Acceleration of the Multiple-Try Metropolis algorithm using antithetic and stratified sampling

The Multiple-Try Metropolis is a recent extension of the Metropolis algorithm in which the next state of the chain is selected among a set of proposals. We propose a modification of the Multiple-Try Metropolis algorithm which allows for the use of correlated proposals, particularly antithetic and stratified proposals. The method is particularly useful for random walk Metropolis in high dimensional spaces and can be used easily when the proposal distribution is Gaussian. We explore the use of quasi Monte Carlo (QMC) methods to generate highly stratified samples. A series of examples is presented to evaluate the potential of the method.     

On dynamic stochastic approximation

The behaviour of the dynamic stochastic approximation algorithm suggested by DUPA[Cbreve] [4, 5] is examined under various conditions. Essentially, convergence in q.m. is proved and the rate of convergence is obtained for three classes of regression functions. Necessary and sufficient conditions are established for the convergence in q.m. of the algorithm in terms of the algorithm parameters for the stationary (nondynamic) case.     

Nonparametric covariate adjustment for receiver operating characteristic curves

The accuracy of a diagnostic test is typically characterized using the receiver operating characteristic (ROC) curve. Summarizing indexes such as the area under the ROC curve (AUC) are used to compare different tests as well as to measure the difference between two populations. Often additional information is available on some of the covariates which are known to influence the accuracy of such measures. The authors propose nonparametric methods for covariate adjustment of the AUC. Models with normal errors and possibly non‐normal errors are discussed and analyzed separately. Nonparametric regression is used for estimating mean and variance functions in both scenarios. In the model that relaxes the assumption of normality, the authors propose a covariate‐adjusted Mann–Whitney estimator for AUC estimation which effectively uses available data to construct working samples at any covariate value of interest and is computationally efficient for implementation. This provides a generalization of the Mann–Whitney approach for comparing two populations by taking covariate effects into account. The authors derive asymptotic properties for the AUC estimators in both settings, including asymptotic normality, optimal strong uniform convergence rates and mean squared error (MSE) consistency. The MSE of the AUC estimators was also assessed in smaller samples by simulation. Data from an agricultural study were used to illustrate the methods of analysis. The Canadian Journal of Statistics 38:27–46; 2010 © 2009 Statistical Society of Canada     

Nonparametric imputation method for nonresponse in surveys

Statistical Methods & Applications - Many imputation methods are based on a statistical model that assumes the variable of interest is a noisy observation of a function of the auxiliary...     

An Attitude Model of Environmental Action: Evidence from Developing and Developed Countries

Social Indicators Research - This paper analyzes the determinants of stated individual support towards environmental action. The analysis is realized by means of an original Partial Least Squares...     

FEAR OF NOVELTY: A MODEL OF SCIENTIFIC DISCOVERY WITH STRATEGIC UNCERTAINTY

This paper analyzes the production of fundamental research as a coordination game played by scholars. In the model, scholars decide to adopt a new idea only if they believe that a critical mass of peers is following a similar research strategy. If researchers observe only a noisy idiosyncratic signal of the true scientific potential of a new idea, we show that the game presents a single threshold equilibrium. In this environment, fundamental research proceeds with large structural breaks followed by long periods of time in which new ideas are unsuccessful. The likelihood of a new idea emerging depends on various parameters, including the rewards of working in the old paradigm, the critical mass of researchers required to create a new school of thought and scholars' ability to properly assess the scientific value of new ideas. (JEL O31, C72, A14)     

Reviews

Theory and Decision -     

A Qualitative Analysis of Requests for Financial Help via GoFundMe by Victims of Intimate Partner Violence

Abstract

Research suggests that a lack of financial resources contributes to victims of intimate partner violence (IPV) both remaining in and returning to abusive intimate relationships. Requesting financial assistance via crowdfunding has emerged as a new alternative for victims of IPV to access financial assistance. Therefore, our study explores how victims of IPV frame requests for financial assistance via the crowdfunding website GoFundMe.com. We qualitatively analyze a sample of 27 women’s requests. We find that victims of IPV may internalize the stigma of seeking assistance and therefore actively work to redefine their character in a positive manner. We also discover that victims’ requests speak to guidelines reflected in aid-based organizations and to judgments they anticipate facing when requesting help from informal social ties. Our findings suggest that seeking financial assistance through crowd funding may reflect similar challenges of accessing help through more traditional avenues.