Loess:: a nonparametric, graphical tool for depicting relationships between variables

Loess is a powerful but simple strategy for fitting smooth curves to empirical data. The term “loess” is an acronym for “local regression” and the entire procedure is a fairly direct generalization of traditional least-squares methods for data analysis. Loess is nonparametric in the sense that the fitting technique does not require an a priori specification of the relationship between the dependent and independent variables. Although it is used most frequently as a scatterplot smoother, loess can be generalized very easily to multivariate data; there are also inferential procedures for confidence intervals and other statistical tests. For all of these reasons, loess is a useful tool for data exploration and analysis in the social sciences. And, loess should be particularly helpful in the field of elections and voting behavior because theories often lead to expectations of nonlinear empirical relationships even though prior substantive considerations provide very little guidance about precise functional forms.     

Competing Risks, Persistence, and Desistance in Analyzing Recidivism

A statistical procedure is developed to analyze recidivism in samples whichare subject to the presence of desisters and to multiple modes ofreconviction. This allows for a more accurate study of individuals'transition and hazard in the type and timing of offenses following aspecific type of conviction. The use of a nonparametric approach forinvestigating failure in the presence of other acting causes is shown;initial estimators of the probabilities of reconviction for different typesof offenses are obtained, and the method can be used both to display thedata and to choose an appropriate parametric family for the survivaltimes. An exponential mixture model for competing risks is presented insuch a way that it allows us to adjust for concomitant variables and toassess their effects on the probabilities both of reconviction forpredetermined types of offenses and desistance and of the hazards ofreconviction; a method for assessing calibration of predicted survivalprobabilities is suggested. A 21-year follow-up of persons convicted ofindecent assault on a female in 1973 illustrates the methods; we find ahigh probability of sexual reconviction for individuals with previoussexual convictions and evidence of diversity and a raised hazard ofreconviction for young chronic offenders.     

Party strategies and electoral competition in post-Communist countries: Evidence from Poland

Poland's major post-Communist party, the SLD, was an electorally successful legacy party during the 1990's. An analysis of Polish National Election Studies data and data from a separate study of new firm creation in Poland indicates their success was built on two important and related factors. One is the growth of new firms, which stimulated the growth of a centrist constituency who voted for parties supporting economic reforms. Second, the SLD adapted to this constituency by themselves becoming more economically liberal, as documented by Grzyma?a-Busse (2002). A conditional logit model of voter choice in the 1997 and 2001 elections relates votes to the distance between voters' preferences on economic policies and the positions of the competing parties. From this analysis we estimate that if the SLD had remained an ideological non-reformist party as did the KS?M in the Czech Republic and the CPRF in Russia it would have been a far weaker party as measured by vote and seat shares. Without the new firm creation, an ideological SLD cum KS?M could have been electorally successful as was the CPRF. The paper concludes by contrasting the the Polish, Czech and Russian post-Communist parties and extending the implications of the results to other developing and industrial economies faced with the need for structural change.     

A New Approach of Juvenile Age Estimation using Measurements of the Ilium and Multivariate Adaptive Regression Splines (MARS) Models for Better Age Prediction

Juvenile age estimation methods used in forensic anthropology generally lack methodological consistency and/or statistical validity. Considering this, a standard approach using nonparametric Multivariate Adaptive Regression Splines (MARS) models were tested to predict age from iliac biometric variables of male and female juveniles from Marseilles, France, aged 0–12 years. Models using unidimensional (length and width) and bidimensional iliac data (module and surface) were constructed on a training sample of 176 individuals and validated on an independent test sample of 68 individuals. Results show that MARS prediction models using iliac width, module and area give overall better and statistically valid age estimates. These models integrate punctual nonlinearities of the relationship between age and osteometric variables. By constructing valid prediction intervals whose size increases with age, MARS models take into account the normal increase of individual variability. MARS models can qualify as a practical and standardized approach for juvenile age estimation.     

