A varying‐coefficient generalized odds rate model with time‐varying exposure: An application to fitness and cardiovascular disease mortality

Varying‐coefficient models have become a common tool to determine whether and how the association between an exposure and an outcome changes over a continuous measure. These models are complicated when the exposure itself is time‐varying and subjected to measurement error. For example, it is well known that longitudinal physical fitness has an impact on cardiovascular disease (CVD) mortality. It is not known, however, how the effect of longitudinal physical fitness on CVD mortality varies with age. In this paper, we propose a varying‐coefficient generalized odds rate model that allows flexible estimation of age‐modified effects of longitudinal physical fitness on CVD mortality. In our model, the longitudinal physical fitness is measured with error and modeled using a mixed‐effects model, and its associated age‐varying coefficient function is represented by cubic B‐splines. An expectation‐maximization algorithm is developed to estimate the parameters in the joint models of longitudinal physical fitness and CVD mortality. A modified pseudoadaptive Gaussian‐Hermite quadrature method is adopted to compute the integrals with respect to random effects involved in the E‐step. The performance of the proposed method is evaluated through extensive simulation studies and is further illustrated with an application to cohort data from the Aerobic Center Longitudinal Study.     

Prediction analysis for microbiome sequencing data

One goal of human microbiome studies is to relate host traits with human microbiome compositions. The analysis of microbial community sequencing data presents great statistical challenges, especially when the samples have different library sizes and the data are overdispersed with many zeros. To address these challenges, we introduce a new statistical framework, called predictive analysis in metagenomics via inverse regression (PAMIR), to analyze microbiome sequencing data. Within this framework, an inverse regression model is developed for overdispersed microbiota counts given the trait, and then a prediction rule is constructed by taking advantage of the dimension‐reduction structure in the model. An efficient Monte Carlo expectation‐maximization algorithm is proposed for maximum likelihood estimation. The method is further generalized to accommodate other types of covariates. We demonstrate the advantages of PAMIR through simulations and two real data examples.     

How placebo responses are formed: a learning perspective

Despite growing scientific interest in the placebo effect and increasing understanding of neurobiological mechanisms, theoretical conceptualization of the placebo effect remains poorly developed. Substantial mechanistic research on this phenomenon has proceeded with little guidance by any systematic theoretical paradigm. This review seeks to present a theoretical perspective on the formation of placebo responses. We focus on information processing, and argue that different kinds of learning along with individuals' genetic make-up evolved as the proximate cause for triggering behavioural and neural mechanisms that enable the formation of individual expectations and placebo responses. Conceptualizing the placebo effect in terms of learning offers the opportunity for facilitating scientific investigation with a significant impact on medical care.     

Back to basics for Bayesian model building in genomic selection

Numerous Bayesian methods of phenotype prediction and genomic breeding value estimation based on multilocus association models have been proposed. Computationally the methods have been based either on Markov chain Monte Carlo or on faster maximum a posteriori estimation. The demand for more accurate and more efficient estimation has led to the rapid emergence of workable methods, unfortunately at the expense of well-defined principles for Bayesian model building. In this article we go back to the basics and build a Bayesian multilocus association model for quantitative and binary traits with carefully defined hierarchical parameterization of Student's t and Laplace priors. In this treatment we consider alternative model structures, using indicator variables and polygenic terms. We make the most of the conjugate analysis, enabled by the hierarchical formulation of the prior densities, by deriving the fully conditional posterior densities of the parameters and using the acquired known distributions in building fast generalized expectation-maximization estimation algorithms.     

Creating Public Awareness of How Goats Are Reared and Milk Produced May Affect Consumer Acceptability

This study evaluated whether showing a video of the different ways of raising goats for milk affected consumer acceptability. Four combinations, 2 Videos (intensive [INT] and semiextensive [SEM] system) × 2 Milk Types (semiskimmed [S] and whole [W] milk), were evaluated by 70 habitual consumers of goat milk, who scored their liking and purchase intention during blind (B), expected (E), and informed (I) acceptability sessions. In the B session, consumers tasted both milk types without information. S samples were preferred over W samples. In the E session, SEM video created high expectations in terms of milk liking and purchase intent, whereas the opposite happened when showing INT video. In the I session, consumers showed a clear preference for combinations created using SEM video, regardless of milk type. W-SEM and S-INT were worse (negative disconfirmation) and better (positive disconfirmation) than expected, respectively. A complete assimilation toward expectations occurred only for S-INT. INT video adversely affected the acceptability of S samples. Concerning purchase intent, W-SEM and S-SEM were worse than expected, but the assimilation was complete only for S-SEM: SEM video increased purchase intent for S samples.     

