Voices of girls with disabilities in rural Iran

This paper investigates the interaction of gender, disability and education in rural Iran, which is a relatively unexplored field of research. The responses of 10 female students with disabilities from Isfahan indicated that the obstacles they faced included marginalization, difficulties in getting from home to school, difficulties within the school building itself, and discrimination by teachers, classmates and school authorities. The data collected for the study contain a wide range of conservative gendered discourses, and show how traditional gender beliefs interact with disability to aggravate the problems faced in education by young women with disabilities. It is hoped that the findings will raise awareness among policy-makers of the many formidable obstacles that make it difficult for young women with disabilities to achieve their full potential in education.     

Has the National Do Not Call Registry Helped or Hurt State-Level Response Rates?: A Time Series Analysis

By the end of the initial registration period on August 31,2003, the National Do Not Call Registry (DNC Registry) had registeredmore than 50 million telephone numbers. Approximately 18 monthslater that number had increased to more than 91 million. Theimpact of the DNC Registry on survey response rates, however,is largely unknown. Some researchers speculate that the registrycould make it easier to distinguish between telephone surveyinterviewers and telemarketers. Other researchers argue thata significant portion of DNC registrants may not make such distinctionsand would prefer instead to reduce all unsolicited calls frommarketers and interviewers alike. Case outcomes from nearly4.5 million telephone numbers called between January 1, 2002,and June 30, 2005, as part of the Behavioral Risk Factor SurveillanceSystem were analyzed. Using trend analyses and autoregressiveintegrated moving average (ARIMA) time series modeling, we assessedthe impact of the DNC Registry on state-level monthly responserates in 47 states. Our findings indicate that once pre-DNCRegistry trends in response rates and other potential covariatesare accounted for, the national Do Not Call rules have had nosignificant impact on state-level response rates in either apositive or negative direction.     

Partner Naming and Forgetting: Recall of Network Members

Network researchers must contend with recall, forgetting, alters whose names are not known, and other potential biases in estimating the size of personal (ego) networks. We use data from a longitudinal study of sexual and drug use ego networks. Results show 6% forgetting for 30-day sex partners, 18% for drug use partners, and 26% for close friends. Forgetting is decreased by behavioral specificity and salience. Forgetting increases with network size and time frame. In the domain of sex relationships, global estimates of network size, at least over a period of 30 days, are equivalent to estimates from partner naming 92% of the time if anonymous partners are accounted for.     

The Impact of Organizational Change on Employee Turnover Intention: Does Stress Play a Mediating Role?

This study examined the relationship between change interventions and employee turnover intention to see if change interventions lead to increased employee turnover intention. Moreover, the mediating role of employee stress was tested. Data were collected from 162 respondents working at various administrative positions in a large public organization. The results indicate that employee turnover intention is positively correlated to human process, techno structural, human resources, and strategic interventions. Limitations and direction for future research are provided.     

A Hybrid Methodology for Modeling Risk of Adverse Events in Complex Health‐Care Settings

In spite of increased attention to quality and efforts to provide safe medical care, adverse events (AEs) are still frequent in clinical practice. Reports from various sources indicate that a substantial number of hospitalized patients suffer treatment‐caused injuries while in the hospital. While risk cannot be entirely eliminated from health‐care activities, an important goal is to develop effective and durable mitigation strategies to render the system “safer.” In order to do this, though, we must develop models that comprehensively and realistically characterize the risk. In the health‐care domain, this can be extremely challenging due to the wide variability in the way that health‐care processes and interventions are executed and also due to the dynamic nature of risk in this particular domain. In this study, we have developed a generic methodology for evaluating dynamic changes in AE risk in acute care hospitals as a function of organizational and nonorganizational factors, using a combination of modeling formalisms. First, a system dynamics (SD) framework is used to demonstrate how organizational‐level and policy‐level contributions to risk evolve over time, and how policies and decisions may affect the general system‐level contribution to AE risk. It also captures the feedback of organizational factors and decisions over time and the nonlinearities in these feedback effects. SD is a popular approach to understanding the behavior of complex social and economic systems. It is a simulation‐based, differential equation modeling tool that is widely used in situations where the formal model is complex and an analytical solution is very difficult to obtain. Second, a Bayesian belief network (BBN) framework is used to represent patient‐level factors and also physician‐level decisions and factors in the management of an individual patient, which contribute to the risk of hospital‐acquired AE. BBNs are networks of probabilities that can capture probabilistic relations between variables and contain historical information about their relationship, and are powerful tools for modeling causes and effects in many domains. The model is intended to support hospital decisions with regard to staffing, length of stay, and investments in safety, which evolve dynamically over time. The methodology has been applied in modeling the two types of common AEs: pressure ulcers and vascular‐catheter‐associated infection, and the models have been validated with eight years of clinical data and use of expert opinion.     

