Search for optimal designs in a three stagenested random model

In this paper we define a class of unbalanced designs, denoted by C_k,s,t, for estimating the components of variance in a k-stage nested random effects linear model. This class contains many of the designs proposed in the literature for nested components of variance models. We focus on the three-state model and discuss the determination of locally optimal designs within this class using a systematic computer search. For large sample sizes we show that approximate optimal designs may be obtained using a limit argument combined with numerical optimization. A comparison of our designs with previously published designs suggests that, in many cases, our designs result in substantial gains in efficiency.     

Real-life closeness of social media contacts and depressive symptoms among university students

ABSTRACT

Objective: To examine the association between degree of real-life closeness of social media (SM) contacts and depressive symptoms. Participants: Students ages 18–30 (N = 1124) were recruited in August 2016. Methods: Participants completed an online survey assessing SM use and depression. We used multivariable logistic regression to assess associations between real-life closeness of SM contacts and depressive symptoms. Results: After controlling for covariates, each 10% increase in the proportion of SM friends with whom participants had no face-to-face relationship was associated with a 9% increase in odds of depressive symptoms (AOR = 1.09; 95% CI = 1.05–1.13). However, each 10% increase in the proportion of SM friends with whom participants had a close face-to-face relationship was associated with a 7% decrease in depressive symptoms (AOR = 0.93; 95% CI = 0.89–0.97). Conclusions: Having no in-person relationship with SM contacts is associated with increased depressive symptoms; however, having close in-person relationships with SM contacts is associated with decreased depressive symptoms.     

Victim or Whore: The Similarities and Differences between Victim's Experiences of Domestic Violence and Sex Trafficking

This research review addresses the similarities and differences between domestic violence and sex trafficking victimization. While there is evidence that domestic violence and sex trafficking often co-occur, there is a large disparity in the understanding and interventions utilized by law enforcement as well as the services available for victims of each crime despite the considerable overlap of victimization. This article explores current research regarding domestic violence and sex trafficking with a focus towards identifying areas of overlap and areas distinct to sex trafficking.     

Problems with Traditional Science Publishing and Finding a Wider Niche for Post-Publication Peer Review

Science affects multiple basic sectors of society. Therefore, the findings made in science impact what takes place at a commercial level. More specifically, errors in the literature, incorrect findings, fraudulent data, poorly written scientific reports, or studies that cannot be reproduced not only serve as a burden on tax-payers’ money, but they also serve to diminish public trust in science and its findings. Therefore, there is every need to fortify the validity of data that exists in the science literature, not only to build trust among peers, and to sustain that trust, but to reestablish trust in the public and private academic sectors that are witnessing a veritable battle-ground in the world of science publishing, in some ways spurred by the rapid evolution of the open access (OA) movement. Even though many science journals, traditional and OA, claim to be peer reviewed, the truth is that different levels of peer review occur, and in some cases no, insufficient, or pseudo-peer review takes place. This ultimately leads to the erosion of quality and importance of science, allowing essentially anything to become published, provided that an outlet can be found. In some cases, predatory OA journals serve this purpose, allowing papers to be published, often without any peer review or quality control. In the light of an explosion of such cases in predatory OA publishing, and in severe inefficiencies and possible bias in the peer review of even respectable science journals, as evidenced by the increasing attention given to retractions, there is an urgent need to reform the way in which authors, editors, and publishers conduct the first line of quality control, the peer review. One way to address the problem is through post-publication peer review (PPPR), an efficient complement to traditional peer-review that allows for the continuous improvement and strengthening of the quality of science publishing. PPPR may also serve as a way to renew trust in scientific findings by correcting the literature. This article explores what is broadly being said about PPPR in the literature, so as to establish awareness and a possible first-tier prototype for the sciences for which such a system is undeveloped or weak.     

Who gets over the training hurdle? A study of the training experiences of young men and women in Britain

Using longitudinal data from the British National Child Development Study, this paper examines gender differences in the determinants of work-related training. The analysis covers a crucial decade in the working lives of this 1958 birth cohort of young men and women – the years spanning the ages of 23 to 33. Hurdle negative binomial models are used to estimate the number of work-related training events lasting at least three days. This approach takes into account the fact that more than half the men and two thirds of the women in the sample experienced no work-related training lasting three or more days over the period 1981 to 1991. Our analysis suggests that reliance on work-related training to improve the skills of the work force will result in an increase in the skills of the already educated, but will not improve the skills of individuals entering the labor market with relatively low levels of education. JEL classification: C25, I21, J24. Received February 9, 1996/Accepted August 14, 1996     

Infant mortality in the Marshall Islands

Levy and Booth present previously unpublished infant mortality rates for the Marshall Islands. They use an indirect method to estimate infant mortality from the 1973 and 1980 censuses, then apply indirect and direct methods of estimation to data from the Marshall Islands Women's Health Survey of 1985. Comparing the results with estimates of infant mortality obtained from vital registration data enables them to estimate the extent of underregistration of infant deaths. The authors conclude that 1973 census appears to be the most valid information source. Direct estimates from the Women's Health Survey data suggest that infant mortality has increased since 1970-1974, whereas the indirect estimates indicate a decreasing trend in infant mortality rates, converging with the direct estimates in more recent years. In view of increased efforts to improve maternal and child health in the mid-1970s, the decreasing trend is plausible. It is impossible to estimate accurately infant mortality in the Marshall Islands during 1980-1984 from the available data. Estimates based on registration data for 1975-1979 are at least 40% too low. The authors speculate that the estimate of 33 deaths per 1000 live births obtained from registration data for 1984 is 40-50% too low. In round figures, a value of 60 deaths per 1000 may be taken as the final estimate for 1980-1984.     

Random-Effects Modeling of Categorical Response Data

In many applications observations have some type of clustering, with observations within clusters tending to be correlated. A common instance of this occurs when each subject in the sample undergoes repeated measurement, in which case a cluster consists of the set of observations for the subject. One approach to modeling clustered data introduces cluster-level random effects into the model. The use of random effects in linear models for normal responses is well established. By contrast, random effects have only recently seen much use in models for categorical data. This chapter surveys a variety of potential social science applications of random effects modeling of categorical data. Applications discussed include repeated measurement for binary or ordinal responses, shrinkage to improve multiparameter estimation of a set of proportions or rates, multivariate latent variable modeling, hierarchically structured modeling, and cluster sampling. The models discussed belong to the class of generalized linear mixed models (GLMMs), an extension of ordinary linear models that permits nonnormal response variables and both fixed and random effects in the predictor term. The models are GLMMs for either binomial or Poisson response variables, although we also present extensions to multicategory (nominal or ordinal) responses. We also summarize some of the technical issues of model-fitting that complicate the fitting of GLMMs even with existing software.     

Looking Behavior and Smiling in Down Syndrome Infants

We studied the relation between direction of gaze and smiling in 15 typically developing infants and 15 infants with Down syndrome. All of them were videotaped during face-to-face interaction with their mothers at home, and while having access to their familiar toys. Results showed that mothers in the two groups behaved in a similar way; that Down syndrome infants looked at their mother's face for longer than typically developing children; and that the relationship between looking and smiling was similar in the two cases and reflected as an increase in the time the infant looked at its mother's face and a decrease in the time the infant looked at toys. It was deduced that Down syndrome infants are capable of distinguishing the differential significance of faces and toys, so that, in the same way as typically developing infants, they direct their affective behavior fundamentally towards the social element, which leads us to consider the affiliative function implied by this expression.