Infinite mixture-of-experts model for sparse survival regression with application to breast cancer

BACKGROUND: We present an infinite mixture-of-experts model to find an unknown number of sub-groups within a given patient cohort based on survival analysis. The effect of patient features on survival is modeled using the Cox's proportionality hazards model which yields a non-standard regression component. The model is able to find key explanatory factors (chosen from main effects and higher-order interactions) for each sub-group by enforcing sparsity on the regression coefficients via the Bayesian Group-Lasso. RESULTS: Simulated examples justify the need of such an elaborate framework for identifying sub-groups along with their key characteristics versus other simpler models. When applied to a breast-cancer dataset consisting of survival times and protein expression levels of patients, it results in identifying two distinct sub-groups with different survival patterns (low-risk and high-risk) along with the respective sets of compound markers. CONCLUSIONS: The unified framework presented here, combining elements of cluster and feature detection for survival analysis, is clearly a powerful tool for analyzing survival patterns within a patient group. The model also demonstrates the feasibility of analyzing complex interactions which can contribute to definition of novel prognostic compound markers

The Effect of female leadership on establishment and employee outcomes: evidence from linked employer-employee data

In this paper we use a large linked employer-employee data set on German establishments between 1993 and 2012 to investigate how the gender composition of the top layer of management affects a variety of establishment and worker outcomes. We use two different measures to identify the gender composition of the top layer based on direct survey data: the fraction of women among top managers, and the fraction of women among working proprietors. We document the following facts: a) There is a strong negative association between the fraction of women in the top layer of management and several establishment outcomes, among them business volume, investment, total wage bill per worker, total employment, and turnover; b) Establishments with a high fraction of women in the top layer of management are more likely to implement female-friendly policies, such as providing childcare facilities or promoting and mentoring female junior staff; c) The fraction of women in the top layer of management is also negatively associated with employment and wages, both male and female, full-time and part-time. However, all of these associations vanish when we include establishment fixed effects and establishment-specific time trends. This reveals a substantial sorting of female managers across establishments: small and less productive establishments that invest less, pay their employees lower wages, but are more female-friendly are more likely to be led by women

Discounting Health and Money: New Evidence Using A More Robust Method

International audienceThis study compares discounting for money and health in a field study. We applied the direct method, which measures discounting independent of utility, in a representative French sample, interviewed at home by professional interviewers. We found more discounting for money than for health. The median discount rates (6.5% for money and 2.2 % for health) were close to market interest rates suggesting that the direct method solves the puzzle of unrealistically high discount rates typically observed in applied economics. Constant discounting fitted the data better than hyperbolic discounting. The substantial individual heterogeneity in discounting could be explained by age and occupation