Processes,procedures and journal development: Past,present and future

This paper is written as an overview of developments relating to the Journal. The authors explain the background to their editorship and the plans and structures they implemented. They provide a progress report and also discuss the process of running the Journal so as to explain to potential authors how the systems operate and the philosophy of the Journal.     

The Undisciplined Youth and a Moral Panic in Independent India,Circa 1947-1964

The undisciplined youth is one figure that is key to understanding the 1950s and 1960s in India. Politicians, officials, academics, youth leaders, and journalists developed and spread a discourse that imagined the collective behaviour of Indian youths as falling well below adult expectations of them in independent India. The imagery of the youth lacking in discipline was tied up with cycles of student unrest and the idea that the methods of protest used during the pre-independence period had wrongly continued into the post-independence period, but this discursive formation was often extended to include all Indian youths and it became translated into a long-term anxiety about the future of the newly established nation-state. These tropes about the undisciplined Indian youth became a symbol of the country's unresolved future. Unless the crisis of youth could be remedied, the narrative went, then the potentiality of Indian independence and its first generation of citizens could never be realised. This discourse took on a novel and distinctive shape during the initial years following Indian independence in 1947, it crystallised during the early 1950s, and there was a continued build-up of public concern that lasted throughout the 1960s.     

Moment closure based parameter inference of stochastic kinetic models

Parameter inference for stochastic kinetic models is a topic that spans many disciplines. Although it is possible to carry out exact inference using partial observations of a stochastic process, it is often computationally impractical. In this paper we use the moment closure approximation of the underlying stochastic process as a fast approximation of the likelihood. We show that this approximation is fast and accurate, even when the population numbers are small.     

Using the EM algorithm for Bayesian variable selection in logistic regression models with related covariates

We develop a Bayesian variable selection method for logistic regression models that can simultaneously accommodate qualitative covariates and interaction terms under various heredity constraints. We use expectation-maximization variable selection (EMVS) with a deterministic annealing variant as the platform for our method, due to its proven flexibility and efficiency. We propose a variance adjustment of the priors for the coefficients of qualitative covariates, which controls false-positive rates, and a flexible parameterization for interaction terms, which accommodates user-specified heredity constraints. This method can handle all pairwise interaction terms as well as a subset of specific interactions. Using simulation, we show that this method selects associated covariates better than the grouped LASSO and the LASSO with heredity constraints in various exploratory research scenarios encountered in epidemiological studies. We apply our method to identify genetic and non-genetic risk factors associated with smoking experimentation in a cohort of Mexican-heritage adolescents.     

A network epidemic model for online community commissioning data

A statistical model assuming a preferential attachment network, which is generated by adding nodes sequentially according to a few simple rules, usually describes real-life networks better than a model assuming, for example, a Bernoulli random graph, in which any two nodes have the same probability of being connected, does. Therefore, to study the propagation of “infection” across a social network, we propose a network epidemic model by combining a stochastic epidemic model and a preferential attachment model. A simulation study based on the subsequent Markov Chain Monte Carlo algorithm reveals an identifiability issue with the model parameters. Finally, the network epidemic model is applied to a set of online commissioning data.