THREE-WAY STRATIFICATION SAMPLING DESIGN WHEN ONE OF THE STRATIFYING VARIABLES IS TIME

Bryant, Hartley & Jessen (1960) presented a two‐way stratification sampling design when the sample size n is less than the number of strata. Their design was extended to a three‐way stratification case by Chaudhary & Kumar (1988) , but this design does not take into account serial correlation, which might be present as a result of the presence of a time variable. In this paper, a new sampling procedure is presented for three‐way stratification when one of the stratifying variables is time. The purpose of such a design is to take into account serial correlation. The variance of the unweighted estimator of the population mean with respect to a super population model is used as the basis for comparison. Simulation results show that the suggested design is more efficient than the Chaudhary & Kumar (1988) design.     

The convolution theorem for estimating linear functionals in indirect nonparametric regression models

Nonparametric regression—directly or indirectly observed—is one of the important statistical models. On one hand it contains two infinite dimensional parameters (the regression function and the error density), and on the other it is of rather simple structure. Therefore, it may serve as an interesting paradigm for illustrating or developing abstract statistical theory for non-Euclidean parameters. In this paper estimation of a linear functional of the indirectly observed regression function is considered, when a deterministic design is used. It should be noted that any Fourier coefficient of an expansion of the regression function in an orthonormal basis is such a functional. Because the design is deterministic the observables are independent but not identically distributed. Local asymptotic normality is established and applied to prove Hájek's convolution theorem for this functional. Pertinent references are Beran [1977. Robust location estimates. Ann. Statist. 5, 431–444] and McNeney and Wellner [2000. Application of convolution theorems in semiparametric models with non-i.i.d. data. J. Statist. Plann. Inference 91, 441–480]. For purposes explained above, however, the paper is kept self-contained and full proofs are provided.     

Multi‐Product Quality Competition: Impact of Resource Constraints

We study a multi‐product firm with limited capacity where the products are vertically (quality) differentiated and the customer base is heterogeneous in their valuation of quality. While the demand structure creates opportunities through proliferation, the firm should avoid cannibalization between its own products. Moreover, the oligopolistic market structure puts competitive pressure and limits the firm's market share. On the other hand, the firm has limited resources that cause a supply‐side fight for adequate and profitable production. We explicitly characterize the conditions where each force dominates. Our focus is on understanding how capacity constraints and competition affect a firm's product‐mix decisions. We find that considering capacity constraints could significantly change traditional insights (that ignore capacity) related to product‐line design and the role of competition therein. In particular, we show that when the resources are limited, the firm should offer only the product that has the highest margin per unit capacity. We find that this product could be the diametrically opposite product suggested by the existing literature. In addition, we show that for intermediate capacity levels, whereas the margin per unit capacity effect dominates in a less competitive market, proliferation and cannibalization effects dominate in a more competitive market.     

Annual mortality rates and excess deaths of children under five in Iraq, 1991-98

Data from two parallel household surveys conducted in Iraq by UNICEF in 1999 show that under-5 mortality declined steadily from 1974 to 1990, reaching about 63 per 1,000 live births in the period 1986-90. It then rose dramatically to 118 per 1,000 in 1991, the year of the Gulf War. The number of 'excess' under-5 deaths (i.e., the number in excess of the number predicted from past trends) in Iraq between 1991 and 1998 was calculated assuming that, instead of the rates measured by the 1999 survey for this period, either (a) average mortality rates for the period 1986-90 had been maintained, or (b) mortality had continued to decline at the rate observed between 1974 and 1990. According to these calculations, the estimated number of excess deaths resulting from the Gulf War and its aftermath up to 1998 was between 400,000 (assumption a) and 500,000 (assumption b).