Flexible modelling of spatial variation in agricultural field trials with the R package INLA

The objective of this paper was to fit different established spatial models for analysing agricultural field trials using the open-source R package INLA. Spatial variation is common in field trials, and accounting for it increases the accuracy of estimated genetic effects. However, this is still hindered by the lack of available software implementations. We compare some established spatial models and show possibilities for flexible modelling with respect to field trial design and joint modelling over multiple years and locations. We use a Bayesian framework and for statistical inference the integrated nested Laplace approximations (INLA) implemented in the R package INLA. The spatial models we use are the well-known independent row and column effects, separable first-order autoregressive ( AR1⊗AR1 ) models and a Gaussian random field (Matérn) model that is approximated via the stochastic partial differential equation approach. The Matérn model can accommodate flexible field trial designs and yields interpretable parameters. We test the models in a simulation study imitating a wheat breeding programme with different levels of spatial variation, with and without genome-wide markers and with combining data over two locations, modelling spatial and genetic effects jointly. The results show comparable predictive performance for both the AR1⊗AR1 and the Matérn models. We also present an example of fitting the models to a real wheat breeding data and simulated tree breeding data with the Nelder wheel design to show the flexibility of the Matérn model and the R package INLA

Positions of interest groups towards labour market reforms in Germany : a novel content analysis of press releases

Unions, employers’ associations and social welfare organizations play an important part in reforming the labour market. This study investigates their positions in this policy field, in particular towards minimum wages and labour market regulations. Two contradicting arguments are outlined concerning the interest groups’ strategic interests. They have to represent their core membership and, at the same time, pursue strategic long-term goals that might contradict their clienteles’ interests. We estimate the interest groups’ positions with a content analysis. This method is regularly used for political parties but has not been applied to interest groups so far. About 1500 press releases from 14 organizations serve as our data source. We find that unions pursue different strategies depending on their (potential) membership. The service union strongly advocate the introduction of a minimum wage while industrial unions focus on stricter regulation of atypical contracts. Employers’ associations generally oppose minimum wages but their main priority is defending the flexibility of agency work. The positions of social welfare organizations are shaped by their dual role as representative of the marginalized and as employers in the social sector. Overall, we show that content analysis is a valuable tool to analyse positions of interest groups