Survival Modelling for Data From Combined Cohorts: Opening the Door to Meta Survival Analyses and Survival Analysis Using Electronic Health Records

Non-parametric estimation of the survival function using observed failure time data depends on the underlying data generating mechanism, including the ways in which the data may be censored and/or truncated. For data arising from a single source or collected from a single cohort, a wide range of estimators have been proposed and compared in the literature. Often, however, it may be possible, and indeed advantageous, to combine and then analyse survival data that have been collected under different study designs. We review non-parametric survival analysis for data obtained by combining the most common types of cohort. We have two main goals: (i) to clarify the differences in the model assumptions and (ii) to provide a single lens through which some of the proposed estimators may be viewed. Our discussion is relevant to the meta-analysis of survival data obtained from different types of study, and to the modern era of electronic health records.     

Are cooperatives gender sensitive? A confirmatory and predictive analysis of women's collective entrepreneurship

The literature on entrepreneurship has developed a huge body of fruitful research to explain why women do not engage in business as often as men. However, relatively little is known about the role that different business models may play in driving women's entrepreneurial activity, which is examined in this study. In this paper we develop a model to empirically test the relationship between women's motivations to become entrepreneurs and their willingness to embark on business through cooperatives, a particular organizational model. We find that the fit between women's needs and expectations and the guiding principles of cooperatives is decisive for the materialization of female entrepreneurship. Furthermore, we explore the role that institutions can play in fostering this link. In doing so, we extend the literature on women's entrepreneurship by highlighting key factors to better channel the development of this potential resource for economic development. Our confirmatory model highlights the role of cooperatives as a type of organization particularly suited to the interests and needs of women entrepreneurs. Thus, the promotion of this business model can be useful to improve the number of women entrepreneurs and, in turn, enhance economic development.     

The relationship between business characteristics and ICT deployment in the rural tourism sector. The case of Spain

The deployment of information and communication technologies (ICT) is crucial for the competitiveness of rural tourism businesses. It is therefore important to know the relation between a firm's characteristics and ICT deployment. This study makes two hierarchical segmentations to predict the behaviour of these firms when deploying the Web and e‐mail. This work determines which characteristics are related to ICT deployment. Activity and category are the two characteristics that most effectively predict a firm's behaviour, whereas location and size are less effective. These results have implications for entrepreneurial behaviour and for public agents working in rural tourism. Copyright © 2009 John Wiley & Sons, Ltd.     

BargCrEx: A System for Bargaining Based Aggregation of Crowd and Expert Opinions in Crowdsourcing

Group Decision and Negotiation - Crowdsourcing and crowd voting systems are being increasingly used in societal, industry, and academic problems (labeling, recommendations, social choice, etc.) due...     

Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty

Macroeconomic data are subject to data revisions. Yet, the usual way of generating real-time density forecasts from Bayesian Vector Autoregressive (BVAR) models makes no allowance for data uncertainty from future data revisions. We develop methods of allowing for data uncertainty when forecasting with BVAR models with stochastic volatility. First, the BVAR forecasting model is estimated on real-time vintages. Second, the BVAR model is jointly estimated with a model of data revisions such that forecasts are conditioned on estimates of the ‘true’ values. We find that this second method generally improves upon conventional practice for density forecasting, especially for the United States.