Development of Parenting Skills in Individuals with an Intellectual Impairment: an epigenetic explanation

Current changes in legislation in the United States support the rights of individuals with an intellectual impairment to marry and have children. Current societal views, however, are heavily influenced by our history of viewing these individuals as inadequate parents. This historical view is based upon the assumption that those with intellectual impairments are genetically inferior. Changing views of development, however, suggest that the issue of how individuals with intellectual impairments develop is somewhat more complex. The epigenetic model is one that proposes that development is the result of the complex transaction between the individual and the environment. This paper applies this model to persons with an intellectual impairment to better understand the parenting skills they display. It is argued that by intervening and changing developmental pathways, the development of parenting skills of those with intellectual impairments can be facilitated.     

Media Publicity and the Voluntary Sector: The Case of Nonprofit Organizations in New York City

Media publicity is an important resource for contemporary voluntary associations, but very little is actually known about the resources and organizational characteristics that are most important for getting media attention. To address this question, we collected and analyzed data on the organizational attributes and news publicity of 739 nonprofit organizations in New York City. We find that an organization's income, paid staff, membership size, and library resources are significantly related to getting media publicity, whereas the number of chapter affiliations is inversely related to publicity. Association type is also a significant factor that influences an organization's ability to get publicity. We discuss the implications that these findings have for current debates about advocacy and civic engagement in the nonprofit sector.     

Rehabilitating the Criminality of Immigrants Under Section 19 of the Canadian Immigration Act1

Immigration has historically been associated with moral entrepreneurship and xenophobia. In periods of high unemployment and global dislocation, immigrants easily become the targets of political commentators who complain of their criminality, morals, demand on public services, and competition for scarce employment. In this exercise, looking at the recidivism of immigrants who come to Canada with a previous, foreign criminal history, quite a different picture emerges. Among this random sample (N=204), 97.5 percent of immigrants granted a rehabilitation waiver under the provisions of the Canadian Immigration Act were not re‐arrested in Canada within a period of about 3.5 years after their landing was approved by the Minister. Of those who were arrested, most of the delinquency was manageable and, in fact, resulted in either an acquittal, diversion or lower‐range sanctions. This is not the kind of imagery complained of by the tabloids or critics in the body politic. It behooves us, then, to exercise care in discussing crime and immigration, as it is a subject easily prone to the creation of “moral panics” and resulting repressive legislation against persons of color.     

WAGE DISCRIMINATION ACROSS ETHNIC GROUPS: EVIDENCE FROM ISRAEL

We investigate wage differentials between ethnic groups in Israel, proposing a new methodology and an illustration based on the latest Israeli census. By using separate wage equations for the various occupations, our methodology allows us to decompose the wage differential into three components: one reflecting human capital differences; one reflecting wage discrimination; and a third indicating occupational segregation. We find that 70 percent of the wage gap is due to segregation, 26 percent to wage discrimination and only 4 percent to human capital differences. Evidence is also found for the existence of duality in the Israeli labor market.     

Design optimization using ANOVA

This paper describes the design optimization of a robot sensor used for locating 3-D objects employing the Taguchi method in a computer simulation scenario. The location information from the sensor is to be utilized to control the movements of an industrial robot in a 'pick-and-place' or assembly operation. The Taguchi method, which is based on the Analysis-of-Variance (ANOVA) approach, is utilized to improve the performance of the sensor over a wider operating range. A review of the Taguchi method is presented along with step-by-step implementation details to identify and optimize the design parameters of the sensor. The method allows us to gauge the impact of various interactions present in the sensor system exclusively and permits us to single out those factors that have a dominant influence on the overall performance of the sensor. The investigation suggests that the Taguchi method is a more structured and efficient approach for achieving a robust design compared with the classical full factorial design approach.     

Führung durch Selbstführung

This paper outlines the conceptual bases, strategies, and psychological attributes of leadership by self-leadership. In addition, relations to other theories of leadership are drawn. Dimensions and correlates of self-leadership competence are described and discussed. Various approaches for developing self-leadership competence are discussed as well.     

Empirical likelihood confidence intervals for the mean of a population containing many zero values

If a population contains many zero values and the sample size is not very large, the traditional normal approximation‐based confidence intervals for the population mean may have poor coverage probabilities. This problem is substantially reduced by constructing parametric likelihood ratio intervals when an appropriate mixture model can be found. In the context of survey sampling, however, there is a general preference for making minimal assumptions about the population under study. The authors have therefore investigated the coverage properties of nonparametric empirical likelihood confidence intervals for the population mean. They show that under a variety of hypothetical populations, these intervals often outperformed parametric likelihood intervals by having more balanced coverage rates and larger lower bounds. The authors illustrate their methodology using data from the Canadian Labour Force Survey for the year 2000.     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.