Ethnic Differences in Trajectories of Family Cohesion for Mexican American and Non-Hispanic White Adolescents

This study examined gender, family structure, SES and language usage as predictors of cultural orientation and family cohesion. Ethnic differences in trajectories of family cohesion were tested within a hierarchical linear modeling framework. The sample consisted of 4156 adolescent respondents, measured at three time points during three consecutive years. The three study groups consisted of Mexican Americans oriented to Mexican culture (N = 738), Mexican Americans oriented to majority American culture (N = 867), and Non-Hispanic Whites (N = 2551). Family cohesion was assessed using the cohesion subscale of the Family Adaptability and Cohesion Scale (FACES III). Analyses consisted of hierarchical linear modeling (HLM) in which a linear trajectory of family cohesion for the three groups was computed followed by a test for the effects of ethnicity with the inclusion of control variables. Thus, ethnic differences in the trajectories of family cohesion over time were examined. Neither group of Mexican Americans was significantly different from Non-Hispanic Whites in initial status. However, Mexican Americans oriented to Mexican culture showed a significant increase in family cohesion at mid adolescence. Judith C. Baer is an Associate Professor at Rutgers University. She received her Ph.D. in Social Work from the University of Houston. Her major research interests include the study of adolescent development within the contexts of culture, and family, adolescent sexual risk taking, and the nosology of mental disorders. Mark F. Schmitz is Clinical Assistant Professor at Temple University. He received his Ph.D. in sociology at Iowa State University. His major research interest involves the use of several large epidemiologic datasets for an extensive examination of the empirical basis for the diagnostic criteria of various DSM-IV mental disorders. He also is involved in research on cultural issues in child development and family processes.     

Predictive crime mapping

Geographic Information Systems (GIS) have emerged as a key tool in intelligence-led policing and spatial predictions of crime are being used by many police services to reduce crime. Break and entries (BNEs) are one of the most patterned and predictable crime types, and may be particularly amendable to predictive crime mapping. A pilot project was conducted to spatially predict BNEs and property crime in Vancouver, Canada. Using detailed data collected by the Vancouver Police Department on where and when observed crimes occur, the statistical model was able to predict future BNEs for residential and commercial locations. Ideally implemented within a mobile GIS, the automated model provides continually updated predictive maps and may assist patrol units in self-deployment decisions. Future research is required to overcome computational and statistical limitations, and to preform model validation.     

CRIME DIVERSITY*

Large geographic areas should host a greater diversity of crime compared with small geographic areas. This proposition is reasonable given that larger geographic areas should not only support more crime but also contain a greater diversity of criminogenic settings. This article uses a neutral model to characterize crime richness as a function of area. The model starts with two neutral assumptions: 1) that all environments are statistically equivalent and exert no influence on what types of crimes occur there; and 2) that different crime types occur independently of one another. The model produces rigorous predictions for the mean and variance in crime richness with increasing area. Tests of the model against a sample of 172,055 crimes occurring in Los Angeles during the year 2013 are qualitatively consistent with neutral expectations. The model is made quantitatively consistent by constant scaling. Resampling experiments show that at most 20 percent of the mean crime richness is attributable to nonrandom clustering and assortment of crime types. A modified neutral model allowing for variation crime concentration is consistent with observed variance in crime richness. The results suggest that very general and largely neutral laws may be driving crime diversity in space.     

How often have X- and autosomal-STRs mutations equivocal parental origin been assigned?

Short tandem repeat markers (STRs) are widely applied in population, evolutionary, and forensic genetics, due to extensive polymorphism in the number of repetitive motifs. The primary mutational mechanism leading to changes in the length of STRs is thought to be polymerase template slippage. Mutation rates in STRs and corresponding parental assignment are usually assessed through the number of Mendelian incompatibilities observed in one-generational, parent(s)-child, pedigrees, and paternal mutations have been assumed to be preponderant over maternal ones. Notwithstanding, diploid and haplodiploid modes of genetic transmission may not allow for the unequivocal assigning of the mutation to the correct parental origin (either paternal or maternal), especially when genotyping methodologies of fragment length determination are employed. In this work, the frequency under which a mutation might be assigned to the wrong parental origin or be interpreted as having an ambiguous origin is analyzed for both diploid and haplodiploid modes of genetic transmission. Genotypic configurations were generated with Python™ programming language, considering parents-child trios for autosomal transmission, and parents-daughter trios for the X chromosomal one. One single-, one two- or one three-step mutation was simulated in each familial constellation, and the resulting genotypic configuration was analyzed regarding the parental assignment of the mutation. When considering autosomal transmission, the meiosis suffering mutation was randomly selected. Contrarily, differential analyses were performed for paternal and maternal mutations for X-chromosomal transmission. In this work, we show that the biases in the rates between paternal and maternal mutations differ for autosomal and X-chromosomal modes of transmission. In the differential analysis performed for the X-chromosomal STRs, it is possible to ascertain that the maternal and paternal meioses are subject to different biases, the latter being better estimated than the first. This work shows that simulated data, along with reliable and properly communicated real one, may be crucial for the correct modeling of biological processes, such as the mutation in STRs.     

