Bayesian comparison of latent variable models: Conditional vs marginal likelihoods

Typical Bayesian methods for models with latent variables (or random effects) involve directly sampling the latent variables along with the model parameters. In high-level software code for model definitions (using, e.g., BUGS, JAGS, Stan), the likelihood is therefore specified as conditional on the latent variables. This can lead researchers to perform model comparisons via conditional likelihoods, where the latent variables are considered model parameters. In other settings, however, typical model comparisons involve marginal likelihoods where the latent variables are integrated out. This distinction is often overlooked despite the fact that it can have a large impact on the comparisons of interest. In this paper, we clarify and illustrate these issues, focusing on the comparison of conditional and marginal Deviance Information Criteria (DICs) and Watanabe-Akaike Information Criteria (WAICs) in psychometric modeling. The conditional/marginal distinction corresponds to whether the model should be predictive for the clusters that are in the data or for new clusters (where "clusters" typically correspond to higher-level units like people or schools). Correspondingly, we show that marginal WAIC corresponds to leave-one-cluster out (LOcO) cross-validation, whereas conditional WAIC corresponds to leave-one-unit out (LOuO). These results lead to recommendations on the general application of the criteria to models with latent variables.Comment: Manuscript in press at Psychometrika; 31 pages, 8 figure

Fitting multilevel models in complex survey data with design weights: Recommendations

Abstract Background Multilevel models (MLM) offer complex survey data analysts a unique approach to understanding individual and contextual determinants of public health. However, little summarized guidance exists with regard to fitting MLM in complex survey data with design weights. Simulation work suggests that analysts should scale design weights using two methods and fit the MLM using unweighted and scaled-weighted data. This article examines the performance of scaled-weighted and unweighted analyses across a variety of MLM and software programs. Methods Using data from the 2005–2006 National Survey of Children with Special Health Care Needs (NS-CSHCN: n = 40,723) that collected data from children clustered within states, I examine the performance of scaling methods across outcome type (categorical vs. continuous), model type (level-1, level-2, or combined), and software (Mplus, MLwiN, and GLLAMM). Results Scaled weighted estimates and standard errors differed slightly from unweighted analyses, agreeing more with each other than with unweighted analyses. However, observed differences were minimal and did not lead to different inferential conclusions. Likewise, results demonstrated minimal differences across software programs, increasing confidence in results and inferential conclusions independent of software choice. Conclusion If including design weights in MLM, analysts should scale the weights and use software that properly includes the scaled weights in the estimation.</p

Age differences in heroin and prescription opioid abuse among enrolees into opioid treatment programs

<p>Abstract</p> <p>Background</p> <p>In the United States, among those entering opioid treatment programs (OTPs), prescription opioid (PO) abusers tend to be younger than heroin users. Admissions of older persons to OTPs have been increasing, and it is important to understand typical patterns of use among those older enrolees.</p> <p>Methods</p> <p>To disentangle the effect of age on recent heroin and PO abuse 29,114 enrolees into 85 OTPs were surveyed across 34 states from 2005-2009. OTPs where PO use was prevalent were oversampled.</p> <p>Results</p> <p>Mean age was 34; 28% used heroin only. Younger enrolees had increased odds of using POs relative to using heroin only but mixed model analysis showed that much of the total variability in type of use was attributed to variation in age between OTPs rather than within OTPs.</p> <p>Conclusions</p> <p>Organizational and cultural phenomena (e.g., OTP characteristics) must be examined to better understand the context of individual characteristics (e.g., age). If nesting of enrolees within OTPs is ignored, then associations that primarily operate at the OTP level may be misinterpreted as exclusively dependent on individuals.</p

Leadership in agricultural machinery circles: experimental evidence from Tajikistan

Leadership is critical for the viability of rural groups. The way in which leadership is legitimised can mediate leader and group member behaviour in the face of social dilemmas. Yet there has been scant research on leader‐follower dynamics in naturally occurring groups. Highlighting the case of agricultural machinery circles in Tajikistan, the effect of leading by example on investments to a collective good is studied in a framed field experiment. To increase realism, and contrary to standard economic experiments, this investment is a voucher allowing the group to make a real‐world machinery purchase at reduced costs. Two treatments manipulate leaders’ legitimisation. Elected leaders achieve 30 per cent higher contributions to the collective investment against a baseline version without a leader. Contributions remain, on average, relatively stable over the course of the game. The results are discussed with reference to the debate on external intervention in agricultural producer organisations.Peer Reviewe

What Makes Some People Think Astrology Is Scientific?

