Relative effect sizes for measures of risk

Effect sizes are an important component of experimental design, data analysis, and interpretation of statistical results. In some situations, an effect size of clinical or practical importance may be unknown to the researcher. In other situations, the researcher may be interested in comparing observed effect sizes to known standards to quantify clinical importance. In these cases, the notion of relative effect sizes (small, medium, large) can be useful as benchmarks. Although there is generally an extensive literature on relative effect sizes for continuous data, little of this research has focused on relative effect sizes for measures of risk that are common in epidemiological or biomedical studies. The aim of this paper, therefore, is to extend existing relative effect sizes to the relative risk, odds ratio, hazard ratio, rate ratio, and Mantel–Haenszel odds ratio for related samples. In most scenarios with equal group allocation, effect sizes of 1.22, 1.86, and 3.00 can be taken as small, medium, and large, respectively. The odds ratio for a non rare event is a notable exception and modified relative effect sizes are 1.32, 2.38, and 4.70 in that situation.     

Risk aversion and equilibrium selection in a vertical contracting setting: an experiment

Theory and Decision - The theoretical literature on vertical relationships usually assumes that beliefs about secret contracts take specific forms. In a recent paper, Eguia et al. (Games Econ Behav...     

Does the Mission of an Organization Affect the Quality of Low-Skilled Jobs in Quasi-markets?: A Comparison Between Social Enterprises and For-Profit Organizations

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - In recent decades, many countries have witnessed the introduction of quasi-market regulation, predominantly in the field...     

A breakpoint detection in the mean model with heterogeneous variance on fixed time intervals

Statistics and Computing - This work is motivated by an application for the homogenization of global navigation satellite system (GNSS)-derived integrated water vapour series. Indeed, these series...     

Risk Assessment of Listeriosis Linked to the Consumption of Two Soft Cheeses Made from Raw Milk: Camembert of Normandy and Brie of Meaux

This article reports a quantitative risk assessment of human listeriosis linked to the consumption of soft cheeses made from raw milk. Risk assessment was based on data purposefully acquired inclusively over the period 2000-2001 for two French cheeses, namely: Camembert of Normandy and Brie of Meaux. Estimated Listeria monocytogenes concentration in raw milk was on average 0.8 and 0.3 cells/L, respectively, in Normandy and Brie regions. A Monte Carlo simulation was used to account for the time-temperature history of the milk and cheeses from farm to table. It was assumed that cell progeny did not spread within the solid cheese matrix (as they would be free to do in liquid broth). Interaction between pH and temperature was accounted for in the growth model. The simulated proportion of servings with no L. monocytogenes cell was 88% for Brie and 82% for Camembert. The 99th percentile of L. monocytogenes cell numbers in servings of 27 g of cheese was 131 for Brie and 77 for Camembert at the time of consumption, corresponding respectively to three and five cells of L. monocytogenes per gram. The expected number of severe listeriosis cases would be < or =10(-3) and < or =2.5 x 10(-3) per year for 17 million servings of Brie of Meaux and 480 million servings of Camembert of Normandy, respectively.     

Model-based hierarchical clustering with Bregman divergences and Fishers mixture model: application to depth image analysis

Model-based clustering is a method that clusters data with an assumption of a statistical model structure. In this paper, we propose a novel model-based hierarchical clustering method for a finite statistical mixture model based on the Fisher distribution. The main foci of the proposed method are: (a) provide efficient solution to estimate the parameters of a Fisher mixture model (FMM); (b) generate a hierarchy of FMMs and (c) select the optimal model. To this aim, we develop a Bregman soft clustering method for FMM. Our model estimation strategy exploits Bregman divergence and hierarchical agglomerative clustering. Whereas, our model selection strategy comprises a parsimony-based approach and an evaluation graph-based approach. We empirically validate our proposed method by applying it on simulated data. Next, we apply the method on real data to perform depth image analysis. We demonstrate that the proposed clustering method can be used as a potential tool for unsupervised depth image analysis.     

The Impact of Family Policies on Fertility Trends in Developed Countries

We examine how strongly fertility trends respond to family policies in OECD countries. In the light of the recent fertility rebound observed in several OECD countries, we empirically test the impact of different family policy instruments on fertility, using macro panel data from 18 OECD countries that spans the years 1982–2007. Our results confirm that each instrument of the family policy package (paid leave, childcare services and financial transfers) has a positive influence on average, suggesting that the combination of these forms of support for working parents during their children’s early years is likely to facilitate parents’ choice to have children. Policy levers do not all have the same weight, however: in-cash benefits covering childhood after the year of childbirth and the provision of childcare services for children under age three have a larger potential influence on fertility than leave entitlements and benefits granted around childbirth. Moreover, we find that the influence of each policy measure varies across different family policy contexts. Our findings are robust after controlling for birth postponement, endogeneity, time-lagged fertility reactions and for different aspects of national contexts, such as female labour market participation, unemployment, labour market protection and the proportion of children born out of marriage.     

Welfare, labor supply and heterogeneous preferences: evidence for Europe and the US

Following the report of the Stiglitz Commission, measuring and comparing well-being across countries has gained renewed interest. Yet, analyses that go beyond income and incorporate non-market dimensions of welfare most often rely on the assumption of identical preferences to avoid the difficulties related to interpersonal comparisons. In this paper, we suggest an international comparison based on individual welfare rankings that fully retain preference heterogeneity. Focusing on the consumption-leisure trade-off, we estimate discrete choice labor supply models using harmonized microdata for 11 European countries and the US. We retrieve preference heterogeneity within and across countries and analyze several welfare criteria which take into account that differences in income are partly due to differences in tastes. The resulting welfare rankings clearly depend on the normative treatment of preference heterogeneity with alternative metrics. We show that these differences can indeed be explained by estimated preference heterogeneity across countries—rather than demographic composition.     

Nonparametric Instrumental Variable Estimation of Structural Quantile Effects

We study the asymptotic distribution of Tikhonov regularized estimation of quantile structural effects implied by a nonseparable model. The nonparametric instrumental variable estimator is based on a minimum distance principle. We show that the minimum distance problem without regularization is locally ill‐posed, and we consider penalization by the norms of the parameter and its derivatives. We derive pointwise asymptotic normality and develop a consistent estimator of the asymptotic variance. We study the small sample properties via simulation results and provide an empirical illustration of estimation of nonlinear pricing curves for telecommunications services in the United States.