Prosocial behavior in families: Moderators of resource sharing

Archival studies of within-family prosocial behavior (Judge & Hrdy, 1992; Smith, Kish, & Crawford, 1987) have shown that inheritance patterns support Hamilton’s (1964) theory of inclusive fitness, such that people will more of their estates to relatives of closer genetic relatedness. In a survey-based simulation of these studies, students allocated one of three lotteries to their blood relatives. As expected, participants allocated greater proportions of their lotteries to relatives of greater genetic relatedness. This effect became stronger with decreasing lottery amounts. Relatives of certain relatedness were favored over relatives of uncertain relatedness (via paternal uncertainty), and this effect was stronger among those with less money to allocate. Male participants tended to favor their young female relatives over their young male relatives when given the smallest lottery, but this sex preference reversed when male participants were given the largest lottery. In general, scarcer resources led to more evolutionarily conservative investment strategies.     

Genetic Counseling for Fragile X Syndrome: Recommendations of the National Society of Genetic Counselors

The National Society of Genetic Counselors' (NSGC) recommendations for fragile X syndrome (FXS) genetic counseling are intended to assist health care professionals who provide genetic counseling for individuals and families in whom the diagnosis of FXS is strongly suspected or has been made. The recommendations are the opinions of genetic counselors with expertise in FXS counseling and are based on clinical experience, a review of pertinent English language medical articles, and reports of expert committees. These recommendations should not be construed as dictating an exclusive course of management, nor does use of such recommendations guarantee a particular outcome. These recommendations do not displace a health care provider's professional judgment based on the clinical circumstances of a particular client.     

A Method for Analyzing Videotaped Genetic Counseling Sessions

This study describes the development and evaluation of a multi-item scale for analyzing the genetic counseling process, the Manchester Observation Code (MOC) for genetic counseling. The instrument is specific to the field of genetic counseling and is designed for analysis of the communication between counselor and client. Coding is done directly from videotaped sessions. Because communication is the means by which genetic counseling is accomplished, the method measures four relevant components of communication: (1) grammatical form, (2) purpose, (3) subject, and (4) cue source. The instrument enables an observer to code the counselor's statements into these four components. Three videotaped sessions were used to measure interrater reliability, or the consistency of rating for each of the four communication domains using this method. Three videotaped sessions were also used to measure test-retest reliability, or the consistency of the designed method from one time to another. A total of 21 videotaped sessions were tested using the method. A statistical measure of reliability established consistency of the designed method; Cohen's kappa yielded 0.7 for interrater reliability and 0.79 for test-retest reliability. These findings suggest this instrument may be used to identify important elements of the genetic counseling process.     

Robust mean and covariance structure analysis through iteratively reweighted least squares

Robust schemes in regression are adapted to mean and covariance structure analysis, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is properly weighted according to its distance, based on first and second order moments, from the structural model. A simple weighting function is adopted because of its flexibility with changing dimensions. The weight matrix is obtained from an adaptive way of using residuals. Test statistic and standard error estimators are given, based on iteratively reweighted least squares. The method reduces to a standard distribution-free methodology if all cases are equally weighted. Examples demonstrate the value of the robust procedure.The authors acknowledge the constructive comments of three referees and the Editor that lead to an improved version of the paper. This work was supported by National Institute on Drug Abuse Grants DA01070 and DA00017 and by the University of North Texas Faculty Research Grant Program.     

Information matrix estimation procedures for cognitive diagnostic models

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance.     

Four Covariance Structure Models for Canonical Correlation Analysis: A COSAN Modeling Approach

The mathematical connection between canonical correlation analysis (CCA) and covariance structure analysis was first discussed through the Multiple Indicators and Multiple Causes (MIMIC) approach. However, the MIMIC approach has several technical and practical challenges. To address these challenges, a comprehensive COSAN modeling approach is proposed. Specifically, we define four COSAN-CCA models to correspond with four possible combinations of the data to be analyzed and the unique parameters to be estimated. In terms of the data, one can analyze either the unstandardized or standardized variables. In terms of the unique parameters, one can estimate either the weights or loadings. Besides the unique parameters of each COSAN-CCA model, all four COSAN-CCA models also estimate the canonical correlations as their common parameters. Taken together, the four COSAN-CCA models provide the correct point estimates and standard error estimates for all commonly used CCA parameters. Two numeric examples are used to compare the standard error estimates obtained from the MIMIC approach and the COSAN modeling approach. Moreover, the standard error estimates from the COSAN modeling approach are validated by a simulation study and the asymptotic theory. Finally, software implementation and future extensions are discussed.     