Citizens in both North America and Europe are apt to read horoscope columns in newspapers and magazines. While some people read these casually and purely for entertainment, some believe that astrology has scientific status and can provide real insight into events and personality. Using data from a European survey, this article explores some of the reasons why some people think that astrology is scientific and how astrology is viewed in relation to other knowledge-producing practices. Three hypotheses in particular are tested. The first is that some Europeans lack the necessary scientific literacy to distinguish science from pseudoscience. The second is that people are confused about what astrology actually is. The third is derived from Adorno’s work on authoritarianism and the occult and postulates that those who adhere to authoritarian values are more likely to believe in astrological claims. Support is found for all three hypotheses. </jats:p

Parental education and the risk of cerebral palsy for children:an evaluation of causality

Aim To explore whether increasing parental education has a causal effect on risk of cerebral palsy (CP) in the child, or whether unobserved confounding is a more likely explanation. Method We used data from Norwegian registries on approximately 1.5 million children born between 1967 and 2011. We compared results from a traditional cohort design with results from a family‐based matched case–control design, in which children with CP were matched to their first cousins without CP. In addition, we performed a simulation study to assess the role of unobserved confounding. Results In the cohort design, the odds of CP were reduced in children of mothers and fathers with higher education (adjusted odds ratio [OR] 0.67, 95% confidence interval [CI] 0.60–0.75 for maternal education, and adjusted OR 0.75, 95% CI 0.67–0.85 for paternal education). In the family‐based case–control design, only an association for maternal education remained (adjusted OR 0.80, 95% CI 0.64–0.99). Results from a simulation study suggested that this association could be explained by unobserved confounding. Interpretation A causal effect of obtaining higher education on risk of CP in the child is unlikely. Results stress the importance of continued research on the role of genetic and environmental risk factors that vary by parents’ educational level.publishedVersio

Development and exploratory cluster-randomised opportunistic trial of a theory-based intervention to enhance physical activity among adolescents

Peer reviewedPostprin

Long-Term Effects of Polychlorinated Biphenyls and Dioxins on Pregnancy Outcomes in Women Affected by the Yusho Incident

Background: Maternal exposure to polychlorinated biphenyls (PCBs) is associated with increased proportions of spontaneous abortion and stillbirth in animal studies. In Japan in 1968, accidental human exposure to rice oil contaminated with PCBs and other dioxin-related compounds, such as polychlorinated dibenzofurans (PCDFs), led to the development of what was later referred to as Yusho oil disease. Objective: The aim of this study was to investigated the association of maternal PCB and dioxin exposure with adverse pregnancy outcomes in Yusho women. Methods: In 2004, we interviewed 214 Yusho women (512 pregnancies) about their pregnancy outcomes over the past 36 years. Pregnancy outcomes included induced abortion, spontaneous abortion, preterm delivery, and pregnancy loss. Results: In pregnancy years 1968-1977 (within the first 10 years after exposure), the proportions of induced abortion [adds ration adjusted for age at delivery (ORadj) = 5.93; 95% confidence interval (CI), 2.21-15.91; two-tailed p < 0.001) and preterm delivery (ORadj = 5.70; 95% CI, 1.17-27.79; p = 0.03) were significantly increased compared with the proportions in pregnancy years 1958-1967 (10 years before the incident). Spontaneous abortion (ORadj = 2.09; 95% CI, 0.84-5.18), and pregnancy loss (ORadj = 2.11; 95% CI, 0.92-4.87) were more frequent (OR = 2.18; 95% CI, 1.02-4.66), but these were not significant (p = 0.11 and p = 0.08, respectively) in pregnancy years 1968-1977. We found no significant increases in the proportions of these adverse pregnancy outcomes in pregnancies occurring during 1978-1987 or 1988-2003 compared with those in pregnancies before 1968. Conclusion: High levels of PCB/PCDF exposure had some adverse effects on pregnancy outcome in Yusho women