Gradual growth versus shape invariance in perceptual decision making.

A dominant theme in modeling human perceptual judgments is that sensory neural activity is summed or integrated until a critical bound is reached. Such models predict that, in general, the shape of response time distributions change across conditions, although in practice, this shape change may be subtle. An alternative view is that response time distributions are shape invariant across conditions or groups.

Bayesian t tests for accepting and rejecting the null hypothesis.

Progress in science often comes from discovering invariances in relationships among variables; these invariances often correspond to null hypotheses. As is commonly known, it is not possible to state evidence for the null hypothesis in conventional significance testing. Here we highlight a Bayes factor alternative to the conventional t test that will allow researchers to express preference for either the null hypothesis or the alternative.

A hierarchical process-dissociation model.

In fitting the process-dissociation model (L. L. Jacoby, 1991) to observed data, researchers aggregate outcomes across participant, items, or both.

Detecting chance: a solution to the null sensitivity problem in subliminal priming.

In many paradigms, the persuasiveness of subliminal priming relies on establishing that stimuli are undetectable. The standard significance test approach is ill-suited as null results may reflect either truly undetectable stimuli or a lack of power to resolve weakly detectable stimuli. We present a novel statistical model as an alternative.

Hierarchical models for the probabilities of conception.

In the last thirty years, there has been considerable interest in finding better models to fit data for probabilities of conception. An important early model was proposed by Barrett and Marshall (1969) and extended by Schwartz, MacDonald and Heuchel (1980). Recently, researchers have further extended these models by adding covariates.

A comment on Heathcote, Brown, and Mewhort's QMLE method for response time distributions.

Heathcote, Brown, and Mewhort (2002) have introduced a new, robust method of estimating response time distributions. Their method may have practical advantages over conventional maximum likelihood estimation. The basic idea is that the likelihood of parameters is maximized given a few quantiles from the data.

An evaluation of the Vincentizing method of forming group-level response time distributions.

Vincentizing (quantile averaging) is a popular means of pooling response time distributions across individuals to produce a group average. The benefit of Vincentizing is that the resulting histogram "looks like" an average of the individuals. In this article, we competitively test Vincentizing against the more mundane approach of averaging parameter estimates from fits to individuals.

Multivariate regression trees for analysis of abundance data.

Multivariate regression tree methodology is developed and illustrated in a study predicting the abundance of several cooccurring plant species in Missouri Ozark forests. The technique is a variation of the approach of Segal (1992) for longitudinal data. It has the potential to be applied to many different types of problems in which analysts want to predict the simultaneous cooccurrence of several dependent variables.

In vivo and in vitro evidence suggest that HB-EGF regulates endometrial expression of human decay-accelerating factor.

Human endometrium expresses the critical complement component C3 in a cyclic fashion, with the highest expression in the secretory phase. As activated complement can kill cells, self or foreign, the secretory endometrial epithelium protects itself by concomitant expression of complement-protective proteins. The objectives of our present study were to describe the spatial and temporal regulation of the complement-protective protein decay-accelerating factor (DAF) in human endometrium and to identify local regulators of its expression.