Changing climates of conflict: A social network experiment in 56 schools.

Theories of human behavior suggest that individuals attend to the behavior of certain people in their community to understand what is socially normative and adjust their own behavior in response. An experiment tested these theories by randomizing an anticonflict intervention across 56 schools with 24,191 students. After comprehensively measuring every school's social network, randomly selected seed groups of 20-32 students from randomly selected schools were assigned to an intervention that encouraged their public stance against conflict at school. Compared with control schools, disciplinary reports of student conflict at treatment schools were reduced by 25% over 1 year. The effect was stronger when the seed group contained more "social referent" students who, as network measures reveal, attract more student attention. Network analyses of peer-to-peer influence show that social referents spread perceptions of conflict as less socially normative.

Identification of Homophily and Preferential Recruitment in Respondent-Driven Sampling.

Respondent-driven sampling (RDS) is a link-tracing procedure used in epidemiologic research on hidden or hard-to-reach populations in which subjects recruit others via their social networks. Estimates from RDS studies may have poor statistical properties due to statistical dependence in sampled subjects' traits. Two distinct mechanisms account for dependence in an RDS study: homophily, the tendency for individuals to share social ties with others exhibiting similar characteristics, and preferential recruitment, in which recruiters do not recruit uniformly at random from their network alters. The different effects of network homophily and preferential recruitment in RDS studies have been a source of confusion and controversy in methodological and empirical research in epidemiology. In this work, we gave formal definitions of homophily and preferential recruitment and showed that neither is identified in typical RDS studies. We derived nonparametric identification regions for homophily and preferential recruitment and showed that these parameters were not identified unless the network took a degenerate form. The results indicated that claims of homophily or recruitment bias measured from empirical RDS studies may not be credible. We applied our identification results to a study involving both a network census and RDS on a population of injection drug users in Hartford, Connecticut (2012-2013).

Nonparametric Identification for Respondent-Driven Sampling.

We detail nonparametric identification results for respondent-driven sampling when sampling probabilities are assumed to be functions of network degree known to scale. We show that the conditions for consistency of the Volz-Heckathorn estimator are weaker than previously assumed.

The effect of images of Michelle Obama's face on trick-or-treaters' dietary choices: A randomized control trial.

OBJECTIVE: To evaluate the microfoundations of a personality-inspired public health campaign's influence on minors. DESIGN: Multi-year randomized control trial. SETTING: Economics professor's front porch in New Haven, CT. PARTICIPANTS: 1223 trick-or-treaters in New Haven over three years; on average, 8.5 years old and 53% male (among children whose gender was identifiable). ELIGIBILITY: Trick-or-treaters over the age of three that approached the house. INTERVENTION: Random assignment to the Michelle Obama side of the porch or the Comparison side of the porch. MAIN OUTCOME MEASURE: Selection of fruit over candy. METHODS: Difference-in-means estimates. RESULTS: We estimate that viewing a photograph of Michelle Obama's face relative to control conditions caused children to be 19% more likely to choose fruit over candy. CONCLUSIONS: Michelle Obama's initiative to reduce childhood obesity has influenced children's dietary preferences. Whether this influence extends beyond Halloween trick-or-treating in New Haven, CT on the porch of an economics professor requires further research.

Driving fatalities on US presidential election days: a reanalysis.

BACKGROUND: Redelmeier and Tibshirani reported a statistical analysis in the Journal of the American Medical Association in 2008 indicating that presidential election days are strongly associated (P < 0.001) with an increased risk of driving fatalities (as measured by the number of persons involved in fatal crashes). FINDINGS: We present evidence indicating that the risk of driving fatalities on presidential election days is neither statistically nor substantively unusual. Although we find weakly suggestive evidence that presidential elections may increase the risk of driving fatalities during election hours, any increase appears to be entirely offset by a lowered risk during non-election hours. CONCLUSIONS: We find weaker support for an association between election days and driving fatalities than was previously reported. Our results suggest caution in evaluating policy prescriptions that presuppose that election days pose an unusual risk to the public.

Chocolate scents and product sales: a randomized controlled trial in a Canadian bookstore and café.

We report the results of a 31-day trial on the effects of chocolate scent on purchasing behavior in a bookstore. Our study replicates and extends a 10-day randomized controlled trial in order to examine the generalizability of the original finding. We first introduce the study of store atmospherics and highlight the importance and dearth of replication in this area. In the next section, we describe the original study and discuss the theory of ambient scent effects on product sales, and the role of scent-product congruity. We then describe our design and methods, followed by presentation and discussion of our results. We find no evidence that chocolate scent affects sales. These findings indicate the importance of replication in varied settings. Contextual factors and the choices available to customers may moderate the effects of ambient scent on purchasing behavior. Our study highlights the value of examining the generalizability of experimental findings, both for theory and practice.

Editorial Bias in Crowd-Sourced Political Information.

The Internet has dramatically expanded citizens' access to and ability to engage with political information. On many websites, any user can contribute and edit "crowd-sourced" information about important political figures. One of the most prominent examples of crowd-sourced information on the Internet is Wikipedia, a free and open encyclopedia created and edited entirely by users, and one of the world's most accessed websites. While previous studies of crowd-sourced information platforms have found them to be accurate, few have considered biases in what kinds of information are included. We report the results of four randomized field experiments that sought to explore what biases exist in the political articles of this collaborative website. By randomly assigning factually true but either positive or negative and cited or uncited information to the Wikipedia pages of U.S. senators, we uncover substantial evidence of an editorial bias toward positivity on Wikipedia: Negative facts are 36% more likely to be removed by Wikipedia editors than positive facts within 12 hours and 29% more likely within 3 days. Although citations substantially increase an edit's survival time, the editorial bias toward positivity is not eliminated by inclusion of a citation. We replicate this study on the Wikipedia pages of deceased as well as recently retired but living senators and find no evidence of an editorial bias in either. Our results demonstrate that crowd-sourced information is subject to an editorial bias that favors the politically active.

Combining List Experiment and Direct Question Estimates of Sensitive Behavior Prevalence.

Survey respondents may give untruthful answers to sensitive questions when asked directly. In recent years, researchers have turned to the list experiment (also known as the item count technique) to overcome this difficulty. While list experiments are arguably less prone to bias than direct questioning, list experiments are also more susceptible to sampling variability. We show that researchers need not abandon direct questioning altogether in order to gain the advantages of list experimentation. We develop a nonparametric estimator of the prevalence of sensitive behaviors that combines list experimentation and direct questioning. We prove that this estimator is asymptotically more efficient than the standard difference-in-means estimator, and we provide a basis for inference using Wald-type confidence intervals. Additionally, leveraging information from the direct questioning, we derive two nonparametric placebo tests for assessing identifying assumptions underlying list experiments. We demonstrate the effectiveness of our combined estimator and placebo tests with an original survey experiment.