A longitudinal analysis of factors associated with reporting violent crimes to the police

The use of generalized estimating equations and time-series methods for fitting longitudinal models in the National Crime Victimization Survey (NCVS) is discussed, with reference to the relation between the reporting of a violent crime to the police and previous victimizations. Two longitudinal models are fit to NCVS data to predict the likelihood of reporting a violent crime to the police based on characteristics of the victim and the incident and based on previous victimization experiences. In both models, it is found that higher reporting rates are associated with positive results accruing from reporting previous victimization to the police.     

Is Violence Bad for Your Health? An Assessment of Chronic Disease Outcomes in a Nationally Representative Sample

Longitudinal offending research has grown substantially in the last two decades. Despite this increased scholarly attention, longitudinal investigations of the effects of offending on physical health have not kept pace. Acknowledging the intersections of criminology, criminal justice, and public health, this study examines the relationship between violent offending and chronic diseases among a nationally representative longitudinal sample of young adults. Results suggest that variation across offender typologies (i.e. adolescence-limited, adult-onset, and consistent violence during youth and young adulthood) significantly predicts experiencing chronic disease in early adulthood, with the risk being the most pronounced among those individuals, who demonstrate violence continuity. Study limitations and policy implications are discussed.     

Bullying in Childhood,Externalizing Behaviors,and Adult Offending: Evidence From a 30-Year Study

This study examined the developmental processes linking childhood bullying to criminal offending in adulthood, using data from a 30-year longitudinal study. The linkages between bullying in childhood and three criminal offending outcomes in adulthood were estimated both before and after control for a range of confounding factors. A series of protective factors that potentially mediated these linkages were also examined. The results of the study showed that while the majority of the association between childhood bullying and adult offending could be explained by confounding factors including childhood externalizing behavior, there was evidence for direct linkages from bullying to violent offending and arrest/conviction. There was little evidence to suggest mediation of the associations. The results suggest that bullying prevention requires interventions aimed specifically at bullying behavior.     

组织RNA检测用于死亡时间推断的研究进展

近几年来利用RNA的降解程度来推断死亡时间已逐渐成为法医学研究热点.本文复习相关研究文献,对大鼠不同组织(脑组织、心脏组织、肝脏组织和肾组织等)中RNA在推断死亡时间的具体应用方法做出总结,归纳出不同组织中的各类RNA在推断死亡时间方面的适用范围,以及对此种方法在推断死亡时间的过程中产生的问题及可行性的解决方法.     

Assessing Covariates of Adolescent Delinquency Trajectories: A Latent Growth Mixture Modeling Approach

Using data from a community sample of 1218 boys and girls (mean age at the first wave was 15.5 years), this longitudinal study examined several covariates—adjustment problems, poor academic achievement, negative life events, and unsupportive family environments—of distinctive trajectories of juvenile delinquency. Latent growth mixture modeling analysis revealed 6 trajectory groups: rare offenders, moderate late peakers, high late peakers, decreasers, moderate-level chronics, and high-level chronics. Several factors discriminated between more normative groups and high-level chronic offenders, including poor academic achievement, unsupportive family environments, life events, and substance use, whereas almost no differences were found between groups with more serious offending trajectories. Overall, there was more specificity in correlates of distinctive offending trajectories than expected by general theories of crime (e.g., Gottfredson, M. R., and Hirschi, T., 1990, A General Theory of Crime. Stanford University Press, Stanford, CA).     

Growth curves of deviant behavior in early adolescence: A multilevel analysis

Multilevel growth curve models provide a means of analyzing individual differences in the growth of deviance, allow a number of theories to be integrated in a single model, and can help to unify research on deviant/delinquent/criminal careers at different stages of the life cycle. Building on the distinction between population heterogeneity and state dependence as alternative explanations of persistent individual differences in deviance (Heckman, 1981; Nagin and Paternoster, 1991), we show that models with two levels can be used to represent and analyze a variety of criminological theories. The first level (level 1) uses repeated measurements on individuals to estimate individual-level growth curves. The second level treats the level 1 growth curve parameters (e.g., slope, intercept) as outcome variables and uses time-invariant factors to explain variation in these parameters across individuals. We illustrate this approach by estimating a model of growth in deviance drawn from Gottfredson and Hirschi's deviant propensity theory. An innovative feature is the assumption that adolescents' expected growth curves of deviance follow a classical Pearl-Verhulst logistic growth model (Pearl, 1930). The results suggest that five risk factors—parental psychiatric problems, lack of parental support, living arrangements with zero or one parent in residence, low family income, and male gender—have strongly positive effects on deviant propensity. For example, adolescents with no supportive parents, and no other risk factors, have expected asymptotic levels of deviance (peak levels attained at about age 18) that are about twice as high as those of adolescents with no risk factors. Yet more than two-thirds of the individual-level variability in growth curves is unexplained by the five risk factors. This unobserved heterogeneity would remain hidden in analyses using conventional structural equations models and the same explanatory variables.     

