When the outcome is binary, psychologists often use nonlinear modeling strategies such as logit or probit. These strategies are often neither optimal nor justified when the objective is to estimate ...causal effects of experimental treatments. Researchers need to take extra steps to convert logit and probit coefficients into interpretable quantities, and when they do, these quantities often remain difficult to understand. Odds ratios, for instance, are described as obscure in many textbooks (e.g., Gelman & Hill, 2006, p. 83). I draw on econometric theory and established statistical findings to demonstrate that linear regression is generally the best strategy to estimate causal effects of treatments on binary outcomes. Linear regression coefficients are directly interpretable in terms of probabilities and, when interaction terms or fixed effects are included, linear regression is safer. I review the Neyman-Rubin causal model, which I use to prove analytically that linear regression yields unbiased estimates of treatment effects on binary outcomes. Then, I run simulations and analyze existing data on 24,191 students from 56 middle schools (Paluck, Shepherd, & Aronow, 2013) to illustrate the effectiveness of linear regression. Based on these grounds, I recommend that psychologists use linear regression to estimate treatment effects on binary outcomes.
People who deviate from the established norms of their social group can clarify group boundaries, strengthen group cohesion, and catalyze group and broader social change. Yet social psychologists ...have recently neglected the study of deviants. We conducted in-depth interviews of Princeton University upperclassmen who deviated from a historical and widely known Princeton norm: joining an “eating club,” a social group that undergraduates join at the end of their sophomore year. We explored the themes of these interviews with two rounds of surveys during the semester when students decide whether to join an eating club (pilot survey, N = 408; and a random subsample of the pilot survey with 90% takeup, N = 212). The surveys asked: what are the social and psychological antecedents of deviance from norms? The data suggest that deviance is a pattern: compared to those who conform, students who deviate by not joining clubs report a history of deviance and of feeling different from the typical member of their social group. They also feel less social belonging and identification with Princeton and its social environment. Students who deviate are lower in self-monitoring, but otherwise are comparable to students who conform in terms of personality traits measured by the Big Five, and of their perception of the self as socially awkward, independent, or rebellious. While some of these findings replicate past research, worth further exploration is the role of previous experience with deviance and its meaning for individuals as they decide whether to deviate.
To what extent are television viewers affected by the behaviors and decisions they see modeled by characters in television soap operas? Collaborating with scriptwriters for three prime-time ...nationally-broadcast Spanish-language telenovelas, we embedded scenes about topics such as drunk driving or saving money at randomly assigned periods during the broadcast season. Outcomes were measured unobtrusively by aggregate city- and nation-wide time series, such as the number of Hispanic motorists arrested daily for drunk driving or the number of accounts opened in banks located in Hispanic neighborhoods. Results indicate that while two of the treatment effects are statistically significant, none are substantively large or long-lasting. Actions that could be taken during the immediate viewing session, like online searching, and those that were relatively more integrated into the telenovela storyline, specifically reducing cholesterol, were briefly affected, but not behaviors requiring sustained efforts, like opening a bank account or registering to vote.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Missing data is a common feature of experimental datasets. Standard methods used by psychology researchers to handle missingness rely on unrealistic assumptions, invalidate random assignment ...procedures, and bias estimates of effect sizes. We describe different classes of missing data typically encountered in experimental datasets, and we discuss how each of them impacts researchers' causal inferences. In this tutorial, we provide concrete guidelines for handling each class of missingness, focusing on 2 methods that make realistic assumptions: (a) inverse probability weighting (IPW) for mild instances of missingness, and (b) double sampling and bounds for severe instances of missingness. After reviewing the reasons why these methods increase the accuracy of researchers' estimates of effect sizes, we provide lines of R code that researchers may use in their own analyses.
Translational Abstract
Researchers rarely manage to collect every piece of information about each participant in their study. For instance, participants sometimes refuse to answer questions that they consider sensitive (e.g., income, political orientation, sexual practices) or quit the study before completing it. If ignored or handled inappropriately, this phenomenon referred to as "missingness" generally compromises researchers' ability to make causal inferences based on their experiments. Specifically, missingness biases researchers' estimates of the effect size of the treatment. In this tutorial, we review the different ways in which missingness impacts the results of experimental studies and provide researchers with concrete steps for addressing each type of missingness they may encounter. For mild cases of missingness, we recommend using a method called inverse probability weighting (IPW). For severe instances of missingness, we recommend that researchers recontact a sample of participants with missing values to fill the gaps. This method, which involves recollecting data, is called double sampling and bounds. For both methods, we provide lines of R code that researchers may use in their own analyses.