Three-dimensional modeling of the various volumes of canines to determine age and sex: a preliminary study

Canines are usually used in anthropological and forensic sciences for sex and age determination. The best methods to estimate age are based on secondary dentine apposition, evaluated from periapical X-rays. The aim of this study was to propose a new method of sex and age estimation using 3D models to obtain more precise predictions using tooth volumes. Fifty-eight dental CT scans of patients aged 14-74 with a well-balanced sex ratio composed the sample. One hundred and thirty-three healthy canines were modeled (Mimics 12.0). The sample was divided into a training sample and a validation sample. An age formula was determined using the "pulp volume/tooth volume" ratio. Sex prediction was adjusted with total volumes. Applying the equations to the validation sample, no significant difference was found between the real and predicted ages, and 100% of the sex predictions were correct. This preliminary study gives interesting results, and this method is worth being tested on a larger data sample.     

A Two‐Level Model for Evidence Evaluation in the Presence of Zeros*

Abstract: Likelihood ratios (LRs) provide a natural way of computing the value of evidence under competing propositions. We propose LR models for classification and comparison that extend the ideas of Aitken, Zadora, and Lucy and Aitken and Lucy to include consideration of zeros. Instead of substituting zeros by a small value, we view the presence of zeros as informative and model it using Bernoulli distributions. The proposed models are used for evaluation of forensic glass (comparison and classification problem) and paint data (comparison problem). Two hundred and sixty‐four glass samples were analyzed by scanning electron microscopy, coupled with an energy dispersive X‐ray spectrometer method and 36 acrylic topcoat paint samples by pyrolysis gas chromatography hyphened with mass spectrometer method. The proposed LR model gave very satisfactory results for the glass comparison problem and for most of the classification tasks for glass. Results of comparison of paints were also highly satisfactory, with only 3.0% false positive answers and 2.8% false negative answers.     

走向双重维度的研究——德美法学教育的研究性及其启示

研究性教学旨在通过学生主体参与,培养学生理论研究与创新工作的能力。德美法学教育改革中逐步凸显的理论指向与实践指向平衡发展的研究性教学,对我国当前的法学教育深有启迪。借鉴德美研究性教学经验,发展适合我国法学本科研究性教学的具体模式,将为完善我国当前的本科法学教育提供新的思考。     

Major depression – a study on the validity of clinicians’ diagnoses in medicolegal assessment

Major depression ranges among the most frequently diagnosed psychiatric disorders. Accordingly, diagnoses of depression are often underlying insurance, compensation or disability claims. This report evaluates the validity of clinicians’ diagnoses of major depression in a sample of claimants. In 2015, n = 127 consecutive cases were examined for medicolegal assessment. For all of them, a diagnosis of major depression had been established by clinicians. All testees underwent a psychiatric interview, a physical examination, they answered questionnaires for depressive symptoms according to DSM-5, embitterment disorder, post concussion syndrome (PCS) and unspecific somatic complaints. Performance and symptom validity tests were administered. Only 31% fulfilled the diagnostic criteria for DSM-5 major depression according to self-report, while none did so according to psychiatric assessment. Negative response bias was found in 64% of cases, feigned neurologic symptoms in 22%. Symptom exaggeration was indiscriminate rather than depression-specific. By self-report, 64% of the participants qualified for embitterment disorder and 93% for PCS. In conclusion, clinicians’ diagnoses of depression seem often confounded by improper assessment of the diagnostic criteria, confusion of depression with bereavement or embitterment and also by response bias.     

Integrating Behavioral Health Care and Primary Care: Application of a Clinical and Economic Model in Culturally Diverse Communities

Although mental illness treatment protocols exist, the organization and financing of screening and treatment services inhibit access. These challenges are compounded for refugees, immigrants, and other groups vulnerable due to their ethnicity, race, or culture. By creating a system-wide, collaborative, integrated model that recognizes and addresses critical clinical and economic aspects in the delivery of services, high quality, evidence-based care can be made available to groups susceptible to the burdens of mental illness. Clinically and financially aligning primary and specialty care offers a viable alternative for improving access and quality of mental health services to vulnerable populations.