The addition of error bars in graphs can greatly assist readers in determining where differences lie between groups or conditions. The use of error bars to represent the standard error of the mean or confidence intervals is relatively straightforward for between-subject (independent group) designs. However, confusion still abounds as to how best to graph these same measures for within-subject (repeated-measures) designs. This paper serves both to consolidate previous recommendations regarding error bars for within-subject studies and to provide clear instructions as to how to implement these recommendations using typical statistical packages.

The problem of calculating error bars in within-subject designs has proven to be a difficult problem and has received much attention in recent years. Baguley (Behavior Research Methods, 44, 158-175, 2012) recommended what he called the Cousineau-Morey method. This method requires two steps: first, centering the data set in a certain way to remove between-subject differences and, second, integrating a correction factor to debias the standard errors obtained from the normalized data set. However, within some statistical packages, it can be difficult to integrate this correction factor. Baguley (2012) proposed a solution that works well in most statistical packages in which the alpha level is altered to incorporate the correction factor. However, with this solution, it is possible to plot confidence intervals, but not standard errors. Here, we propose a second solution that can return confidence intervals or standard error bars in a mean plot.

Health Behavior in School-Aged Children: NEXT Longitudinal Study 2009-2013, https://clinicaltrials.gov/ct2/show/NCT01031160?term=Simons-Morton&rank=3, NCT01031160.

Children born preterm have poorer outcomes than children born full-term, but the caregiving environment can ameliorate some of these differences. Recent research has proposed that preterm birth may be a plasticity factor, leading to better outcomes for preterm than full-term infants in higher quality environments. This analysis uses data from two waves of an Irish study of children (at 9 months and 3 years of age, n=11,134 children) and their caregivers (n=11,132 mothers, n=9,998 fathers) to investigate differences in how caregiving affects social, cognitive, and motor skills between full-term, late preterm, and very preterm children. Results indicate that parental emotional distress and quality of attachment are important for child outcomes. Both being born very preterm and late preterm continue to be risk factors for poorer outcomes at 3 years of age. Only fathers’ emotional distress significantly moderated the effect of prematurity on infants’ cognitive and social outcomes – no other interactions between prematurity and environment were significant. These interactions were somewhat in line with diathesis stress, but the effect sizes were too small to provide strong support for this model. There is no evidence that preterm birth is a plasticity factor.

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This study captures sleep habits of adolescents one year after high school regardless of school and/or working status. Implications and future directions are discussed.

Introduction Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior and crashes and near-crashes, using naturalistic driving research methods. Method Participants’ driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18 months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants’ KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Results Conscientiousness was marginally negatively associated with CNC (path c = −0.034, p = .09) and both potential mediators KRD (path a = −0.040, p = .09) and secondary task engagement while driving (path a = −0.053, p = .03). KRD, but not secondary task engagement, was found to mediate (path b = 0.376, p = .02) the relationship between conscientiousness and CNC (path c’ = −0.025, p = .20). Conclusions Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, suffered fewer CNC. Practical Applications Part of the variability in crash-risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers’ personality into account when providing guidance, and establishing norms and expectations about driving.

Objective-To examine changes in health behaviors among U.S. emerging adults one year after high school.Participants-The national sample of participants (n=1927), including those attending 4-year college/university (n=884), 2-year colleges/technical schools (n=588), and no college (n=455), participated in annual spring surveys 2013-2014.Methods-Health behaviors were assessed the last year of high school and first year of college; differences by college status controlling for previous-year values were estimated using regression analyses.Correspondence to: Bruce Simons-Morton, mortonb@mail.nih.gov. Conclusions-Health risk behaviors among emerging adults varied by college status. HHS Public Access