A Hierarchical Bayesian Model for Measuring Motion Adaptation

Previous research has shown that motion imagery draws on the same neural circuits that are involved in perception of motion, thus leading to a motion aftereffect (Winawer et al., 2010). Imagined stimuli can induce a similar shift in participants’ psychometric functions as neural adaptation due to a perceived stimulus. However, these studies have been criticized on the grounds that they fail to exclude the possibility that the subjects might have guessed the experimental hypothesis, and behaved accordingly (Morgan et al., 2012). In particular, the authors claim that participants can adopt arbitrary response criteria, which results in similar changes of the central tendency μ of psychometric curves as those shown by Winawer et al. (2010).

A prediction model for assessing residential radon concentration in Switzerland

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.

Biodiversity effects on nitrate concentrations in soil solution: a Bayesian model

Ecosystems are faced with high rates of species loss which has consequences for their functions and services. To assess the effects of plant species diversity on the nitrogen (N) cycle, we developed a model for monthly mean nitrate (NO3-N) concentrations in soil solution in 0-30 cm mineral soil depth using plant species and functional group richness and functional composition as drivers and assessing the effects of conversion of arable land to grassland, spatially heterogeneous soil properties, and climate. We used monthly mean NO3-N concentrations from 62 plots of a grassland plant diversity experiment from 2003 to 2006. Plant species richness (1-60) and functional group composition (1-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Plant community composition, time since conversion from arable land to grassland, soil texture, and climate data (precipitation, soil moisture, air and soil temperature) were used to develop one general Bayesian multiple regression model for the 62 plots to allow an in-depth evaluation using the experimental design. The model simulated NO3-N concentrations with an overall Bayesian coefficient of determination of 0.48. The temporal course of NO3-N concentrations was simulated differently well for the individual plots with a maximum plot-specific Nash-Sutcliffe Efficiency of 0.57. The model shows that NO3-N concentrations decrease with species richness, but this relation reverses if more than approx. 25 % of legume species are included in the mixture. Presence of legumes increases and presence of grasses decreases NO3-N concentrations compared to mixtures containing only small and tall herbs. Altogether, our model shows that there is a strong influence of plant community composition on NO3-N concentrations.

Psychological adaptation to spousal loss in old age: The role of personality

Spousal loss is an inevitable critical life event for most individuals in old age, mostly associated with a negative impact on various well-being measures, ie. lower life satisfaction, higher rates of loneliness and depressive symptoms compared to married peers. While the negative effects on well-being are well documented in literature, the modifying factors accounting for the large variability in adaptation to loss are discussed controversially. The potential relevance of personality in the adaptation process has rarely been examined and findings regarding the role of time since loss are contradictory. Based on a vulnerability-stress-model this contribution aims a) to compare psychological well-being of bereaved individuals with married counterparts and b) to investigate the protective effects of different personality traits (Big Five, resilience), and the role of time since loss for adaptation in terms of life satisfaction, loneliness and depression. Data from a questionnaire study about the loss of a spouse in middle and old age in the German- and French-speaking parts of Switzerland are reported. The study is part of the Swiss National Centre of Competence in Research LIVES (Swiss National Science Foundation). The sample consists of 351 widowed persons (39% men, widowed since 0 - 5 years), and 605 married controls (50% men), aged 60 - 89 years. Group comparisons reveal the detrimental effect of spousal bereavement on all indicators of psychological adaptation. Results from hierarchical regression analyses show furthermore, that the effect of spousal loss on all psychological outcomes is moderated by personality traits. Separate analyses with the group of bereaved individuals suggest, that the protective effect of personality varies by the time passed since loss. Our results contribute to a better understanding of the variability in psychological adaptation to spousal loss in old age and give hints for counselling practice.

Teacher emotions in the classroom: Associations with students’ engagement, classroom discipline and the interpersonal teacher-student relationship

The present study explores teacher emotions, in particular how they are predicted by students’ behaviour and the interpersonal aspect of the teacher-student relationship (TSR). One hundred thirty-two secondary teachers participated in a quantitative study relying on self-report questionnaire data. Based on the model of teacher emotions by Frenzel (2014), teachers rated their experienced joy, anger and anxiety during classroom instruction (dependent variable). Students’ motivational behaviour (= engagement), socio-emotional behaviour (= discipline in class) and relational behaviour (= closeness; interpersonal TSR) were assessed as the independent variables. Teachers’ self-efficacy beliefs served as a control variable. Hierarchical regression analysis revealed that the interpersonal relationship formed between teachers and students was the strongest predictor for teachers’ joy (positive relation) and anxiety (negative relation), whereas lack of discipline in class best predicted teachers’ anger experiences. Students’ engagement also proved a significant predictor of teacher emotions. The results suggest that interpersonal TSR plays a particularly important role in teachers’ emotional experiences in class.

WGTTEST: Stata module to test the impact of sampling weights in regression analysis

wgttest performs a test proposed by DuMouchel and Duncan (1983) to evaluate whether the weighted and unweighted estimates of a regression model are significantly different.