Evaluating Faculty Publications in Accounting Ph.D. Programs: The Author Affiliation Index as an Alternative

We propose a new model, the Author Affiliation Index (AAI), for examining journal quality, explain how the AAI is calculated, and report the resulting scores for 35 accounting and accounting-related journals. Next, we compare AAI journal rankings with those from other published studies and examine the correlations between them to show how the AAI can be used to evaluate relatively new journals, such as Accounting and the Public Interest, that are not included in extant ranking lists. By explaining its flexibility, we demonstrate that the AAI model can serve as a valuable tool for measuring journal quality and for meeting AACSB accreditation requirements for faculty groups as well as individual faculty. The AAI is based on the principle that as the percentage of authors in a journal who are accounting faculty at doctoral-granting institutions increases, the perceived value of that journal in terms of quality to Ph.D.-granting accounting programs also increases. Although our illustrations focus on the construction of this measure for use by Ph.D.-granting institutions, we describe how it can be adapted for use by other faculty groups.

Job Burnout in Public Accounting: Understanding Gender Differences

Job burnout is linked to job outcomes in public accounting professionals (Fogarty et al., 2000; Jones et al., 2010; Jones et al., 2012). Although women and men have entered the profession in relatively equal numbers, there is a significantly lower percentage of women partners (AICPA, 2011). Extant research has not sufficiently explored how burnout may affect the genders distinctly and whether these differences may lend insight as to women’s choices to exit. A large participant group with a similar proportion of women (n=836) and men (n=845) allowed examination of the burnout construct on a more profound level than extant studies. The three dimensions of job burnout in women and men public accountants were analyzed, not only in total, but also by functional area and position level. Overall findings are that women report higher levels of reduced personal accomplishment and men report higher levels of depersonalization. In light of these findings, suggestions are made for firm and individual actions that may mitigate the intensity of burnout experienced by both women and men public accountants.

Role Stress and Job Outcomes in Public Accounting: Have the Gender Experiences Converged?

Using data collected from professionals in a large U.S. national public accounting firm, we explored gender differences in perceived levels of role stress and job outcomes as well as the effects of a healthy lifestyle as a coping mechanism for role stress, burnout and related job outcomes. Our large sample size (1,681) and equal participation by women (49.7%) and men (50.3%) allowed us to analyze the causal relationships of these variables using a previously tested multi-disciplinary research model (Jones, Norman, & Wier, 2010). We found that women and men perceive similar levels of role stress as defined by role ambiguity and role overload, and that women perceive less role conflict. Men and women perceive similar levels of job satisfaction and job performance. Contrary to earlier studies, women do not report higher levels of turnover intentions. Results show that efforts of the public accounting firms over the past decade may be somewhat successful in reducing the levels of role stress and turnover intentions among women. Another plausible explanation could be that an expansionist theory of gender, work and family (Barnett & Hyde, 2001) may now be responsible for improved well-being of females to the point where the genders have converged in their experience of role stress and job outcomes in public accounting.

Accounting for Fetal Death: Vital Statistics and the Medicalization of Pregnancy in the United States

Recent reports by the Centers for Disease Control and Prevention have decried the high rate of fetal mortality in the contemporary United States. Much of the data about fetal and infant deaths, as well as other poor pregnancy outcomes, are tabulated and tracked through vital statistics. In this article, I demonstrate how notions of fetal death became increasingly tied to the surveillance of maternal bodies through the tabulating and tracking of vital statistics in the middle part of the twentieth century. Using a historical analysis of the revisions to the United States Standard Certificate of Live Birth, and the United States Standard Report of Fetal Death, I examine how the categories of analysis utilized in these documents becomes integrally linked to contemporary ideas about fetal and perinatal death, gestational age, and prematurity. While it is evident that there are relationships between maternal behavior and birth outcomes, in this article I interrogate the ways in which the surveillance of maternal bodies through vital statistics has naturalized these relationships. Copyright 2013 Elsevier Ltd. All rights reserved.

Distinctive Convergence in Australian Floral Colours Seen Through the Eyes of Australian Birds

We used a colour-space model of avian vision to assess whether a distinctive bird pollination syndrome exists for floral colour among Australian angiosperms. We also used a novel phylogenetically based method to assess whether such a syndrome represents a significant degree of convergent evolution. About half of the 80 species in our sample that attract nectarivorous birds had floral colours in a small, isolated region of colour space characterized by an emphasis on long-wavelength reflection. The distinctiveness of this 'red arm' region was much greater when colours were modelled for violet-sensitive (VS) avian vision than for the ultraviolet-sensitive visual system. Honeyeaters (Meliphagidae) are the dominant avian nectarivores in Australia and have VS vision. Ancestral state reconstructions suggest that 31 lineages evolved into the red arm region, whereas simulations indicate that an average of five or six lineages and a maximum of 22 are likely to have entered in the absence of selection. Thus, significant evolutionary convergence on a distinctive floral colour syndrome for bird pollination has occurred in Australia, although only a subset of bird-pollinated taxa belongs to this syndrome. The visual system of honeyeaters has been the apparent driver of this convergence.

MULTIPLE DISEASES IN CARRIER PROBABILITY ESTIMATION: ACCOUNTING FOR SURVIVING ALL CANCERS OTHER THAN BREAST AND OVARY IN BRCAPRO

Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 familes from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO’s concordance index from 0.758 to 0.762 (p = 0.046), improves its positive predictive value from 35% to 39% (p < 10−6) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability < 10%. Copyright c 2000 John Wiley & Sons, Ltd.

Squared Extrapolation Methods (SQUAREM): A New Class of Simple and Efficient Numerical Schemes for Accelerating the Convergence of the EM Algorithm

We derive a new class of iterative schemes for accelerating the convergence of the EM algorithm, by exploiting the connection between fixed point iterations and extrapolation methods. First, we present a general formulation of one-step iterative schemes, which are obtained by cycling with the extrapolation methods. We, then square the one-step schemes to obtain the new class of methods, which we call SQUAREM. Squaring a one-step iterative scheme is simply applying it twice within each cycle of the extrapolation method. Here we focus on the first order or rank-one extrapolation methods for two reasons, (1) simplicity, and (2) computational efficiency. In particular, we study two first order extrapolation methods, the reduced rank extrapolation (RRE1) and minimal polynomial extrapolation (MPE1). The convergence of the new schemes, both one-step and squared, is non-monotonic with respect to the residual norm. The first order one-step and SQUAREM schemes are linearly convergent, like the EM algorithm but they have a faster rate of convergence. We demonstrate, through five different examples, the effectiveness of the first order SQUAREM schemes, SqRRE1 and SqMPE1, in accelerating the EM algorithm. The SQUAREM schemes are also shown to be vastly superior to their one-step counterparts, RRE1 and MPE1, in terms of computational efficiency. The proposed extrapolation schemes can fail due to the numerical problems of stagnation and near breakdown. We have developed a new hybrid iterative scheme that combines the RRE1 and MPE1 schemes in such a manner that it overcomes both stagnation and near breakdown. The squared first order hybrid scheme, SqHyb1, emerges as the iterative scheme of choice based on our numerical experiments. It combines the fast convergence of the SqMPE1, while avoiding near breakdowns, with the stability of SqRRE1, while avoiding stagnations. The SQUAREM methods can be incorporated very easily into an existing EM algorithm. They only require the basic EM step for their implementation and do not require any other auxiliary quantities such as the complete data log likelihood, and its gradient or hessian. They are an attractive option in problems with a very large number of parameters, and in problems where the statistical model is complex, the EM algorithm is slow and each EM step is computationally demanding.