Bradley-Terry models in R : the BradleyTerry2 package

This is a short overview of the R add-on package BradleyTerry2, which facilitates the specification and fitting of Bradley-Terry logit, probit or cauchit models to pair-comparison data. Included are the standard 'unstructured' Bradley-Terry model, structured versions in which the parameters are related through a linear predictor to explanatory variables, and the possibility of an order or 'home advantage' effect or other 'contest-specific' effects. Model fitting is either by maximum likelihood, by penalized quasi-likelihood (for models which involve a random effect), or by bias-reduced maximum likelihood in which the first-order asymptotic bias of parameter estimates is eliminated. Also provided are a simple and efficient approach to handling missing covariate data, and suitably-defined residuals for diagnostic checking of the linear predictor

Questions and Answers About the National Survey of Children\u27s Exposure to Violence.

Presents an overview of the National Survey of Children\u27s Exposure to Violence (NatSCEV), the most comprehensive nationwide survey to date of the incidence and prevalence of children\u27s exposure to violence, sponsored by OJJDP and the Centers for Disease Control and Prevention and carried out by the Crimes Against Children Research Center of the University of New Hampshire. It outlines the survey’s objectives and key features, how exposure to violence was measured, and plans for followup surveys and publications. NatSCEV bases its estimates on a large, nationally representative sample of more than 4,500 children ages 17 and younger. The survey interviewed caregivers of children ages 9 and younger and children and youth ages 10 to 17 about 45 different kinds of violence, abuse, and victimization in the past year and over the course of their lifetime

Children\u27s Exposure to Intimate Partner Violence and Other Family Violence.

Explores in depth the survey results from the National Survey of Children\u27s Exposure to Violence (NatSCEV) regarding exposure to family violence among children in the United States, including exposure to intimate partner violence, assaults by parents on siblings of children surveyed, and other assaults involving teen and adult household members. These results confirm that children are exposed to unacceptable rates of violence in the home. The bulletin presents information regarding the types of exposure to family violence, the gender of the perpetrator, the relationship of the child witness to the perpetrator, and youth\u27s reactions to the incident. It also discusses the implications of the survey data for researchers, practitioners, and policymakers and makes policy recommendations, including better screening protocols for exposure to family violence, improved interventions for those exposed, increased coordination of services for adult and child victims of family violence, and more prevention and education programs to reduce family violence. This is the second in a series of bulletins that present findings from NatSCEV, the most comprehensive nationwide survey to date of the incidence and prevalence of children’s exposure to violence across all ages, settings, and timeframes

Child and Youth Victimization Known to Police, School, and Medical Authorities.

Presents the survey results from the National Survey of Children\u27s Exposure to Violence (NatSCEV) regarding authorities\u27 knowledge of victimization incidents involving children and youth, particularly police, school, and medical authorities. Compared with a similar study in the early 1990s, the survey found that authorities were more likely to know about NatSCEV survey participants\u27 exposure to violence, which may reflect efforts by authorities, criminal justice and child protection agencies, and advocates to promote disclosure. This increase in disclosure is also consistent with the decrease in child victimizations during the last two decades. The survey found that 46 percent of children who were victimized in the previous year had at least one victimization known to school, police, and medical authorities, with school authorities (e.g., teachers, principals, and counselors) being the most likely to know of the victimizations. However, police were most likely to know about many of the most serious victimizations. In general, authorities were most likely to know about serious victimizations, including sexual abuse by an adult, kidnapping, and gang or group assaults. They were least likely to know about victimizations committed by other youth, including peer and sibling assaults, dating violence, flashing, and completed or attempted rate. This bulletin also discusses factors that promote or hinder disclosure of victimization incidents to authorities, and the implications of the increase in disclosure for prevention and treatment. This is the fourth in a series of bulletins that present findings from NatSCEV, the most comprehensive nationwide survey to date of the incidence and prevalence of children’s exposure to violence across all ages, settings, and timeframes

Modelling rankings in R: the PlackettLuce package

This paper presents the R package PlackettLuce, which implements a generalization of the Plackett-Luce model for rankings data. The generalization accommodates both ties (of arbitrary order) and partial rankings (complete rankings of subsets of items). By default, the implementation adds a set of pseudo-comparisons with a hypothetical item, ensuring that the underlying network of wins and losses between items is always strongly connected. In this way, the worth of each item always has a finite maximum likelihood estimate, with finite standard error. The use of pseudo-comparisons also has a regularization effect, shrinking the estimated parameters towards equal item worth. In addition to standard methods for model summary, PlackettLuce provides a method to compute quasi standard errors for the item parameters. This provides the basis for comparison intervals that do not change with the choice of identifiability constraint placed on the item parameters. Finally, the package provides a method for model-based partitioning using covariates whose values vary between rankings, enabling the identification of subgroups of judges or settings that have different item worths. The features of the package are demonstrated through application to classic and novel data sets.Comment: In v2: review of software implementing alternative models to Plackett-Luce; comparison of algorithms provided by the PlackettLuce package; further examples of rankings where the underlying win-loss network is not strongly connected. In addition, general editing to improve organisation and clarity. In v3: corrected headings Table 4, minor edit

Transcutaneous removal of an intravenous catheter fragment using a spider FX™ Embolic Protection device

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113099/1/ccd25839.pd