Guaranteed Conditional Performance of Control Charts via Bootstrap Methods

To use control charts in practice, the in‐control state usually has to be estimated. This estimation has a detrimental effect on the performance of control charts, which is often measured by the false alarm probability or the average run length. We suggest an adjustment of the monitoring schemes to overcome these problems. It guarantees, with a certain probability, a conditional performance given the estimated in‐control state. The suggested method is based on bootstrapping the data used to estimate the in‐control state. The method applies to different types of control charts, and also works with charts based on regression models. If a non‐parametric bootstrap is used, the method is robust to model errors. We show large sample properties of the adjustment. The usefulness of our approach is demonstrated through simulation studies.     

Some Results on Comparing the Quantiles of Dependent Groups

Recently, Lombard derived an extension of the Doksum–Sievers shift function to dependent groups. This article suggests using a particular numerical method for determining the critical value, reports on the ability of the method to control the probability of a Type I error when sample sizes are small, and it provides comparisons with methods aimed at comparing deciles. It is found that for continuous distributions, Lombard's method performs well and in particular has high power relative to the other two methods considered. But when tied values can occur, now it can have relatively poor power; a method based on the Harrell-Davis estimator is found to give more satisfactory results.     

The additive hazard estimator is consistent for continuous-time marginal structural models

Lifetime Data Analysis - Marginal structural models (MSMs) allow for causal analysis of longitudinal data. The standard MSM is based on discrete time models, but the continuous-time MSM is a...     

Daily transformational leadership and employee job crafting: The role of promotion focus

Transformational leaders are expected to challenge their followers to take greater ownership of their work, allowing the leader to align followers with tasks that enhance their performance. In the present study, we hypothesize that transformational leadership is positively related to followers' job-crafting behaviour – proactive behaviour aimed at optimizing job demands and job resources. Moreover, we argue that followers' promotion focus (i.e. being driven by growth and development needs) positively moderates this relationship. Data were collected from 107 employees from Norwegian knowledge-based organizations (response?=?93.2%). Participants responded to a general questionnaire and five daily diary questionnaires (total N?=?535 occasions). The results of multilevel analyses revealed partial support for our hypotheses. Followers' day-level perception of their leader's transformational behaviour was positively related to followers' day-level job crafting in the form of increasing structural and social resources. Moreover, daily transformational leadership was particularly beneficial for job crafting when followers scored high (vs. low) on the trait promotion focus. We conclude that transformational leaders can encourage their followers' use of job crafting, and that employees' promotion focus facilitates this effect.     

When Cooperation is the Norm of Appropriateness: How Does CEO Cooperative Behaviour Affect Organizational Performance?

The current study has tested the prediction that CEO cooperative behaviour has an impact upon organizational performance. This is a fundamental organizational issue that is in clear need of illumination through studies of practice. We pursued the issue through a study of leadership in organizations located in the Norwegian socio‐cultural context in which cooperation has been, and still is, a norm of appropriateness. The study provided empirical evidence of a positive relationship between CEO cooperative behaviour and organizational performance. This relationship appeared to be stronger in organizational contexts in which CEOs are perceived to have legitimacy and managerial discretion, and it appeared to be weaker in organizations in which individual performance pay is the rule. Since some organizational characteristics have the potential to enhance the impact of CEO cooperative behaviour while other characteristics might inhibit this impact, leaders have to consider carefully how to develop and maintain individual and organizational capabilities that are needed to act appropriately.     

Latin American Productivity from 1990 to 1998 in the Mexican Journal of Psychology

Published uninterruptedly since 1984, the Mexican Journal of Psychology (MJP) has been recognized as one of the most important periodicals in Spanish-language psychology. After coping with financial impediments and a lack of scientific contributions, the significance of the MJP emerged. The journal remains vital in the development of Latin American psychology. It is today recognized as having the highest impact of all Latin American psychology journals as well as having the second highest impact of all psychology journals in the Spanish language. The goal of the present study was to review the profiles of the MJP from 1990 to 1998 by using a bibliometric classification procedure. Four indicators were employed in the present analysis of the articles including measurement techniques, methodology, field of psychology, and main results.     

Structure and adequacy of human service facilities: challenges for nonprofit managers

Findings from a statewide survey of nonprofit human service organizations in Illinois show great diversity in access to and use of facilities. Large proportions have facility-related problems that will require substantial investments beyond the financial capacity of the organizations themselves. The findings also point to major shortcomings in attention to or knowledge about facility-related problems among managers of these organizations. The findings have important policy implications for nonprofit managers, as well as for public and private funders and policy makers.     

Leaving the Nordic Path? The Changing Role of Danish Trade Unions in the Welfare Reform Process

For a long period, Denmark has been labeled a ‘model country’ with a comprehensive welfare state and a successful model of corporatist policy‐making. Danish unions are considered amongst the strongest in the world, and they have for a long time been a distinct part of the political system, and as social partners, they were strongly integrated into decision‐making processes. The analysis of the Danish welfare and labour market policy during the last two decades documents a profound change in the arrangement and in the status of the social partners (especially unions) in the Danish political system. The results show that two important pillars of the Danish model – the social partner basis and the collective trust in partnership – are eroding. Unions are no longer part of the law‐making process and, since 2007, they are formally excluded from the organization of the decision‐making process. Recent developments point at weaker unions that operate more as lobbyists instead of being strong corporatist institutions or part of the decision‐making process. The results of the study are thought‐provoking and the basis for a revised thinking of the Danish and the Nordic model.     

Income effects of divorce in families with dependent children

The Norwegian post-divorce transfer scheme for families with children guarantees minimum maintenance payments from the non-custodial to the custodial parent. We studied the economic effects of divorce in such families. When the mother has custody, she falls behind before maintenance payments. After adding these, the outcomes at the median are very similar for both parents, contrasting studies from other countries, but the risk of a drop in equivalized income is large.     

Robust ANCOVA: Some Small-sample Results when there are Multiple Groups and Multiple Covariates

Numerous methods have been proposed for dealing with the serious practical problems associated with the conventional analysis of covariance method, with an emphasis on comparing two groups when there is a single covariate. Recently, Wilcox (2005a: section 11.8.2) outlined a method for handling multiple covariates that allows nonlinearity and heteroscedasticity. The method is readily extended to multiple groups, but nothing is known about its small-sample properties. This paper compares three variations of the method, each method based on one of three measures of location: means, medians and 20% trimmed means. The methods based on a 20% trimmed mean or median are found to avoid Type I error probabilities well above the nominal level, but the method based on medians can be too conservative in various situations; using a 20% trimmed mean gave the best results in terms of Type I errors. The methods are based in part on a running interval smoother approximation of the regression surface. Included are comments on required sample sizes that are relevant to the so-called curse of dimensionality.