A SCALE IN SEARCH OF A CONSTRUCT: COMMENTS ON GAVIN AND WAMBOLDT

The article examines some issues raised in Gavin and Wamboldt's (1992) recent study on the Family-of-Origin Scale (FOS) (Hovestadt, Anderson, Piercy, Cochran, & Fine, 1985). The discussion centers on unresolved concerns regarding the validity and utility of the FOS and on unsubstantiated and potentially misleading claims made in the Gavin and Wamboldt article. A case is made for conceptual and methodological precision in the study of family phenomena.     

Ideologies & Narratives in Relation to ‘Fat’ Children as Bullies, ‘Easy Targets’ and Victims

In this study, we explore narratives in relation to ‘fatness’, drawing on focus group interviews with parents, early years practitioners, teachers and young people. The study is located in a larger study on bullying and resilience, with no specific focus on obesity or ‘fatness’. Analysis of the interview data highlighted a recurrent focus on ‘fatness’ within the participants’ narratives, by labelling and stigmatising the ‘fat kid’ and ‘bigger children’. We conclude that obesity and fatness, as abnormalities, are now included in commonsense talk in relation to ‘easy targets’, victims and bullies.     

The Value of Supplier Information to Improve Management of a Retailer's Inventory

The distribution of lead time demand is essential for determining reorder points in inventory systems. Usually, the distribution of lead time demand is approximated directly. However, in some cases it may be worthwhile to take the demand per unit time and lead time into account, particularly when specific information is available. This paper deals with the situation where a supplier, who produces on order in fixed production cycles, provides information on the status of the coming production run. The retailer can use this information to gain insight into the lead-time process. A fixed order (s_vQ) strategy is presented, with a set of reorder points s_v depending on the time t until the first possible delivery, which is determined by the information of the supplier. A Markov model that analyzes a given (s_vQ) strategy is used to quantify the value of the information provided by the supplier. Some numerical examples show that the approach may lead to considerable cost savings compared to the traditional approach that uses only one single reorder point, based on a two-moments approximation. Using this numerical insight, the pros and cons of a more frequent exchange of information between retailers and suppliers can be balanced.     

Estimation of an indicator of the representativeness of survey response

Nonresponse is a major source of estimation error in sample surveys. The response rate is widely used to measure survey quality associated with nonresponse, but is inadequate as an indicator because of its limited relation with nonresponse bias. Schouten et al. (2009) proposed an alternative indicator, which they refer to as an indicator of representativeness or R-indicator. This indicator measures the variability of the probabilities of response for units in the population. This paper develops methods for the estimation of this R-indicator assuming that values of a set of auxiliary variables are observed for both respondents and nonrespondents. We propose bias adjustments to the point estimator proposed by Schouten et al. (2009) and demonstrate the effectiveness of this adjustment in a simulation study where it is shown that the method is valid, especially for smaller sample sizes. We also propose linearization variance estimators which avoid the need for computer-intensive replication methods and show good coverage in the simulation study even when models are not fully specified. The use of the proposed procedures is also illustrated in an application to two business surveys at Statistics Netherlands.     

Generating missing values for simulation purposes: a multivariate amputation procedure

Missing data form a ubiquitous problem in scientific research, especially since most statistical analyses require complete data. To evaluate the performance of methods dealing with missing data, researchers perform simulation studies. An important aspect of these studies is the generation of missing values in a simulated, complete data set: the amputation procedure. We investigated the methodological validity and statistical nature of both the current amputation practice and a newly developed and implemented multivariate amputation procedure. We found that the current way of practice may not be appropriate for the generation of intuitive and reliable missing data problems. The multivariate amputation procedure, on the other hand, generates reliable amputations and allows for a proper regulation of missing data problems. The procedure has additional features to generate any missing data scenario precisely as intended. Hence, the multivariate amputation procedure is an efficient method to accurately evaluate missing data methodology.     

PARAMETER ESTIMATION FOR LOW-ORDER AUTO-REGRESSIVE MODELS WITH MISSING VALUES

Longitudinal data analysis in epidemiological settings is complicated by large multiplicities of short time series and the occurrence of missing observations. To handle such difficulties Rosner & Muñoz (1988) developed a weighted non-linear least squares algorithm for estimating parameters for first-order autoregressive (AR1) processes with time-varying covariates. This method proved efficient when compared to complete case procedures. Here that work is extended by (1) introducing a different estimation procedure based on the EM algorithm, and (2) formulating estimation techniques for second-order autoregressive models. The second development is important because some of the intended areas of application (adult pulmonary function decline, childhood blood pressure) have autocorrelation functions which decay more slowly than the geometric rate imposed by an AR1 model. Simulation studies are used to compare the three methodologies (non-linear, EM based and complete case) with respect to bias, efficiency and coverage both in the presence and in the absence of time-varying covariates. Differing degrees and mechanisms of missingness are examined. Preliminary results indicate the non-linear approach to be the method of choice: it has high efficiency and is easily implemented. An illustrative example concerning pulmonary function decline in the Netherlands is analyzed using this method.     

Mental health and wellbeing of care leavers: Making sense of their perspectives

Despite considerable quantifiable data about the circumstances of care leavers in the United Kingdom, there is less qualitative data about how these circumstances are experienced. This article is underpinned by positioning theory, with a particular focus on the unfolding personal narratives of young care leavers in relation to their mental health and wellbeing and the role of a life‐skills programme in supporting them in this respect. The research illustrates that leaving care projects, such as the one in the current study, are more focused on employment and housing issues than on addressing the mental health and wellbeing needs of young people. Our analysis of interviews with young people illustrates the ambiguity of understandings of concepts such as “mental health” and “wellbeing,” and the complexity of responses to questioning around this area. This illustrates one of the major problems in evaluating the outputs and outcomes of such projects in terms of simplistic targets, where mental health and wellbeing are not clearly defined or understood by young people themselves. The current research provides a more complex picture. More research is needed that involves in‐depth and longitudinal assessment of specific mental health needs of care leavers and how they can be addressed successfully.