Diagnostic tools for hierarchical linear models

An investigation of the modulatory effects of empathic and autistic traits on emotional and facial motor responses during live social interactions

A close relationship between emotional contagion and spontaneous facial mimicry has been theoretically proposed and is supported by empirical data. Facial expressions are essential in terms of both emotional and motor synchrony. Previous studies have demonstrated that trait emotional empathy enhanced spontaneous facial mimicry, but the relationship between autistic traits and spontaneous mimicry remained controversial. Moreover, previous studies presented faces that were static or videotaped, which may lack the "liveliness" of real-life social interactions. We addressed this limitation by using an image relay system to present live performances and pre-recorded videos of smiling or frowning dynamic facial expressions to 94 healthy female participants. We assessed their subjective experiential valence and arousal ratings to infer the amplitude of emotional contagion. We measured the electromyographic activities of the zygomaticus major and corrugator supercilii muscles to estimate spontaneous facial mimicry. Individual differences measures included trait emotional empathy (empathic concern) and the autism-spectrum quotient. We did not find that live performances enhanced the modulatory effect of trait differences on emotional contagion or spontaneous facial mimicry. However, we found that a high trait empathic concern was associated with stronger emotional contagion and corrugator mimicry. We found no two-way interaction between the autism spectrum quotient and emotional condition, suggesting that autistic traits did not modulate emotional contagion or spontaneous facial mimicry. Our findings imply that previous findings regarding the relationship between emotional empathy and emotional contagion/spontaneous facial mimicry using videos and photos could be generalized to real-life interactions.

Electromyographic Validation of Spontaneous Facial Mimicry Detection Using Automated Facial Action Coding

Although electromyography (EMG) remains the standard, researchers have begun using automated facial action coding system (FACS) software to evaluate spontaneous facial mimicry despite the lack of evidence of its validity. Using the facial EMG of the zygomaticus major (ZM) as a standard, we confirmed the detection of spontaneous facial mimicry in action unit 12 (AU12, lip corner puller) via an automated FACS. Participants were alternately presented with real-time model performance and prerecorded videos of dynamic facial expressions, while simultaneous ZM signal and frontal facial videos were acquired. Facial videos were estimated for AU12 using FaceReader, Py-Feat, and OpenFace. The automated FACS is less sensitive and less accurate than facial EMG, but AU12 mimicking responses were significantly correlated with ZM responses. All three software programs detected enhanced facial mimicry by live performances. The AU12 time series showed a roughly 100 to 300 ms latency relative to the ZM. Our results suggested that while the automated FACS could not replace facial EMG in mimicry detection, it could serve a purpose for large effect sizes. Researchers should be cautious with the automated FACS outputs, especially when studying clinical populations. In addition, developers should consider the EMG validation of AU estimation as a benchmark.

Enhanced Mirror Neuron Network Activity and Effective Connectivity during Live Interaction Among Female Subjects

Facial expressions are indispensable in daily human communication. Previous neuroimaging studies investigating facial expression processing have presented pre-recorded stimuli and lacked live face-to-face interaction. Our paradigm alternated between presentations of real-time model performance and pre-recorded videos of dynamic facial expressions to participants. Simultaneous functional magnetic resonance imaging (fMRI) and facial electromyography activity recordings, as well as post-scan valence and arousal ratings were acquired from 44 female participants. Live facial expressions enhanced the subjective valence and arousal ratings as well as facial muscular responses. Live performances showed greater engagement of the right posterior superior temporal sulcus (pSTS), right inferior frontal gyrus (IFG), right amygdala and right fusiform gyrus, and modulated the effective connectivity within the right mirror neuron system (IFG, pSTS, and right inferior parietal lobule). A support vector machine algorithm could classify multivoxel activation patterns in brain regions involved in dynamic facial expression processing in the mentalizing networks (anterior and posterior cingulate cortex). These results indicate that live social interaction modulates the activity and connectivity of the right mirror neuron system and enhances spontaneous mimicry, further facilitating emotional contagion.