How frequently are Autosomal and X-STRs multistep mutations perceived as single-step?

Short tandem repeats (STRs) incur in length mutations that involve the loss or gain of repeats. STR mutation rates are usually estimated considering the rates of observed Mendelian incompatibilities in one generation familial configurations. When considering multistep mutations, for the autosomal and X-chromosomal modes of genetic transmission, underestimations are inevitable when using this approach (MIA), due to the occurrence of mutational events deceptively perceived as involving fewer steps. The rate of this occurrence depends on the mode of genetic transmission considered, the parental origin of the mutation, the type of familial configuration considered, and the genotypic background of the progenitor(s). MIA biases were weighted and compared for the diploid and haplodiploid modes of transmission, using familial genotypic configurations (parent(s)-child duos and trios) generated resorting to Python™ and real population databases from Norway, Somalia, and Spain for 10 Aut-STRs and Argentina, Eastern Asia, and Northern Europe for 12 X-STRs. One two- or one three-step mutation was simulated in each of the 1,000,000 familial configurations. The frequency with which mutations could be interpreted as involving fewer steps, when the most parsimonious reasoning is employed, was computed. Results showed that the magnitude and type of biases depend on the type of familial data and the genetic mode of transmission considered, being higher in duos than in trios, both in autosomes and the X chromosome. Indeed, whether X- or Aut-STRs are analyzed, trios generally provide better estimates and should be favored over duos. The pooling of the two types of data is not advised. The greater the number of steps involved in the mutation, the worst the estimates obtained. In X-chromosomal analyzes, trios with a paternal mutation presented the best estimates and mother-daughter duos the worst; mother-son duos showed similar estimates to trios when a maternal mutation was considered.     

Using group-based trajectory modeling in conjunction with propensity scores to improve balance

This paper builds upon two prior papers by Haviland and Nagin (Psychometrika 70:1–22, 2005) and Haviland, Nagin, and Rosenbaum (Working paper, 2006) that attempt to bring the key attributes of an experiment to the analysis of non-experimental longitudinal data. Using a case study of the facilitation effect of gang membership on violence, it systematically examines the contribution of group-based trajectory modeling to the achievement of covariate balance in observational data. In this case study, inclusion of the posterior probabilities of group membership (PPGM), from a model on the pre-treatment measures of the outcome variable, created closer balance on these key covariates than did analyses that did not include them. Still closer balance was obtained on these key covariates by stratifying the analysis by trajectory group. This stratification was achieved by fitting separate propensity score models and matching gang joiners to gang abstainers within trajectory group. In addition, we demonstrated that further balance could be obtained on additional covariates by including PPGM from a model on pre-treatment longitudinal data of these covariates. While this case study is only one empirical example, we believe that it provides useful empirical evidence on the value of performing within trajectory group causal inference in observational longitudinal data and on the use of the PPGM in achieving balance in propensity score-based causal inference.

MARKETIZED MENTALITY,COMPETITIVE/EGOISTIC SCHOOL CULTURE,AND DELINQUENT ATTITUDES AND BEHAVIOR: AN APPLICATION OF INSTITUTIONAL ANOMIE THEORY*

We analyze the individual‐level and school‐level determinants of delinquency through the lens of a macro‐sociological theory of crime—institutional anomie theory (IAT). The concept of a “marketized mentality” is introduced as a predictor of students’ delinquency, along with an egoistic/competitive school culture—a feature of the school community. Five hypotheses pertaining to the readiness to use violence and self‐reported delinquency were assessed using multilevel modeling with data from a survey in Germany for 4,150 students clustered in 69 schools. The results largely meet theoretical expectations. The measure of marketized mentality exhibits robust relationships with both forms of delinquency at the individual level, and an egoistic/competitive school culture helps explain variation in levels of these forms of delinquency across schools. Also consistent with expectations, the anti‐social effects of marketized mentality are accentuated for both the readiness to use violence and committing instrumentally motivated property offenses as a competitive/egoistic school climate increases. The results of our analyses reveal that bringing in concepts of IAT can appreciably enhance understanding of the characteristics of students and features of communal school organization that are conducive to youthful offending.