Abstract
Identifying influential people within a community to involve in a program is an important strategy of behavioral interventions. How to efficiently identify the most effective individuals is ...an outstanding question. This paper compares two common strategies: consulting ‘network insiders’ versus ‘network observers’ who have knowledge of but who do not directly participate in the community. Compared to aggregating information from all insiders, asking relatively fewer observers is more cost-effective, but may come at a cost of accuracy. We use data from a large-scale field experiment demonstrating that
central students
, identified through the aggregated nominations of students (insiders), reduced peer conflict in 56 middle schools. Teachers (observers) also identified students they saw as influential. We compare the causal effect of the two types of nominated students on peer outcomes and the differences between the two types of students. In contrast to the prosocial effects of central students on peer conflict, teacher nominees have no, or even antisocial, influence on their peers’ behaviors. Teachers (observers) generally nominated students with traits salient to them, suggesting that observer roles may systematically bias their perception. We discuss strategies for improving observers’ ability to identify influential individuals in a network as leverage for behavioral change.
Social norms are powerful drivers of human behavior, so much so that people conform to norms even when they would prefer to deviate. Researchers have theorized that in these cases, people conform to ...avoid the costs of deviance. For one, a large body of work suggests that individuals endure psychological costs such as guilt, shame, self-deprecation, or decreased self-esteem for deviating from norms. For two, norm violators are often perceived and labeled negatively, marginalized, stigmatized, or punished by other people. Notwithstanding the possible psychological or social costs, people do decide to violate norms. In the present dissertation, I ask: Who are the deviants, and why? Once individuals have deviated from a norm, how does this experience shape them? These questions are important to address because deviants play critical roles in their communities. Specifically, public acts of deviance can signal disagreement with current practices, and catalyze group and broader social change. In this dissertation, I present evidence from qualitative and quantitative studies in the lab and the field suggesting that the experience of violating a norm increases individuals' inclination to deviance. The results also indicate a possible psychological mechanism explaining this effect: deviating causes people to depreciate their perception of the costs of deviance. After reviewing the relevant literature in Chapter 1, I present findings from in-depth interviews and two rounds of surveys of deviants and conformists (Chapter 2) suggesting that deviance is a pattern: compared to conformists, deviants report a history of deviance and of feeling different from the typical member of their groups. Chapters 3 and 4 focus on the question of how deviance becomes a pattern. Together, the results of online experiments using behavioral games (Chapter 3) and a field experiment in the Hasidic community (Chapter 4) challenge traditional views of deviance as personality or a stable individual trait that develops early in the life span. Instead, these findings suggest that patterns of deviance can emerge from an experience of deviance at any point in one's life.
Data quality and trust in the data collection process are critical concerns in survey research, particularly when surveyors are needed for reaching “diverse and inconvenient subject pools.” In ...response to irregularities in a smartphone-based pilot survey data collection in Nigeria, we developed an audio check method that unobtrusively recorded surveyors reading aloud questions to participants. We present evidence that this method detected wholesale data fabrication in 14% of our surveys, prevented further fabrication, and improved data quality through provision of regular feedback to surveyors. Using simulation, we demonstrate that undetected fabrication would have introduced significant bias in our analyses. The audio check performs well compared to more traditional methods of detecting fabrication, and a comparative cost–benefit analysis reveals a savings of more than US$1,500 per surveyor by relying on the audio check. The audio check is a viable tool for psychologists who work with survey teams.
S–(CF3)Thianthrenium and S–(CF3)dibenzothiophenium cations form potent chalcogen bonds (ChBs) with Mo(CO)5CN−, yielding S2N2 supramolecular motifs. Crystal structures reveal shorter S⋯N contacts ...opposite the CF3 group compared to the aryl substituents. The energetic features of the ChBs have been studied using DFT calculations demonstrating the structure guiding role of ChBs.
S–(CF 3 )Thianthrenium and S–(CF 3 )dibenzothiophenium cations form potent chalcogen bonds (ChBs) with Mo(CO) 5 CN − , yielding S 2 N 2 supramolecular motifs. Crystal structures reveal shorter S⋯N ...contacts opposite the CF 3 group compared to the aryl substituents. The energetic features of the ChBs have been studied using DFT calculations demonstrating the structure guiding role of ChBs.
S-(CF
3
)Thianthrenium and S-(CF
3
)dibenzothiophenium cations form potent chalcogen bonds (ChBs) with Mo(CO)
5
CN
−
, yielding S
2
N
2
supramolecular motifs. Crystal structures reveal shorter S N ...contacts opposite the CF
3
group compared to the aryl substituents. The energetic features of the ChBs have been studied using DFT calculations demonstrating the structure guiding role of ChBs.
Fine-tuning of the electrostatic potentials of sulfonium cations influences the lengths of S N chalcogen bonds in supramolecular assemblies.
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