The history and metamorphosis of the National Registry of Health Care Providers in Clinical Social Work

This paper traces the history and metamorphosis of the National Registry of Health Care Providers in Clinical social Work. It was created in 1975 to credential qualified clinical social workers, and to identify them through a published directory. In 1987 it became the National Institute for Clinical Social Work Advancement. Its objectives and purposes moved from credentialling to advancing the speciality of clinical social work through research, education and marketing.     

The Turkish alevis

The Alevi comprise a specific ethnic group in Turkey of especial interest. In presenting a case study of an Alevi community in Ankara that arose out of internal urban migration, the present paper delineates the way in which the Alevis have moved away from constituting a counterculture during the period of the Ottoman period to comprising a working class subculture of great organizational and political potential in contemporary Turkey. The paper also describes the ethnic markedness of the Alevi community and the problems that arise out of this markedness.     

Does Cultural Difference Affect Investment–Cash Flow Sensitivity? Evidence from OECD Countries

We investigate the influence of national culture on corporate investment–cash flow sensitivity. We conjecture that national culture shapes managerial perceptions of information asymmetry and agency problems, thus impacting the investment–cash flow relationship. We document empirical evidence in support of our claim. By linking the investment–cash flow sensitivity to cultural differences, our findings show that, while collectivism has an attenuating influence, uncertainty avoidance, power distance and masculinity have a reinforcing effect on the relationship between cash flow and investment. Our results hold for a sample of 205,268 firm‐years across 24 OECD countries between 1990 and 2017, and are robust after accounting for alternative statistical approaches, sample compositions and measures of cultural dimensions, along with controls for institutional and governmental factors. In addition, by decomposing cash flow into uses and sources of funds in a dynamic multi‐equation model, where firms make financing and investment decisions jointly subject to the constraint that sources must equal uses of cash, we find that national culture shapes how firms react to changes in cash flow.     

New Venture Survival: A Review and Extension

This paper provides an evaluative overview of the new venture survival literature. Since Stinchcombe's primary attempt to explain the mortality rates of new ventures, different research fields, including entrepreneurship, management and sociology, have devoted considerable attention to the antecedents of new venture survival. Despite this lively research commitment, a comprehensive review of the literature on new venture survival – as one of the most essential performance measures for new ventures – is missing. Covering 54 years of research, this paper provides an overview of the factors affecting new venture survival and highlights important methodological aspects in this research field. The review concludes by discussing opportunities for future research.     

From Intended to Actual and Beyond: A Cross‐Disciplinary View of (Human Resource Management) Implementation

Despite increasing interest in human resource management (HRM) implementation as an explanation for the association between HRM and firm performance, considerable confusion remains about what implementation means. In order to develop conceptual definitions of HRM implementation and implementation effectiveness, this study builds on three different literatures outside the HRM field (strategy, innovation, and change management), which have addressed this topic extensively. As a result, implementation is characterized as a dynamic process, involving the interaction among multiple actors, starting with the adoption of a new practice and ending with its routinization. This is distinguished from implementation effectiveness as an outcome of that process. The study helps to achieve construct clarity, hence providing a more solid basis for future research and allowing for a better consolidation of findings. The authors also develop an agenda for further research by reviewing a number of theoretical and methodological approaches that have been used in implementation research across fields, including HRM. Overall, the study aims to establish implementation research as a highly relevant academic and practical quest not only in HRM, but also in other management literatures.     

Selection bias for treatments with positive Phase 2 results

In drug development, treatments are most often selected at Phase 2 for further development when an initial trial of a new treatment produces a result that is considered positive. This selection due to a positive result means, however, that an estimator of the treatment effect, which does not take account of the selection is likely to over‐estimate the true treatment effect (ie, will be biased). This bias can be large and researchers may face a disappointingly lower estimated treatment effect in further trials. In this paper, we review a number of methods that have been proposed to correct for this bias and introduce three new methods. We present results from applying the various methods to two examples and consider extensions of the examples. We assess the methods with respect to bias of estimation of the treatment effect and compare the probabilities that a bias‐corrected treatment effect estimate will exceed a decision threshold. Following previous work, we also compare average power for the situation where a Phase 3 trial is launched given that the bias‐corrected observed Phase 2 treatment effect exceeds a launch threshold. Finally, we discuss our findings and potential application of the bias correction methods.     

Leveraging historical data into oncology development programs: Two case studies of phase 2 Bayesian augmented control trial designs

Leveraging historical data into the design and analysis of phase 2 randomized controlled trials can improve efficiency of drug development programs. Such approaches can reduce sample size without loss of power. Potential issues arise when the current control arm is inconsistent with historical data, which may lead to biased estimates of treatment efficacy, loss of power, or inflated type 1 error. Consideration as to how to borrow historical information is important, and in particular, adjustment for prognostic factors should be considered. This paper will illustrate two motivating case studies of oncology Bayesian augmented control (BAC) trials. In the first example, a glioblastoma study, an informative prior was used for the control arm hazard rate. Sample size savings were 15% to 20% by using a BAC design. In the second example, a pancreatic cancer study, a hierarchical model borrowing method was used, which enabled the extent of borrowing to be determined by consistency of observed study data with historical studies. Supporting Bayesian analyses also adjusted for prognostic factors. Incorporating historical data via Bayesian trial design can provide sample size savings, reduce study duration, and enable a more scientific approach to development of novel therapies by avoiding excess recruitment to a control arm. Various sensitivity analyses are necessary to interpret results. Current industry efforts for data transparency have meaningful implications for access to patient‐level historical data, which, while not critical, is helpful to adjust for potential imbalances in prognostic factors.     

Label‐ and Level‐Invariant Graphical Log‐Linear Models

We introduce two types of graphical log‐linear models: label‐ and level‐invariant models for triangle‐free graphs. These models generalise symmetry concepts in graphical log‐linear models and provide a tool with which to model symmetry in the discrete case. A label‐invariant model is category‐invariant and is preserved after permuting some of the vertices according to transformations that maintain the graph, whereas a level‐invariant model equates expected frequencies according to a given set of permutations. These new models can both be seen as instances of a new type of graphical log‐linear model termed the restricted graphical log‐linear model, or RGLL, in which equality restrictions on subsets of main effects and first‐order interactions are imposed. Their likelihood equations and graphical representation can be obtained from those derived for the RGLL models.