An analysis of pulsation periods of long period variable stars

Summary.  We report the results of a period change analysis of time series observations for 378 pulsating variable stars. The null hypothesis of no trend in expected periods is tested for each of the stars. The tests are non-parametric in that potential trends are estimated by local linear smoothers. Our testing methodology has some novel features. First, the null distribution of a test statistic is defined to be the distribution that results in repeated sampling from a population of stars. This distribution is estimated by means of a bootstrap algorithm that resamples from the collection of 378 stars. Bootstrapping in this way obviates the problem that the conditional sampling distribution of a statistic, given a particular star, may depend on unknown parameters of that star. Another novel feature of our test statistics is that one-sided cross-validation is used to choose the smoothing parameters of the local linear estimators on which they are based. It is shown that doing so results in tests that are tremendously more powerful than analogous tests that are based on the usual version of cross-validation. The positive false discovery rate method of Storey is used to account for the fact that we simultaneously test 378 hypotheses. We ultimately find that 56 of the 378 stars have changes in mean pulsation period that are significant when controlling the positive false discovery rate at the 5% level.     

DATA-BASED CHOICE OF THE SMOOTHING PARAMETER FOR A KERNEL DENSITY ESTIMATOR

The problem of optimally choosing the smoothing parameter of a Fourier integral density estimator (FIE) is addressed. A new data-based method of so doing is shown to be related to, but an improvement over, the method of Davis (1981). It is shown that Davis' method does not lead to consistent estimation of certain, principally multimodal, densities. In a simulation study involving the bimodal mixture of two normal densities, the new method is seen to represent a substantial improvement.     

Practicing Birchism: The Assumption and Limits of Idiocultural Coherence in Framing Theory

Social movement theory and research over the past twenty years have utilized the concepts incorporated under the rubric of Framing Theory in order to draw attention to the cultural ‘meaning work’ within a social movement or social movement organization. Underlying Framing Theory is an assumption of what I term idiocultural coherence – that for a movement organization to be successful, its members must come to agree cognitively with its cultural understandings and identify collectively with it. Drawing on an example of the John Birch Society, a very successful conspiratorial, anti-communist organization, I show how people may join a social movement organization not because they necessarily or fully agree with its collective action frames but because it provides an opportunity to act collectively and publicly perform a collective identity. I argue that a narrow focus on idiocultural processes obfuscates important cultural processes ‘outside’ of a movement organization that have an impact on how and why people join an organization and maintain membership.     

Affective and Behavioral Features of Jealousy Protest: Associations with Child Temperament,Maternal Interaction Style,and Attachment

This study explored variation in affective and behavioral components of infants’ jealousy protests during an eliciting condition in which mother and an experimenter directed differential attention exclusively toward a rival. Variation was examined in relation to child temperamental emotionality, maternal interaction style, and attachment security. At 45 weeks, intensity of infants’distress and durations of mother‐ and stranger‐directed behavioral responses, including gaze, touch, and proximity‐seeking, were observed in the eliciting condition. We also assessed infants’positive emotionality (PE) and negative emotionality (NE) and maternal interaction styles of sensitivity and engagement. At 54 weeks, attachment security was measured in the Strange Situation Procedure. Findings revealed that distress differed with temperamental emotionality and maternal interaction style. Specifically, distress was greater in infants with lower PE and having mothers who displayed less sensitivity and engagement. Analyses on behavioral responses toward the experimenter revealed linkages with maternal interaction style. Specifically, experimenter‐directed gaze and touch were greater among infants of mothers who demonstrated less sensitivity and engagement. Behavioral responses toward mother were found associated with quality of attachment. Specifically, mother‐directed proximity and touch were highest among infants later judged insecure resistant and lowest among those later judged insecure/avoidant; with infants later judged secure displaying moderate durations of mother‐directed proximal contact.     

Using hybrid models to support the development of organizational evaluation capacity: a case narrative

The ongoing need for public sector organizations to enhance their internal evaluation capacity is increasingly resulting in the use of hybrid evaluation project models, where internal evaluators work with external contracted evaluators to complete evaluative work. This paper first seeks to identify what is currently known about internal evaluation through a synthesis of the literature in this area. It then presents a case narrative illustrating how internal and external evaluation approaches may be used together to strengthen an evaluation project and to develop the evaluation capacity of the organization. Lessons learned include the need to integrate internal and external resources throughout the evaluation and to clarify expectations at the outset of the project.     

Nonparametric Predictive Inference for Exposure Assessment

Exposure assessment for food and drink consumption requires the combining of information about people's consumption of products with concentration data sets to provide predictions for chemical intake by humans. In this article, we present a method called nonparametric predictive inference (NPI) for exposure assessment. NPI is a distribution‐free method relying only on Hill's assumption . Effectively, is a postdata exchangeability assumption, which is a natural starting point for nonparametric statistics. For further discussion we refer to works by Hill and Coolen. We illustrate how NPI can be implemented to produce predictions for an individual's exposure based on consumption, body weight, and concentration data. NPI has the advantage that we do not have to assume a distribution to implement it. There may, however, be information available to suggest a distribution for a random quantity. Therefore, we present an NPI‐Bayes hybrid method where this information can be taken into account by using Bayesian methods while using NPI for the other random quantities in the model.