On identification problems requiring linked autosomal markers

This paper considers identification problems based on DNA marker data. The topics we discuss are general, but we will exemplify them in a simple context. There is DNA available from two persons. There is uncertainty about the relationship between the two individuals and a number of hypotheses describing the possible relationship is available. The task is to determine the most likely pedigree. This problem is fairly standard. However, there are some problems that cannot be solved using DNA from independently segregating loci. For example, the likelihoods for (i) grandparent–grandchild, (ii) uncle–niece and (iii) half-sibs coincide for such DNA data and so these relations cannot be distinguished on the basis of markers normally used for forensic identification problems: the likelihood ratio comparing any pair of hypotheses will be unity.Sometimes, but not in the examples we consider, other sources of DNA like mtDNA or sex chromosomes can help to distinguish between such equally likely possibilities. Prior information can likewise be of use. For instance, age information can exclude alternative (i) above and also indicate that alternative (iii) is apriori more likely than alternative (ii).More generally, the above problems can be solved using linked autosomal markers. To study the problem in detail and understand how linkage works in this regard, we derive an explicit formula for a pair of linked markers. The formula extends to independent pairs of linked markers. While this approach adds to the understanding of the problem, more markers are required to obtain satisfactory results and then the Lander–Green algorithm is needed. Simulation experiments are presented based on a range of scenarios and we conclude that useful results can be obtained using available freeware (MERLIN and R).The main message of this paper is that linked autosomal markers deserve greater attention in forensic genetics and that the required laboratory and statistical analyses can be performed based on existing technology and freeware.     

The Effects of Different Maceration Techniques on Nuclear DNA Amplification Using Human Bone

Abstract: Forensic anthropologists routinely macerate human bone for the purposes of identity and trauma analysis, but the heat and chemical treatments used can destroy genetic evidence. As a follow‐up to a previous study on nuclear DNA recovery that used pig ribs, this study utilizes human skeletal remains treated with various bone maceration techniques for nuclear DNA amplification using the standard Combined DNA Index System (CODIS) markers. DNA was extracted from 18 samples of human lower leg bones subjected to nine chemical and heat maceration techniques. Genotyping was carried out using the AmpF?STR^® COfiler^® and AmpF?STR^® Profiler Plus^® ID kits. Results showed that heat treatments via microwave or Biz/Na₂CO₃ in sub‐boiling water efficiently macerate bone and produce amplifiable nuclear DNA for genetic analysis. Long‐term use of chemicals such as hydrogen peroxide is discouraged as it results in poor bone quality and has deleterious effects on DNA amplification.     

创伤性脑损伤后生物分子标志物的研究进展

创伤性脑损伤(traumatic brain injury,TBI)是指机械性外力作用于头部时发生的损伤,导致一个或者多个病变,如颅内损伤、神经病学或者神经心理学改变、意识障碍或者死亡。TBI可因直接打击、缺血缺氧性脑损伤、炎性介质、细胞因子及氧自由基等机制诱发神经元死亡。TBI发生发展过程中产生了大量生物分子标志物,深入研究TBI后生物分子标志物的变化及其规律,对法医学鉴定及临床治疗都有重大意义。本文结合相关文献概述了TBI相关生物分子标志物的研究进展,为寻找更精确的与TBI诊断相关的生物分子标志物提供参考依据。     

Revisiting Respondent “Fatigue Bias” in the National Crime Victimization Survey

For more than three decades the National Crime Victimization Survey (NCVS)—and its predecessor the National Crime Survey (NCS)—have been used to calculate estimates of nonfatal crime in the United States. Though the survey has contributed much to our understanding of criminal victimization, some aspects of the survey’s methodology continue to be analyzed (e.g., repeat victimizations, proxy interviews, and bounding). Surprisingly, one important aspect of NCVS methodology has escaped this scrutiny: respondent fatigue. A potential source of nonsampling error, fatigue bias is thought to manifest as respondents become “test wise” after repeated exposure to NCVS survey instruments. Using a special longitudinal NCVS data file, we revisit the presence and influence of respondent fatigue in the NCVS. Specifically, we test the theory that respondents exposed to longer interviews during their first interview are more likely to refuse to participate in the survey 6 months later. Contrary to expectations based on the literature, results show that prior reporting of victimization and exposure to a longer interview is not a significant predictor of a noninterview during the following time-in-sample once relevant individual characteristics are accounted for. Findings do demonstrate significant effects of survey mode and several respondent characteristics on subsequent survey non-participation.