Analysis of regional environment and regional innovation strategy based on cybernetics

In this paper, based on the perspective of carbon emissions, the regional environment and regional innovation strategies were analyzed by using cybernetics. The main idea was to calibrate the diesel engine simulation model with predictive function based on the data collected from the bench test, and then according to the simulation model, the genetic algorithm was applied to optimize the EGR parameters and fuel injection parameters with the target of emission generation and output torque. First of all, the combustion process and emission performance of diesel engine with internal exhaust re-circulation were studied by genetic algorithm, and the genetic algorithm model was constructed. Then, the genetic algorithm program was written based on Matlab. In addition, taking the NOx emission as the target, and the Soot emission and the output torque of the original machine as constraints, through the joint simulation of Matlab and GT-Power, the EGR parameters and fuel injection parameters of the 10% to 50% load conditions were optimized at the speed of 1500 r/min and 2000 r/min. Finally, the validity of this method was verified and analyzed.     

Age differences in the neural response to negative feedback

Affective processing is one domain that remains relatively intact in healthy aging. Investigations into the neural responses associated with reward anticipation have revealed that older and younger adults recruit the same midbrain reward regions, but other evidence suggests this recruitment may differ depending on the valence (gain, loss) of the incentive cue. The goal of the current study was to examine functional covariance during gain and loss feedback in younger and healthy older adults. A group of 15 older adults (mean age = 68.5) and 16 younger adults (mean age = 25.4) completed a revised Monetary Incentive Delay task (rMID; Knutson, Westdorp, Kaiser, &; Hommer, 2000) while in the fMRI scanner. The rMID is a reaction time task where successful performance, either gaining a reward or avoiding a loss, is defined by hitting a button during the brief presentation of a visual target. Participants receive gain and loss anticipation cues before each trial and feedback after each trial with four possible outcomes: +$5.00, +0.00, -$5.00, and -Affective processing is one domain that remains relatively intact in healthy aging. Investigations into the neural responses associated with reward anticipation have revealed that older and younger adults recruit the same midbrain reward regions, but other evidence suggests this recruitment may differ depending on the valence (gain, loss) of the incentive cue. The goal of the current study was to examine functional covariance during gain and loss feedback in younger and healthy older adults. A group of 15 older adults (mean age = 68.5) and 16 younger adults (mean age = 25.4) completed a revised Monetary Incentive Delay task (rMID; Knutson, Westdorp, Kaiser, & Hommer, 2000) while in the fMRI scanner. The rMID is a reaction time task where successful performance, either gaining a reward or avoiding a loss, is defined by hitting a button during the brief presentation of a visual target. Participants receive gain and loss anticipation cues before each trial and feedback after each trial with four possible outcomes: +$5.00, +0.00, -$5.00, and -$0.00. Using seed-voxel partial least squares analyses, with seed voxels in the caudate and ventromedial prefrontal cortex, whole-brain functional covariance revealed that younger and older adults engage the same network of regions to support general feedback processing. However, older adults engaged two additional networks to support processing of negative feedback, gain_miss (+0), loss_miss (-$5), and loss_hit (?0), specifically. These findings are in line with theories of a positivity effect in aging and may have implications for reward-stimulus learning and decision making following performance-contingent negative feedback.     

Neuroticism and extraversion share genetic and environmental effects with negative and positive mood spillover in a nationally representative sample

Work-family spillover research focuses on how negative and positive moods in one life domain carry over to another. Domain-specific etiologies (e.g., family conflict) are often emphasized to explain spillover. Yet, strong correlations exist between spillover variables of the same emotional valence but originating from different domains, suggesting individual differences in the tendencies to prolong mood-states. The current study (N = 1143 individuals) examined whether these general tendencies are associated with neuroticism and extraversion and how genetic and environmental effects contribute to these associations. Findings revealed that neuroticism and extraversion are related to these tendencies through both genetic and environmental pathways.     

Differential Genetic and Environmental Influences on Reactive and Proactive Aggression in Children

While significant heritability for childhood aggression has been claimed, it is not known whether there are differential genetic and environmental contributions to proactive and reactive forms of aggression in children. This study quantifies genetic and environmental contributions to these two forms of aggression in an ethnically diverse urban sample of 9–10 year old twins (N = 1219), and compares results across different informants (child self-report, mother, and teacher ratings) using the Reactive–Proactive Aggression Questionnaire (RPQ). Confirmatory factor analysis of RPQ items indicated a significant and strong fit for a two-factor proactive–reactive model which was significantly superior to a one-factor model and which replicated across gender as well as the three informant sources. Males scored significantly higher than females on both self-report reactive and proactive aggression, findings that replicated on mother and teacher versions of the RPQ. Asian–Americans scored lower than most ethnic groups on reactive aggression yet were equivalent to Caucasians on proactive aggression. African–Americans scored higher than other ethnic groups on all measures of aggression except caregiver reports. Heritable influences were found for both forms of aggression across informants, but while boys’ self-reports revealed genetic influences on proactive (50%) and reactive (38%) aggression, shared and non-shared environmental influences almost entirely accounted for girls’ self-report reactive and proactive aggression. Although genetic correlations between reactive and proactive aggression were significant across informants, there was evidence that the genetic correlation was less than unity in boys self reported aggression, indicating that genetic factors differ for proactive and reactive aggression. These findings provide the first evidence for varying genetic and environmental etiologies for reactive and proactive aggression across gender, and provide additional support for distinction between these two forms of aggression.