Effects of Compounded Nonnormality of Residuals in Hierarchical Linear Modeling

While hierarchical linear modeling is often used in social science research, the assumption of normally distributed residuals at the individual and cluster levels can be violated in empirical data. Previous studies have focused on the effects of nonnormality at either lower or higher level(s) separately. However, the violation of the normality assumption simultaneously across all levels could bias parameter estimates in unforeseen ways. This article aims to raise awareness of the drawbacks associated with compounded nonnormality residuals across levels when the number of clusters range from small to large. The effects of the breach of the normality assumption at both individual and cluster levels were explored. A simulation study was conducted to evaluate the relative bias and the root mean square of the model parameter estimates by manipulating the normality of the data. The results indicate that nonnormal residuals have a larger impact on the random effects than fixed effects, especially when the number of clusters and cluster size are small. In addition, for a simple random-effects structure, the use of restricted maximum likelihood estimation is recommended to improve parameter estimates when compounded residuals across levels show moderate nonnormality, with a combination of small number of clusters and a large cluster size.

Conducting and Evaluating Multilevel Studies: Recommendations, Resources, and a Checklist

Multilevel methods allow researchers to investigate relationships that expand across levels (e.g., individuals, teams, and organizations). The popularity of these methods for studying organizational phenomena has increased in recent decades. Methodologists have examined how these methods work under different conditions, providing an empirical base for making sound decisions when using these methods. In this article, we provide recommendations, tools, resources, and a checklist that can be useful for scholars involved in conducting or assessing multilevel studies. The focus of our article is on two-level designs, in which Level-1 entities are neatly nested within Level-2 entities, and top-down effects are estimated. However, some of our recommendations are also applicable to more complex multilevel designs.

Ecological Predictors of Human Malaria Risk During Different Phases of the Elimination: An Analysis of Historical Data

To understand the evolutionary ecology of disease dynamics, it is crucial to identify the environmental factors that mediate the spread and abundance of parasites and their vectors. However, human-mediated changes in the biotic and abiotic environment and intervention programs are intensifying in the past 30-40 years at a rate that masks the causal effect of the original ecological predictors. In this study, we used archived epidemiological data spanning over 100 years on malaria risk in Hungary to demonstrate that different associations exist between infection risk and environmental predictors during different phases of the elimination program. In the early 20th century, when malaria was quite common in the country and no defense program was operating, as predicted, there was a positive relationship between the area of flooded habitats and the intensity of malaria infection. In contrast, this relationship was absent during middle of the century, when an effective elimination program was already in effect. Furthermore, malaria morbidity in a given year was predicted by the degree of stagnant water cover of the previous year when considering the period before the launch of a drastic mosquito control program by dichloro-diphenyl-trichloroethane (DDT), whereas such relationship could not be revealed for a latter period. Our results highlight that human-induced alterations of the socioecological environment considerably reorganizes the ecological landscape of pathogens and their vectors.

MHC-mediated sexual selection on birdsong: Generic polymorphism, particular alleles and acoustic signals

Several hypotheses predict that the major histocompatibility complex (MHC) drives mating preference in females. Olfactory, colour or morphological traits are often found as reliable signals of the MHC profile, but the role of avian song mediating MHC-based female choice remains largely unexplored. We investigated the relationship between several MHC and acoustic features in the collared flycatcher (Ficedula albicollis), a European passerine with complex songs. We screened a fragment of the class IIB second exon of the MHC molecule, of which individuals harbour 4-15 alleles, while considerable sequence diversity is maintained at the population level. To make statistical inferences from a large number of comparisons, we adopted both null-hypothesis testing and effect size framework in combination with randomization procedures. After controlling for potential confounding factors, neither MHC allelic diversity nor the presence of particular alleles was associated remarkably with the investigated qualitative and quantitative song traits. Furthermore, genetic similarity among males based on MHC sequences was not reflected by the similarity in their song based on syllable content. Overall, these results suggest that the relationship between features of song and the allelic composition and diversity of MHC is not strong in the studied species. However, a biologically motivated analysis revealed that individuals that harbour an MHC allele that impairs survival perform songs with broader frequency range. This finding suggests that certain aspects of the song may bear reliable information concerning the MHC profile of the individuals, which can be used by females to optimize mate choice.

Diagnostics for generalized linear hierarchical models in network meta-analysis

Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix

Background

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance–covariance matrix. However, obtaining the prediction error variance–covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance–covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance–covariance matrix of estimated contemporary group fixed effects.

Results

In this paper, we show that a correction to the variance–covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance–covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance–covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances.

Conclusions

Our method allows for the calculation of a connectedness measure based on the prediction error variance–covariance matrix by calculating only the variance–covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-017-0302-9) contains supplementary material, which is available to authorized users.