The Role of Rape-Supportive Attitudes,Alcohol, and Sexual Arousal in Sexual (Mis)Perception: An Experimental Study

While sexual misperception does not irrevocably lead to sexual aggression, it remains a significant risk factor. The present study investigated the effects of rape-supportive attitudes, alcohol, and sexual arousal on sexual perception. We used a 2 × 2 between-participants factorial design to randomly assign 135 men from the general population to a condition with or without alcohol (blood alcohol concentration target of .08%) and to a condition with or without sexual arousal. Participants were asked to listen to an audiotape depicting a sexual interaction between a man and woman and to indicate if and when they believed the woman was no longer interested in having sex. Results, obtained through survival analyses, indicate that the effects of rape-supportive attitudes on sexual misperception are moderated by alcohol consumption. Alcohol appears to be an important situational factor for activating men’s implicit theories. Our study sheds new light on the role of knowledge structures in sexual perception: It identifies when, as well as suggesting how, rape-supportive attitudes may disturb sexual perception and ultimately lead to sexual misperception.     

Modeling spatial learning in rats based on Morris water maze experiments

The Morris water maze, developed by Morris (J Neurosci Methods 1984: 11: 47–60), is a behavioral experiment designed to test the spatial memory. When repeating the experiment several times, the changes in time (latency) and distance (path) taken to reach the platform are indicators for the learning and memory abilities of the rat. In juvenile toxicity studies, it is of interest to test whether dosing juvenile rats with some compound of interest has an effect on its learning ability. The traditional analysis uses non‐parametric tests to check for a possible dose‐effect. However, due to the many tests performed, this approach lacks power. Here, an alternative method is proposed, accounting for the longitudinal design of the study, the right‐censoring of observations when animals did not find the platform and the correlation between the time and distance taken to reach the platform. Copyright © 2009 John Wiley & Sons, Ltd.     

On Geometry and Scale of a Stochastic Chemostat

A chemostat is a fixed volume bioreactor in which micro–organisms are grown in a continuously renewed liquid medium. We propose a stochastic model for the evolution of the concentrations in the single species and single substrate case. It is obtained as a diffusion approximation of a pure jump Markov process, whose increments are comparable in mean with the deterministic model. A specific time scale, related to the noise intensity, is considered for each source of variation. The geometric structure of the problem, usable by identification procedures, is preserved both in the drift and diffusion term. We study the properties of this model by numerical experiments.     

Block‐threshold‐adapted Estimators via a Maxiset Approach

We study the maxiset performance of a large collection of block thresholding wavelet estimators, namely the horizontal block thresholding family. We provide sufficient conditions on the choices of rates and threshold values to ensure that the involved adaptive estimators obtain large maxisets. Moreover, we prove that any estimator of such a family reconstructs the Besov balls with a near‐minimax optimal rate that can be faster than the one of any separable thresholding estimator. Then, we identify, in particular cases, the best estimator of such a family, that is, the one associated with the largest maxiset. As a particularity of this paper, we propose a refined approach that models method‐dependent threshold values. By a series of simulation studies, we confirm the good performance of the best estimator by comparing it with the other members of its family.     

Multiple recapture methods when sampling without replacement in the last occasion

A technique is presented for estimating the size of a closed population from multiple recapture data when sampling is performed without replacement on the last trapping occasion. The estimator of the population size along with the variance estimator is derived from a log-linear model.     

Fast,closed-form,and efficient estimators for hierarchical models with AR(1) covariance and unequal cluster sizes

This article is concerned with statistically and computationally efficient estimation in a hierarchical data setting with unequal cluster sizes and an AR(1) covariance structure. Maximum likelihood estimation for AR(1) requires numerical iteration when cluster sizes are unequal. A near optimal non-iterative procedure is proposed. Pseudo-likelihood and split-sample methods are used, resulting in computing weights to combine cluster size specific parameter estimates. Results show that the method is statistically nearly as efficient as maximum likelihood, but shows great savings in computation time.     

The validation of surrogate end points by using data from randomized clinical trials: a case-study in advanced colorectal cancer

Summary.  In many therapeutic areas, the identification and validation of surrogate end points is of prime interest to reduce the duration and/or size of clinical trials. Buyse and co-workers and Burzykowski and co-workers have proposed a validation strategy for end points that are either normally distributed or (possibly censored) failure times. In this paper, we address the problem of validating an ordinal categorical or binary end point as a surrogate for a failure time true end point. In particular, we investigate the validity of tumour response as a surrogate for survival time in evaluating fluoropyrimidine-based experimental therapies for advanced colorectal cancer. Our analysis is performed on data from 28 randomized trials in advanced colorectal cancer, which are available through the Meta-Analysis Group in Cancer.