Bayesian regression under combinations of constraints

A Bayesian method for regression under several types of constraints is proposed. The constraints can be range-restricted and include shape restrictions, constraints on the value of the regression function, smoothness conditions and combinations of these types of constraints. The support of the prior distribution is included in the set of piecewise linear functions. It is shown that the proposed prior can be arbitrarily close to the distribution induced by the addition of a polynomial plus an (m−1)-fold integrated Brownian motion. Hence, despite its piecewise linearity, the regression function behaves (approximately) like an m−1 times continuously differentiable random function. Furthermore, thanks to the piecewise linear property, many combinations of constraints can easily be considered. The regression function is estimated by the posterior mode computed by a simulated annealing algorithm. The constraints on the shape and the values of the regression function are taken into account thanks to the proposal distribution, while the smoothness condition is handled by the acceptation step. Simulations from the posterior distribution are obtained by a Gibbs sampling algorithm.     

Use of Biological Markers in Risk Assessment1

Measurements of intermediate end points in the carcinogenic process may reduce uncertainty in human risk assessment from bioassay data, by identifying sources of interspecies variation and dose nonlinearity. This paper describes desirable properties of such markers: persistence, predictive power, temporal relevance, and consistency across dose rate and species. We illustrate these properties by evaluating markers for squamous cell nasal carcinoma in rodents exposed to formaldehyde. We also discuss design issues for bioassays that evaluate markers and tumors simultaneously at necropsy.     

Exact Goodness‐of‐Fit Testing for the Ising Model

The Ising model is one of the simplest and most famous models of interacting systems. It was originally proposed to model ferromagnetic interactions in statistical physics and is now widely used to model spatial processes in many areas such as ecology, sociology, and genetics, usually without testing its goodness of fit. Here, we propose various test statistics and an exact goodness‐of‐fit test for the finite‐lattice Ising model. The theory of Markov bases has been developed in algebraic statistics for exact goodness‐of‐fit testing using a Monte Carlo approach. However, finding a Markov basis is often computationally intractable. Thus, we develop a Monte Carlo method for exact goodness‐of‐fit testing for the Ising model that avoids computing a Markov basis and also leads to a better connectivity of the Markov chain and hence to a faster convergence. We show how this method can be applied to analyze the spatial organization of receptors on the cell membrane.     

Modeling Cholinesterase Activity for Human Dietary Risk Assessment of Carbamate Insecticides

This article demonstrates statistical models to quantify the interaction between a carbamate insecticide and acetylcholinesterase. Carbamates are a class of chemicals that inhibit the activity of acetylcholinesterase in humans, an enzyme involved in the regulation of the neurotransmitter acetylcholine. Following exposure to a carbamate insecticide, we specifically address (1) if acetylcholinesterase activity recovers to its level of preexposure activity; (2) the level of inhibition of acetylcholinesterase activity; (3) the recovery time of acetylcholinesterase activity to its preexposure level for a typical individual; and (4) the upper percentiles of the recovery time of acetycholinesterase activity across individuals. A nonlinear mixed-effects model is fitted to data from a repeated measures experiment conducted with human volunteers randomly assigned to a control and four dose groups. Repeated measurements were taken prior to exposure and at 1, 2, 4, 6, 8, and 21 hours after exposure to the carbamate aldicarb. It was found that full recovery did occur. Inhibition at 1 hour was estimated with maximum inhibition most likely occurring prior to 1-hour postexposure. In addition, recovery was rapid even for sensitive individuals. Given this information, the potential effect from exposure to a carbamate consumed in the diet during a day can be quantitatively assessed.     

A quadratic lower bound for Rocchio’s similarity-based relevance feedback algorithm with a fixed query updating factor

Rocchio’s similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised learning algorithm from examples. In practice, Rocchio’s algorithm often uses a fixed query updating factor. When this is the case, we strengthen the linear Ω(n) lower bound obtained by Chen and Zhu (Inf. Retr. 5:61–86, 2002) and prove that Rocchio’s algorithm makes Ω(k(n−k)) mistakes in searching for a collection of documents represented by a monotone disjunction of k relevant features over the n-dimensional binary vector space {0,1} ⁿ , when the inner product similarity measure is used. A quadratic lower bound is obtained when k is linearly proportional to n. We also prove an O(k(n−k)³) upper bound for Rocchio’s algorithm with the inner product similarity measure in searching for such a collection of documents with a constant query updating factor and a zero classification threshold.     

Modelling state anxiety in a medical setting: The mediating role of embarrassment

Abstract

Little research has been conducted on the relationship between state anxiety and embarrassment in a medical setting. In the prcsent study, several personality and situational variables were examined as antecedents of state anxiety. A total of 277 patients who had come for an examination either as a response to a melanoma screening programme or due to a dermatological complaint participated in the study. Results showed that purpose of patient visit, physician's recommendation, trait anxiety, and embarrassment, were each correlated with state anxiety. Furthermore, using mediated regression analysis as well as structural equations, embarrassment was found to mediate between the above antecedents and state anxiety. The authors proposed a model linking all the variables and identifying their paths. Theoretical and practical considerations of the findings are discussed.     

Improvement of contraception during the course of marriage

Contraceptive effectiveness is conventionally measured by a pregnancy rate, which reveals little about the way in which pregnancy risks vary among couples. In this paper a technique is presented for estimating curves of pregnancy risk. The technique is applied to data from the Family Growth in Metropolitan America study for purposes of estimating how much these couples would have to Improve their initial contraception In order to realize, by contraception alone, the calibre of family limitation claimed by respondents late in their childbearing period. A very substantial improvement Is estimated as necessary.

It Is also argued that the notable increase In contraceptive effectiveness before and after second birth, observed for couples desiring only two children is attributable mainly to a more regular practice of contraception. Changes Iin method preference, decline in average fecundabillty and increased contraceptive skill are viewed as secondary factors.     

A Caution on Comparisons

Abstract

The family is the foundation of our society. By learning about family life in other countries, we learn about our own lives and we realize that we all belong to one big family—the family of mankind. … [Studying families of the world] could help us to get closer to people in distant countries and support the knowledge that “we are one.” — Liv Ullmann, UNICEF Goodwill Ambassador     

Nonresponse in the American Time Use Survey: Who Is Missing from the Data and How Much Does It Matter?

This article examines nonresponse in a large government survey,the American Time Use Survey (ATUS), which interviews personsin households previously interviewed in the Current PopulationSurvey. The response rate for the ATUS has been below 60 percentfor the first two years of its existence, raising questionsabout whether the results can be generalized to the target population.The article begins with an analysis of the types of nonresponseencountered in the ATUS. Noncontact accounts for roughly 60percent of ATUS nonresponse, with refusals accounting for roughly40 percent. We find little support for the hypothesis that busypeople are less likely to respond to the ATUS but find considerablesupport for the hypothesis that people who are weakly integratedinto their communities are less likely to respond, mostly becausethey are less likely to be contacted. When we compare aggregateestimates of time use calculated using the ATUS base weightswithout any adjustment for nonresponse, estimates calculatedusing the ATUS final weights with a nonresponse adjustment,and estimates calculated using weights that incorporate ourown nonresponse adjustment based on a propensity model, we findsome modest differences, but the three sets of estimates arebroadly similar. The article ends with suggestions for furtherresearch and analysis.