Data-driven efficient score tests for deconvolution problems

We consider testing statistical hypotheses about densities of signals in deconvolution models. A new approach to this problem is proposed. We constructed score tests for the deconvolution with the known noise density and efficient score tests for the case of unknown density. The tests are incorporated with model selection rules to choose reasonable model dimensions automatically by the data. Consistency of the tests is proved

Adult attachment styles and the psychological response to infant bereavement

Background: Based on Bowlby's attachment theory, Bartholomew proposed a four-category attachment typology by which individuals judged themselves and adult relationships. This explanatory model has since been used to help explain the risk of psychiatric comorbidity. Objective: The current study aimed to identify attachment typologies based on Bartholomew's attachment styles in a sample of bereaved parents on dimensions of closeness/dependency and anxiety. In addition, it sought to assess the relationship between the resultant attachment typology with a range of psychological trauma variables. Method: The current study was based on a sample of 445 bereaved parents who had experienced either peri- or post-natal death of an infant. Adult attachment was assessed using the Revised Adult Attachment Scale (RAAS) while reaction to trauma was assessed using the Trauma Symptom Checklist (TSC). A latent profile analysis was conducted on scores from the RAAS closeness/dependency and anxiety subscales to ascertain if there were underlying homogeneous attachment classes. Emergent classes were used to determine if these were significantly different in terms of mean scores on TSC scales. Results: A four-class solution was considered the optimal based on fit statistics and interpretability of the results. Classes were labelled “Fearful,” “Preoccupied,” “Dismissing,” and “Secure.” Females were almost eight times more likely than males to be members of the fearful attachment class. This class evidenced the highest scores across all TSC scales while the secure class showed the lowest scores. Conclusions: The results are consistent with Bartholomew's four-category attachment styles with classes representing secure, fearful, preoccupied, and dismissing types. While the loss of an infant is a devastating experience for any parent, securely attached individuals showed the lowest levels of psychopathology compared to fearful, preoccupied, or dismissing attachment styles. This may suggest that a secure attachment style is protective against trauma-related psychological distress

Evidence of symptom profiles consistent with posttraumatic stress disorder and complex posttraumatic stress disorder in different trauma samples

Background: The International Classification of Diseases, 11th version (ICD-11), proposes two related stress and trauma-related disorders, posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD). A diagnosis of CPTSD requires that in addition to the PTSD symptoms, an individual must also endorse symptoms in three major domains: (1) affective dysregulation, (2) negative self-concepts, and (3) interpersonal problems. This study aimed to determine if the naturally occurring distribution of symptoms in three groups of traumatised individuals (bereavement, sexual victimisation, and physical assault) were consistent with the ICD-11, PTSD, and CPTSD specification. The study also investigated whether these groups differed on a range of other psychological problems. Methods and Results: Participants completed self-report measures of each symptom group and latent class analyses consistently found that a three class solution was best. The classes were “PTSD only,” “CPTSD,” and “low PTSD/CPTSD.” These classes differed significantly on measures of depression, anxiety, dissociation, sleep disturbances, somatisation, interpersonal sensitivity, and aggression. The “CPTSD” class in the three samples scored highest on all the variables, with the “PTSD only” class scoring lower and the “low PTSD/CPTSD” class the lowest. Conclusion: This study provides evidence to support the diagnostic structure of CPTSD and indicted that CPTSD is associated with a broad range of other psychological problems

A maximum likelihood method for latent class regression involving a censored dependent variable

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45751/1/11336_2005_Article_BF02294647.pd

Assessing the co-occurrence of intimate partner violence domains across the life-course: relating typologies to mental health

Background: The inter-generational transmission of violence (ITV) hypothesis and polyvictimisation have been studied extensively. The extant evidence suggests that individuals from violent families are at increased risk of subsequent intimate partner violence (IPV) and that a proportion of individuals experience victimisation across multiple rather than single IPV domains. Both ITV and polyvictimisation are shown to increase the risk of psychiatric morbidity, alcohol use, and anger expression. Objective: The current study aimed to 1) ascertain if underlying typologies of victimisation across the life-course and over multiple victimisation domains were present and 2) ascertain if groupings differed on mean scores of posttraumatic stress disorder (PTSD), depression, alcohol use, and anger expression. Method: University students (N=318) were queried in relation to victimisation experiences and psychological well-being. Responses across multiple domains of IPV spanning the life-course were used in a latent profile analysis. ANOVA was subsequently used to determine if profiles differed in their mean scores on PTSD, depression, alcohol use, and anger expression. Results: Three distinct profiles were identified; one of which comprised individuals who experienced “life-course polyvictimisation,” another showing individuals who experienced “witnessing parental victimisation,” and one which experienced “psychological victimisation only.” Life-course polyvictims scored the highest across most assessed measures. Conclusion: Witnessing severe physical aggression and injury in parental relationships as a child has an interesting impact on the ITV into adolescence and adulthood. Life-course polyvictims are shown to experience increased levels of psychiatric morbidity and issues with alcohol misuse and anger expression

What happens in the Lab: Applying Midstream Modulation to Enhance Critical Reflection in the Laboratory

In response to widespread policy prescriptions for responsible innovation, social scientists and engineering ethicists, among others, have sought to engage natural scientists and engineers at the ‘midstream’: building interdisciplinary collaborations to integrate social and ethical considerations with research and development processes. Two ‘laboratory engagement studies’ have explored how applying the framework of midstream modulation could enhance the reflections of natural scientists on the socio-ethical context of their work. The results of these interdisciplinary collaborations confirm the utility of midstream modulation in encouraging both first- and second-order reflective learning. The potential for second-order reflective learning, in which underlying value systems become the object of reflection, is particularly significant with respect to addressing social responsibility in research practices. Midstream modulation served to render the socio-ethical context of research visible in the laboratory and helped enable research participants to more critically reflect on this broader context. While lab-based collaborations would benefit from being carried out in concert with activities at institutional and policy levels, midstream modulation could prove a valuable asset in the toolbox of interdisciplinary methods aimed at responsible innovation

Opportunities to Learn Mathematics Pedagogy and Connect Classroom Learning to Practice: A Study of Future Teachers in the United States and Singapore

In this study, we conducted secondary analyses using the TEDS-M database to explore future mathematics specialists teachers’ opportunities to learn (OTL) how to teach mathematics. We applied latent class analysis techniques to differentiate among groups of prospective mathematics specialists with potentially different OTL mathematics pedagogy within the United States and Singapore. Within the United States, three subgroups were identified: (a) Comprehensive OTL, (b) Limited OTL, and (c) OTL Mathematics Pedagogy. Within Singapore, four subgroups were identified: (a) Comprehensive OTL, (b) Limited Opportunities to Connect Classroom Learning with Practice, (c) OTL Mathematics Pedagogy, and (d) Basic OTL. Understanding the opportunities different prospective teachers had to learn from and their experiences with different components of instructional practice in university and practicum settings has implications for teacher preparation programs

Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

<p>Abstract</p> <p>Background</p> <p>With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality.</p> <p>Results</p> <p>Motivated by inferring transcriptional compensation (TC) interactions in yeast, a stepwise structural equation modeling algorithm (SSEM) is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations) from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC) SSEM works best. SSEM with Bayesian information criterion (BIC) results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions) rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1) small groups of genes that are synthetic sick or lethal (SSL) to SGS1, and (2) a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1), SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2) are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted.</p> <p>Conclusion</p> <p>SSEM is a useful tool for inferring genetic networks, and the results reinforce the possibility of predicting pathways of protein complexes via genetic interactions.</p