networks. These analyses showed how parents' development of “learning citizenship” (Wenger, 2009 ) provides us with insight in collective learning dimensions present in a bottom‐up parenting programme, which is often not included in evaluation studies. Implications for practitioners as facilitators of parents' collective learning are presented.     

Children in immediate danger: Emergency removals in Finnish and Irish child protection

This paper presents a qualitative analysis of front‐line practices regarding emergency removals in Finnish and Irish child protection. It examines how the responses to children's immediate danger are framed by legislation and how front‐line practitioners assess the child's situation and make emergency placement decisions. The data consist of interviews with 16 Irish and 33 Finnish social workers. These child welfare protection systems respond differently to a task that appears to be similar. The Irish team‐based practice rests on the social workers' shared assessment of the child's needs, and the formal decision is made by the courts (or police officers at night‐time); and the Finnish practice involves only one single social worker who makes both the assessment and the removal decision. The Irish system is tightly time regulated, whereas the Finnish system provides a more flexible time frame. Both approaches put a lot of stress on social workers' practice, which also includes creative workarounds (e.g., “planned emergency removals” in Finland). Future research will need to explore these features from the point of view of a child's right to protection.     

An Extended Single‐index Model with Missing Response at Random

An extended single‐index model is considered when responses are missing at random. A three‐step estimation procedure is developed to define an estimator for the single‐index parameter vector by a joint estimating equation. The proposed estimator is shown to be asymptotically normal. An algorithm for computing this estimator is proposed. This algorithm only involves one‐dimensional nonparametric smoothers, thereby avoiding the data sparsity problem caused by high model dimensionality. Some simulation studies are conducted to investigate the finite sample performances of the proposed estimators.     

Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models

Outlier detection algorithms are intimately connected with robust statistics that down‐weight some observations to zero. We define a number of outlier detection algorithms related to the Huber‐skip and least trimmed squares estimators, including the one‐step Huber‐skip estimator and the forward search. Next, we review a recently developed asymptotic theory of these. Finally, we analyse the gauge, the fraction of wrongly detected outliers, for a number of outlier detection algorithms and establish an asymptotic normal and a Poisson theory for the gauge.     

A divergence of opinion: how those involved in child and family social work are responding to the challenges of the Internet and social media

This discussion paper suggests that there is possibly a divergence of opinion taking place within the field of child and family social work and that the stated positions are influencing how practitioners identify and deal with risks and opportunities afforded by the Internet and social media. The suggested divergence is examined and the conclusion drawn is that what is taking place mirrors the fact that the introduction of any new technology inevitably brings with it division and debate. In seeking to understand the reaction to digital technology, consideration is given to a series of wider social discourses on childhood and risk, which includes the controversial notion that the profession is a harbinger of moral panic and that the management of risk has been broadened from child protection to child safety. The discussion paper concludes by calling for child and family social work practitioners to have a balanced debate that needs to be informed not only by current research but also by an open and honest discussion about personal use and an acknowledgement that there will be difficult moral and ethical questions to work through.     

Why Frequency is Not Well Defined for Engineering Systems with Nonexponential Failure Times

Dr. Yellman proposes to define frequency as “a time‐rate of events of a specified type over a particular time interval.” We review why no definition of frequency, including this one, can satisfy both of two conditions: (1) the definition should agree with the ordinary meaning of frequency, such as that less frequent events are less likely to occur than more frequent events, over any particular time interval for which the frequencies of both are defined; and (2) the definition should be applicable not only to exponentially distributed times between (or until) events, but also to some nonexponential (e.g., uniformly distributed) times. We make the simple point that no definition can satisfy (1) and (2) by showing that any definition that determines which of any two uniformly distributed times has the higher “frequency” (or that determines that they have the same “frequency,” if neither is higher) must assign a higher frequency number to the distribution with the lower probability of occurrence over some time intervals. Dr. Yellman's proposed phrase, “time‐rate of events … over a particular time interval” is profoundly ambiguous in such cases, as the instantaneous failure rates vary over an infinitely wide range (e.g., from one to infinity), making it unclear which value is denoted by the phrase “time‐rate of events.”     

A comparison of maximum likelihood and least squares for the estimation of a cumulative distribution

Monte Carlo methods are used to compare the methods of maximum likelihood and least squares to estimate a cumulative distribution function. When the probabilistic model used is correct or nearly correct, the two methods produce similar results with the MLE usually slightly superior When an incorrect model is used, or when the data is contaminated, the least squares technique often gives substantially superior results.     

Self‐Construal,Career Decision Self‐Efficacy,and Perceived Barriers Predict Mexican American Women's Life Satisfaction

This study used the social cognitive theory of well‐being (SCTW; Lent, 2004 ) to examine the role of career decision self‐efficacy (CDSE), perceived educational barriers, and independent self‐construal on the life satisfaction of 176 Mexican American college women. A 3‐step hierarchical regression analysis indicated that independent self‐construal, CDSE, and fewer perceived educational barriers significantly predicted greater life satisfaction among Mexican American college women above and beyond the influence of socioeconomic status and generational status. These findings are consistent with SCTW and highlight the need for counselors and researchers to be aware of the role that self‐construal, CDSE, and perceived educational barriers can have on Mexican American women's life satisfaction. Implications for practice at the secondary‐school and university levels are discussed.     

Bias correction for parameter estimates of spatial point process models

When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best.