Adolescents' attention to traditional and graphic tobacco warning labels: an eye-tracking approach

The objective of this study was determine if the inclusion of Canadian-style graphic images would improve the degree to which adolescents attend to, and subsequently are able to recall, novel warning messages in tobacco magazine advertising. Specifically, our goal was to determine if the inclusion of graphic images would (1) increase visual attention, as measured by eye movement patterns and fixation density, and (2) improve memory for tobacco advertisements among a group of 12 to 14 year olds in the western United States. Data were collected from 32 middle school students using a head-mounted eye-tracking device that recorded viewing time, scan path patterns, fixation locations, and dwell time. Participants viewed a series of 20 magazine advertisements that included five U.S. tobacco ads with traditional Surgeon General warning messages and five U.S. tobacco ads that had been modified to include non-traditional messages and Canadian-style graphic images. Following eye tracking, participants completed unaided- and aided-recall exercises. Overall, the participants spent equal amounts of time viewing the advertisements regardless of the type of warning message. However, the warning messages that included the graphic images generated higher levels of visual attention directed specifically toward the message, based on average dwell time and fixation frequency, and were more likely to be accurately recalled than the traditional warning messages.     

Bias and precision of measures of survival gain from right‐censored data

In cost‐effectiveness analyses of drugs or health technologies, estimates of life years saved or quality‐adjusted life years saved are required. Randomised controlled trials can provide an estimate of the average treatment effect; for survival data, the treatment effect is the difference in mean survival. However, typically not all patients will have reached the endpoint of interest at the close‐out of a trial, making it difficult to estimate the difference in mean survival. In this situation, it is common to report the more readily estimable difference in median survival. Alternative approaches to estimating the mean have also been proposed. We conducted a simulation study to investigate the bias and precision of the three most commonly used sample measures of absolute survival gain – difference in median, restricted mean and extended mean survival – when used as estimates of the true mean difference, under different censoring proportions, while assuming a range of survival patterns, represented by Weibull survival distributions with constant, increasing and decreasing hazards. Our study showed that the three commonly used methods tended to underestimate the true treatment effect; consequently, the incremental cost‐effectiveness ratio (ICER) would be overestimated. Of the three methods, the least biased is the extended mean survival, which perhaps should be used as the point estimate of the treatment effect to be inputted into the ICER, while the other two approaches could be used in sensitivity analyses. More work on the trade‐offs between simple extrapolation using the exponential distribution and more complicated extrapolation using other methods would be valuable. Copyright © 2015 John Wiley & Sons, Ltd.     

Prosecuting the prosecutor: The makings of the Michael Morton Act

Prosecutorial misconduct is not a rare event, but it often goes undetected, unreported, or no action is taken by the criminal justice system. However, when one Texas prosecutor, Ken Anderson, served jail time for wrongfully prosecuting an innocent man, Michael Morton, for murdering his wife, he made history. Anderson withheld exculpatory evidence leading to Morton wrongfully serving 25 years before being released with new DNA evidence. However, Anderson only served a five-day sentence and $500 fine. We discuss the case in the context of inequality and legal realism in the criminal justice system. Also, we look at the implications and new legal action taken by the state of Texas to try and combat this problem, along with looking at these secretive occupational subcultures.     

On Variational Bayes Estimation and Variational Information Criteria for Linear Regression Models

Variational Bayes (VB) estimation is a fast alternative to Markov Chain Monte Carlo for performing approximate Baesian inference. This procedure can be an efficient and effective means of analyzing large datasets. However, VB estimation is often criticised, typically on empirical grounds, for being unable to produce valid statistical inferences. In this article we refute this criticism for one of the simplest models where Bayesian inference is not analytically tractable, that is, the Bayesian linear model (for a particular choice of priors). We prove that under mild regularity conditions, VB based estimators enjoy some desirable frequentist properties such as consistency and can be used to obtain asymptotically valid standard errors. In addition to these results we introduce two VB information criteria: the variational Akaike information criterion and the variational Bayesian information criterion. We show that variational Akaike information criterion is asymptotically equivalent to the frequentist Akaike information criterion and that the variational Bayesian information criterion is first order equivalent to the Bayesian information criterion in linear regression. These results motivate the potential use of the variational information criteria for more complex models. We support our theoretical results with numerical examples.     

