Translating cross-lagged effects into incidence rates and risk ratios: The case of psychosocial safety climate and depression

Longitudinal studies are the gold standard of empirical work and stress research whenever experiments are not plausible. Frequently, scales are used to assess risk factors and their consequences, and cross-lagged effects are estimated to determine possible risks. Methods to translate cross-lagged effects into risk ratios to facilitate risk assessment do not yet exist, which creates a divide between psychological and epidemiological work stress research. The aim of the present paper is to demonstrate how cross-lagged effects can be used to assess the risk ratio of different levels of psychosocial safety climate (PSC) in organisations, an important psychosocial risk for the development of depression. We used available longitudinal evidence from the Australian Workplace Barometer (N?=?1905) to estimate cross-lagged effects of PSC on depression. We applied continuous time modelling to obtain time-scalable cross effects. These were further investigated in a 4-year Monte Carlo simulation, which translated them into 4-year incident rates. Incident rates were determined by relying on clinically relevant 2-year periods of depression. We suggest a critical value of PSC?=?26 (corresponding to ?1.4 SD), which is indicative of more than 100% increased incidents of persistent depressive disorder in 4-year periods compared to average levels of PSC across 4 years.     

Toward a sociology of global comparative placemaking

I call for a globally informed sociology of comparative placemaking that integrates historical and contemporary processes and includes the ephemeral, institutional, and personal. By placemaking, I am referring to the explicit or tacit cooperation among people to create, maintain, and give meaning to places in space through bodily occupation given differential resources and constraints. I review select place, space, and community-based literature about urban, Black, migrant, LGBTQ, and international populations to think about how we can build upon and integrate multiple theoretical, methodological, and epistemological insights to form an explicit placemaking research agenda. A US focus on neighborhoods contrasts with a comparative examination of global urban networks, social polarization, and transformation of the built environment in the interdisciplinary field of global urban studies (Ren, 2018). I argue for a placemaking research agenda that bridges insight from US Urban Sociology with Global Urban Studies to consider how various structures and actors constrain and facilitate place projects. With a globally reaching and comparatively informed sociology of placemaking, we can illuminate our multi-structured story of place and agency in context. We can answer questions about how and why we co-create and are simultaneously disciplined by the process of creation.     

Comparison of labour and birth outcomes between nulliparous women who used epidural analgesia in labour and those who did not: A prospective cohort study

ObjectiveTo compare labour and birth outcomes between nulliparous women who used versus did not use intrapartum epidural analgesia.DesignProspective cohort study.SettingTwo maternity hospitals in Ireland.PopulationA total of 1221 nulliparous women who gave birth vaginally or by emergency caesarean section.MethodsMultinomial logistic regression was used to analyse categorical outcomes, with results presented as ratios of relative risks (RRR). For dichotomous outcomes we used logistic regression, with results presented as odds ratios (OR).Main outcome measuresMode of birth, IV syntocinon use, pyrexia (≥38 °C), antibiotic treatment, first stage labour ≥10 h, second stage labour ≥2 h, blood loss (≥500 mls, ≥1000 mls), perineal trauma. Neonatal outcomes included Apgar score ≥7 at 1 min and 5 min, admission to neonatal intensive care unit, and infant feeding method.ResultsWomen using EA were more likely to require a vacuum-assisted birth (RRR 3.35, p < 0.01) or forceps-assisted birth (RRR 11.69, p < 0.01). Exposure to EA was associated with significantly greater risk of ≥10 h first (OR 6.72, p = 0.01) and ≥2 h second (OR 2.25, p < 0.01) stage labour, increased likelihood of receiving IV syntocinon (OR 9.38, p < 0.01), antibiotics (OR 2.97, p < 0.01) and a greater probability of pyrexia (OR 10.26, p < 0.01). Women who used EA were half as likely to be breastfeeding at three months postpartum (OR 0.53, p < 0.01). No differences were observed between groups in neonatal outcomes.ConclusionsOur data shows significant associations between EA use and several intrapartum outcomes.     

Professional blinders? The novel as an eye-opener in organizational analysis

ABSTRACT

Scholarly textbooks often follow a logic where suitable empirical cases are selected to illustrate the theoretical and analytical points that we as scholars want to make. But what would happen if we would do the opposite: build a textbook on a novel written by a novelist for such purpose and let the theories explain the actions and emotions of fictional characters? In this article, we share and reflect upon our experiences of co-authoring a textbook in organization theory together with a professional novelist. We argue that the novel can function as an eye-opener in organizational analysis, forcing us to look beyond more static and rationalistic perspectives on organizations as well as the stereotypes of such. We build and relate our experiences to the growing literature about using fiction in scholarly work and discuss the potential of such genre-bending work when we bring in flesh and blood into the analyses.     

Lognormal Approximations of Fault Tree Uncertainty Distributions

Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed‐form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling‐based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed‐form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks’s method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models.     

Analyzing multiple vector autoregressions through matrix-variate normal distribution with two covariance matrices

Abstract

This article proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two covariance matrices allow the extension of MtAR to a structural MtAR analysis. The proposed MtAR can also incorporate different lag orders across VAR systems that provide more flexibility to the model. The estimation results from a simulation study and an empirical study on macroeconomic application show favorable performance of our proposed models and method.     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.     

投敌叛变罪若干疑难问题研讨

投敌叛变罪作为危害国家安全的一种重罪,刑法学界的研究状况相对较为薄弱,为此应立足于刑法规定,并紧密结合司法实践,对投敌叛变罪的本质属性、客观表现、罪过形式、罪数形态、犯罪形态及其死刑适用等几个重大疑难问题进行较为深入的研究。     

我校医学影像专业实施素质教育的实践与探索

三峡大学医学院开办医学影像专业有 16年历史 ,经历了从专科向本科转型过度。在素质教育和创新意识培养方面经过了多年的探索实践。大专层次的教育为社会培养了一批临床应用型专业人才 ,缓解了市场需求的压力 ,但部分学生客观上存在着知识面较窄小 ,缺乏后劲的问题。实施本科教育全面提高学生的综合素质需要在多方面下工夫 :转变教育思想 ,更新教育观念 ;转变培养模式 ;优化组合构建新的课程体系 ;强化科研 ,以科研促教学 ;通才教育与专才教育并举。探索本科生素质教育 6年 ,取得了可喜成绩 ,积累了一些经验     

GMM tests for the Katz family of distributions

Generalized method of moments (GMM) is used to develop tests for discriminating discrete distributions among the two-parameter family of Katz distributions. Relationships involving moments are exploited to obtain identifying and over-identifying restrictions. The asymptotic relative efficiencies of tests based on GMM are analyzed using the local power approach and the approximate Bahadur efficiency. The paper also gives results of Monte Carlo experiments designed to check the validity of the theoretical findings and to shed light on the small sample properties of the proposed tests. Extensions of the results to compound Poisson alternative hypotheses are discussed.