The unique relationship between childhood sexual abuse,self-injury and suicide ideation: The mediating role of emotion dysregulation

Child sexual abuse (CSA) has serious short-term and long-term effects, including non-suicidal self-injury (NSSI) and suicidal ideation (SI). One possible thread linking CSA to NSSI and suicide risk is emotion dysregulation. The current study assessed whether facets of emotion dysregulation mediated relations of NSSI behaviours and functions, and SI. Participants (N = 121; Mean age = 18.69, age-range 18–22; 78 per cent female), college students with a history of childhood trauma, completed an online survey. Results indicated that facets of emotion dysregulation (i.e. clarity, non-acceptance) mediated the relationship between CSA and SI. CSA was associated with automatic negative reinforcement, social negative and social positive reinforcement NSSI functions, but was not associated with NSSI behaviours. Emotion dysregulation facets did not mediate the relationship between CSA and NSSI functions. Findings highlight the need to help CSA survivors have clarity and acceptance of emotional experiences to reduce SI risk. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.     

Sibship and Inequality Beliefs: Do Siblings Have a Liberalizing or Conservatizing Effect?

How do individuals come to hold certain beliefs about meritocracy, individualism, and redistribution? Several sociodemographic factors are regularly used to understand variation in these beliefs, but other predictors remain untested. Meanwhile, scholars studying family dynamics are increasingly turning their attention toward the long-term social effects of distinct family features. One facet of this work focuses on the social role of siblings. We investigate the relationship at the intersection of these literatures. How does growing up with (more) siblings influence one's inequality beliefs? Do siblings promote collectivism or might these same relationships foster competition and individualism? Could trust be the mechanism connecting sibship size with inequality beliefs? Or, do sibling effects reflect a broader promotion of conservative thinking in larger families? We investigate these questions using data from the General Social Survey from 1984 to 2018. Our results indicate that siblings are associated with more conservative meritocracy beliefs. On the other hand, we find limited evidence of siblings influencing attitudes toward redistribution.     

Bayesian local influence for survival models

The aim of this paper is to develop a Bayesian local influence method (Zhu et al. 2009, submitted) for assessing minor perturbations to the prior, the sampling distribution, and individual observations in survival analysis. We introduce a perturbation model to characterize simultaneous (or individual) perturbations to the data, the prior distribution, and the sampling distribution. We construct a Bayesian perturbation manifold to the perturbation model and calculate its associated geometric quantities including the metric tensor to characterize the intrinsic structure of the perturbation model (or perturbation scheme). We develop local influence measures based on several objective functions to quantify the degree of various perturbations to statistical models. We carry out several simulation studies and analyze two real data sets to illustrate our Bayesian local influence method in detecting influential observations, and for characterizing the sensitivity to the prior distribution and hazard function.     

Why a Bayesian approach to safety analysis in pharmacovigilance is important

Large databases of routinely collected data are a valuable source of information for detecting potential associations between drugs and adverse events (AE). A pharmacovigilance system starts with a scan of these databases for potential signals of drug-AE associations that will subsequently be examined by experts to aid in regulatory decision-making. The signal generation process faces some key challenges: (1) an enormous volume of drug-AE combinations need to be tested (i.e. the problem of multiple testing); (2) the results are not in a format that allows the incorporation of accumulated experience and knowledge for future signal generation; and (3) the signal generation process ignores information captured from other processes in the pharmacovigilance system and does not allow feedback. Bayesian methods have been developed for signal generation in pharmacovigilance, although the full potential of these methods has not been realised. For instance, Bayesian hierarchical models will allow the incorporation of established medical and epidemiological knowledge into the priors for each drug-AE combination. Moreover, the outputs from this analysis can be incorporated into decision-making tools to help in signal validation and posterior actions to be taken by the regulators and companies. We discuss in this paper the apparent advantage of the Bayesian methods used in safety signal generation and the similarities and differences between the two widely used Bayesian methods. We will also propose the use of Bayesian hierarchical models to address the three key challenges and discuss the reasons why Bayesian methodology still have not been fully utilised in pharmacovigilance activities.     

Statistical approaches for conducting network meta-analysis in drug development

We introduce health technology assessment and evidence synthesis briefly, and then concentrate on the statistical approaches used for conducting network meta-analysis (NMA) in the development and approval of new health technologies. NMA is an extension of standard meta-analysis where indirect as well as direct information is combined and can be seen as similar to the analysis of incomplete-block designs. We illustrate it with an example involving three treatments, using fixed-effects and random-effects models, and using frequentist and Bayesian approaches. As most statisticians in the pharmaceutical industry are familiar with SAS? software for analyzing clinical trials, we provide example code for each of the methods we illustrate. One issue that has been overlooked in the literature is the choice of constraints applied to random effects, and we show how this affects the estimates and standard errors and propose a symmetric set of constraints that is equivalent to most current practice. Finally, we discuss the role of statisticians in planning and carrying out NMAs and the strategy for dealing with important issues such as heterogeneity.     

Vendor Selection with Bundling: A Comment*

In a recent article by Rosenthal, Zydiak, and Chaudhry (1995), a mixed integer linear programming model was introduced to solve the vendor selection problem for the case in which the vendor can sell items individually or as part of a bundle. Each vendor offered only one type of bundle, and the buyer could purchase at most one bundle per vendor. The model employed n(m+ 1) binary variables, where n is the number of vendors and m is the number of products they sell. The existing model can lead to a purchasing paradox: it may force the buyer to pay more to receive less. We suggest a reformulation of the same problem that (i) eliminates this paradox and reveals a more cost-effective purchasing strategy; (ii) uses only n integer variables and significantly reduces the computational workload; and (iii) permits the buyer to purchase more than one bundle per vendor.     

Implementing integrated pest management in professional lawn care: a case study

Human choices regarding land cover management practices may influence ecosystem services provided by urban green spaces. We conducted a 2-year study to compare biological (weed, insect, and disease), aesthetic (lawn quality), and economic (lawn care program cost) attributes of an integrated pest management (IPM) program, in which pesticides are applied on the basis of treatment thresholds, with a standard program, in which pesticides are applied on a calendar basis without pest monitoring. Both programs were managed by a professional lawn care operator. Although weed incidence was low, the IPM program had significantly more lawns with weed presence than the standard program during 2005 and 2006. However, only 21% of the IPM lawns required herbicide applications in 2005, and none exceeded the treatment threshold (5% weed cover) in 2006 as compared to 100% of the standard program lawns being treated for weeds in both years. The IPM program also had significantly more lawns with insect damage than the standard program during June 2005 and August 2005, but not September 2005 and throughout 2006. Only 28% of the IPM lawns required insecticide applications in 2005 and none exceeded the threshold (5% insect damage) in 2006 whereas all of the lawns in the standard program received insecticide treatments in both years. Rhizoctonia blight was present on some of the lawns, but was not a common problem. Although lawn quality was high for both programs (>8, on a scale of 1–9), it was significantly higher for standard than for IPM program lawns during 2005, and June 2006 and September 2006, but not August 2006. The annual lawn management costs were lower for the IPM (281.50) than the standard program (281.50) than the standard program (458.06). Thirty one percent of the IPM program customers who continued with the study in 2006 did so because they were satisfied with the IPM program. Among those who did not continue with the program, 33% cited weed or insect problems, while 33% expected better results. The implications of these findings for implementation of IPM in professional lawn care are further discussed.