Covariate Decomposition Methods for Longitudinal Missing‐at‐Random Data and Predictors Associated with Subject‐Specific Effects

Investigators often gather longitudinal data to assess changes in responses over time within subjects and to relate these changes to within‐subject changes in predictors. Missing data are common in such studies and predictors can be correlated with subject‐specific effects. Maximum likelihood methods for generalized linear mixed models provide consistent estimates when the data are ‘missing at random’ (MAR) but can produce inconsistent estimates in settings where the random effects are correlated with one of the predictors. On the other hand, conditional maximum likelihood methods (and closely related maximum likelihood methods that partition covariates into between‐ and within‐cluster components) provide consistent estimation when random effects are correlated with predictors but can produce inconsistent covariate effect estimates when data are MAR. Using theory, simulation studies, and fits to example data this paper shows that decomposition methods using complete covariate information produce consistent estimates. In some practical cases these methods, that ostensibly require complete covariate information, actually only involve the observed covariates. These results offer an easy‐to‐use approach to simultaneously protect against bias from both cluster‐level confounding and MAR missingness in assessments of change.     

Sense of belonging in secondary schools: a survey of LGB and heterosexual students in Flanders

This study focuses on differences in sense of belonging between lesbian, gay, and bisexual (LGB) and heterosexual students. Data from 1,745 secondary school students were collected with an online survey. Step-wise multiple regression analyses was used to investigate the relationship between sexual orientation and sense of school belonging. The results show that sexual orientation has an impact on sense of belonging for girls, but not for boys. Perceived discrimination and LGB friendliness of the school appeared to be important indicators of sense of belonging for all the respondents, irrespective of their sexual orientation.     

Piece rates and workplace injury: Does survey evidence support Adam Smith?

While piece rates are routinely associated with higher productivity and wages, they can also generate unanticipated effects. Using cross-country European data, we provide among the first general survey evidence of a strong link between piece rates and workplace injury. Despite controls for workplace hazards, job characteristics and worker effort, piece rates workers suffer a 5 percentage point greater likelihood of injury. This remains despite attempts to control for endogeneity and heterogeneity. As piece rate wage premium estimates rarely control for injury likelihood, this raises the specter that part of that premium reflects a compensating wage differential for risk of injury.     

A location analysis approach for military maintenance scheduling with geographically dispersed service areas

This research uses a two-stage maximal covering location problem (MCLP) model to develop Inter continental ballistic missile (ICBM) maintenance schedules for the US Air Force. Solutions are compared to actual missile maintenance activities accomplished at F. E. Warren Air Force Base (AFB), Wyoming in May 2005. Sensitivity analysis is performed to determine the impact of altering security response times and the number of security patrol areas on the quality of daily maintenance schedules and personnel usage. Results indicate marked improvement over traditional Air Force scheduling methods. In addition sensitivity analysis identifies the levels at which the quality and quantity of maintenance performance is impacted.     

Calibration of FISK, an Invasiveness Screening Tool for Nonnative Freshwater Fishes

Adapted from the weed risk assessment (WRA) of Pheloung, Williams, and Halloy, the fish invasiveness scoring kit (FISK) was proposed as a screening tool for freshwater fishes. This article describes improvements to FISK, in particular the incorporation of confidence (certainty/uncertainty) ranking of the assessors' responses, and reports on the calibration of the score system, specifically: determination of most appropriate score thresholds for classifying nonnative species into low-, medium-, and high-risk categories, assessment of the patterns of assessors' confidences in their responses in the FISK assessments. Using receiver operating characteristic (ROC) curves, FISK was demonstrated to distinguish accurately (and with statistical confidence) between potentially invasive and noninvasive species of nonnative fishes, with the statistically appropriate threshold score for high-risk species scores being ≥19. Within the group of species classed as high risk using this new threshold, a "higher risk" category could be visually identified, at present consisting of two species (topmouth gudgeon Pseudorasbora parva and gibel carp Carassius gibelio ). FISK represents a useful and viable tool to aid decision- and policymakers in assessing and classifying freshwater fishes according to their potential invasiveness.