On the Estimation of the Mean with Random Number Of Observations. (Comments on a Paper by M. Singh and V. K. Gupta)

In this paper we study the problem of estimating the mean when the number of observations taken on each unit is a random variable. The estimator proposed by M. Singh and V. K. Gupta (1980) is discussed and modified. It is argued, however, that the arithmetic mean is a more appropriate choice of estimator.     

The body beyond the body: expectation of a sensory event is enough to induce ownership over a fake hand

More than 100 papers have been published on the rubber hand illusion since its discovery 14 years ago. The illusion has been proposed as a demonstration that the body is distinguished from other objects by its participation in specific forms of intermodal perceptual correlation. Here, we radically challenge this view by claiming that perceptual correlation is not necessary to produce the experience of this body as mine. Each of 15 participants was seated with his/her right arm resting upon a table just below another smaller table. Thus, the real hand was hidden from the participant''s view and a life-sized rubber model of a right hand was placed on the small table in front of the participant. The participant observed the experimenter''s hand while approaching—without touching—the rubber hand. Phenomenology of the illusion was measured by means of skin conductance response and questionnaire. Both measures indicated that participants experienced the illusion that the experimenter''s hand was about to touch their hidden hand rather than the rubber hand, as if the latter replaced their own hand. This did not occur when the rubber hand was rotated by 180° or replaced by a piece of wood. This illusion indicates that our brain does not build a sense of self in a merely reactive way, via perceptual correlations; rather it generates predictions on what may or may not belong to itself.     

Effect of Adopters' Lifestyles and Animal-Care Knowledge on Their Expectations Prior to Companion-Animal Guardianship

Human expectations can greatly affect the human–companion animal relationship, sometimes putting nonhuman animals at risk for relinquishment. At 20 animal shelters in Southern Ontario, Canada, potential adopters (N = 234) completed a questionnaire regarding their lifestyle, companion animal-care knowledge, and preadoption expectations of their adopted companion animals. Linear mixed models were used to assess the associations of adopters' lifestyles and companion animal-care knowledge with their expectations for animal behavior, the human–companion animal relationship, and the effort required in companion-animal guardianship. Dog adopters had higher expectations than cat adopters for their companion animal's behavior (p < .001), the human–companion animal relationship (p < .001), and the effort required in companion-animal guardianship (p < .001). Adopters' human relationship statuses were also associated with expectations for the human–companion animal relationship (p = .002). As adopters' companion animal-care knowledge increased, so did their expectations for the effort required in companion-animal guardianship (p < .001). An understanding of adopters' expectations prior to adoption will help animal shelters better match, educate, and prepare adopters for their lives with companion animals.     

Detection of a new 20-bp insertion/deletion (indel) within sheep PRND gene using mathematical expectation (ME) method

Prion-related protein doppel gene (PRND), as an essential member of the mammalian prion gene family, is associated with the scrapie susceptibility as well as phenotype traits, so the genetic variation of the PRND has been highly concerned recently, including the single nucleiotide polymorphism (SNP) and insertion/deletion (indel). Therefore, the objective of present study was to examine the possible indel variants by mathematical expectation (ME) detection method as well as explore its associations with phenotype traits. A novel 20-bp indel was verified in 623 tested individuals representing 4 diversity sheep breeds. The results showed that 3 genotypes were detected and the minor allelic frequency were 0.008 (Lanzhou Fat-Tail sheep, LFTS), 0.084 (Small Tail Han sheep, STHS), 0.021(Tong sheep, TS) and 0.083 (Hu sheep, HS), respectively. Comparing with the traditional method of detecting samples one by one, the reaction times with ME method was decreased by 36.22% (STHS), 37.00% (HS), 68.67% (TS) and 83.33% (LFTS), respectively. Besides, this locus was significantly associated to cannon circumference index (P = 0.012) and trunk index (P = 0.037) in the Hu sheep breed. Notably, it was not concordance with the present result of DNA sequencing (GCTGTCCCTGCAGGGCTTCT) and dbSNPase of NCBI (NC_443194: g.46184887- 46184906delCTGCTGTCCCTGCAGGGCTT). Consequently, it was the first time to detect the new 20-bp indel of sheep PRND gene by ME strategy, which might provide a valuable theoretical basis for marker-assisted selection in sheep genetics and breeding.