Peer Victimization,Self‐esteem,and Ego Resilience Types in Adolescents: A Prospective Analysis of Person‐context Interactions

This study examined bidirectional, longitudinal associations between peer victimisation and self‐esteem in adolescents, and tested for moderator effects of undercontrolling, overcontrolling, and ego‐resilient personality types in these associations. Data were used from 774 adolescents ages 11–16 years who participated in a three‐wave (i.e., 2005, 2006, and 2007) longitudinal study. Structural equation modelling analyses in Mplus demonstrated that, controlling for earlier levels of self‐esteem, self‐reported peer victimization was associated with lower self‐esteem across one‐year time intervals. Vice versa, however, low self‐esteem was not predictive of subsequent self‐reported victimization. Evidence was also found for a moderator effect of personality type on the longitudinal associations between self‐esteem and victimization. Only in the subgroup of overcontrolling adolescents was lower self‐esteem related to subsequently higher levels of peer victimization; their undercontrolling and ego‐resilient peers were unaffected.     

Dose‐Response Models Incorporating Aerosol Size Dependency for Francisella tularensis

The effect of bioaerosol size was incorporated into predictive dose‐response models for the effects of inhaled aerosols of Francisella tularensis (the causative agent of tularemia) on rhesus monkeys and guinea pigs with bioaerosol diameters ranging between 1.0 and 24 μm. Aerosol‐size‐dependent models were formulated as modification of the exponential and β‐Poisson dose‐response models and model parameters were estimated using maximum likelihood methods and multiple data sets of quantal dose‐response data for which aerosol sizes of inhaled doses were known. Analysis of F. tularensis dose‐response data was best fit by an exponential dose‐response model with a power function including the particle diameter size substituting for the rate parameter k scaling the applied dose. There were differences in the pathogen's aerosol‐size‐dependence equation and models that better represent the observed dose‐response results than the estimate derived from applying the model developed by the International Commission on Radiological Protection (ICRP, 1994) that relies on differential regional lung deposition for human particle exposure.     

Modeling the Adenoma and Serrated Pathway to Colorectal CAncer (ASCCA)

Several colorectal cancer (CRC) screening models have been developed describing the progression of adenomas to CRC. Currently, there is increasing evidence that serrated lesions can also develop into CRC. It is not clear whether screening tests have the same test characteristics for serrated lesions as for adenomas, but lower sensitivities have been suggested. Models that ignore this type of colorectal lesions may provide overly optimistic predictions of the screen‐induced reduction in CRC incidence. To address this issue, we have developed the Adenoma and Serrated pathway to Colorectal CAncer (ASCCA) model that includes the adenoma‐carcinoma pathway and the serrated pathway to CRC as well as characteristics of colorectal lesions. The model structure and the calibration procedure are described in detail. Calibration resulted in 19 parameter sets for the adenoma‐carcinoma pathway and 13 for the serrated pathway that match the age‐ and sex‐specific adenoma and serrated lesion prevalence in the COlonoscopy versus COlonography Screening (COCOS) trial, Dutch CRC incidence and mortality rates, and a number of other intermediate outcomes concerning characteristics of colorectal lesions. As an example, we simulated outcomes for a biennial fecal immunochemical test screening program and a hypothetical one‐time colonoscopy screening program. Inclusion of the serrated pathway influenced the predicted effectiveness of screening when serrated lesions are associated with lower screening test sensitivity or when they are not removed. To our knowledge, this is the first model that explicitly includes the serrated pathway and characteristics of colorectal lesions. It is suitable for the evaluation of the (cost)effectiveness of potential screening strategies for CRC.     

Amassing rural power in the fight against fracking in Maryland: A report from the field

ABSTRACT

Social workers can mobilize vulnerable populations to shape policy decisions about industrial practices that could have adverse impacts on their wellbeing. One such practice is hydraulic fracturing or “fracking” to extract oil and natural gas from shale rock deposits. There is scant social work literature on mobilizing opposition to fracking despite a proliferation of literature from other disciplines. This article documents the campaign in Maryland that led to the adoption of the first legislative ban on fracking in a U.S. state with shale gas reserves, using social movement theory to identify factors that led to this successful outcome.     

Acceptance of automation manufacturing technology in China: an examination of perceived norm and organizational efficacy

Abstract

With a shift to more automation technology, social acceptance of technology plays an important role in the manufacturing sector. To what extent this occurs, and affects the adoption of technology, has been less researched, but is important in deciding how such technology is introduced, and the nature of the shift from labour-intensive manufacturing to automation. This research applies the revised technology acceptance model (TAM) to examine the impact of social and individual antecedents on the acceptance of automation manufacturing technology. Survey data are collected from 258 Chinese manufacturers. Results suggest that perceived norms significantly affect organizational intention to use automation manufacturing technology both directly and via perceived usefulness; organizational efficacy explains the intention to use via mediating effect of perceived usefulness and perceived ease of use. This research is one of the first extending and applying TAM from individuals to organizations.     

Die Bedeutung der Zinsschranke

The German Corporate Tax Reform Act of 2008 requires an adjustment of classic valuation concepts because it limits interest deduction from taxable income depending on the operating performance of the company. By using time- and state-contingent discount rates in a risk-neutral valuation with predetermined debt levels, a theoretically sound valuation result is obtained. However, a modified APV-concept which assumes deterministic debt over the planning horizon and constant leverage in the terminal value phase also yields consistent valuation results when two types of tax shields with different levels of risk are distinguished.     

Cox regression with missing covariate data using a modified partial likelihood method

Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard function with the idea being to profile out this function before carrying out the estimation of the parameter of interest. In this step one uses a Breslow type estimator to estimate the cumulative baseline hazard function. We focus on the situation where the observed covariates are categorical which allows us to calculate estimators without having to assume anything about the distribution of the covariates. We show that the proposed estimator is consistent and asymptotically normal, and derive a consistent estimator of the variance–covariance matrix that does not involve any choice of a perturbation parameter. Moderate sample size performance of the estimators is investigated via simulation and by application to a real data example.     

On the robustness of the generalized fused lasso to prior specifications

Using networks as prior knowledge to guide model selection is a way to reach structured sparsity. In particular, the fused lasso that was originally designed to penalize differences of coefficients corresponding to successive features has been generalized to handle features whose effects are structured according to a given network. As any prior information, the network provided in the penalty may contain misleading edges that connect coefficients whose difference is not zero, and the extent to which the performance of the method depend on the suitability of the graph has never been clearly assessed. In this work we investigate the theoretical and empirical properties of the adaptive generalized fused lasso in the context of generalized linear models. In the fixed \(p\) setting, we show that, asymptotically, adding misleading edges in the graph does not prevent the adaptive generalized fused lasso from enjoying asymptotic oracle properties, while forgetting suitable edges can be more problematic. These theoretical results are complemented by an extensive simulation study that assesses the robustness of the adaptive generalized fused lasso against misspecification of the network as well as its applicability when theoretical coefficients are not exactly equal. Our contribution is also to evaluate the applicability of the generalized fused lasso for the joint modeling of multiple sparse regression functions. Illustrations are provided on two real data examples.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.