Abstract
Rejection and acceptance are potent elicitors of feelings of loneliness, and research on the effects of bullying, ostracism, and social exclusion in young and older adults illustrates the connection. In fact, one of the most frequently used measures of loneliness asks about experiences of rejection/acceptance (e.g., how often do you feel left out, that you are part of a group of friends, that there are people who really understand you). In addition, my analyses have shown that loneliness has three dimensions, of which one is a sense of belonging to a larger group. This sense of belonging or acceptance is an understudied but I think important player in some of the consequences of loneliness. This may be particularly true in clinical populations with psychiatric diagnoses. At the conclusion of this presentation, the learner should be better able to:

• Summarize an evolutionary theory of loneliness;
• Describe the consequences of loneliness for health and well-being;
• Identify environmental circumstances, experiences, and individual characteristics that may thwart a sense of belonging and increase feelings of loneliness; and
• Appraise the belongingness needs and challenges of high-risk segments of the population.

Abstract
Here is a problem that can arise when analyzing certain kinds of samples of a numeric variable: a large number of data points cluster at the maximum or minimum of the relevant scale, but the distribution is otherwise mostly as expected (e.g. normal, uniform, etc). This situation presents a number of challenges for interpretability and model selection, and cannot always be remedied by standard transformations like log or arcsine. In this presentation I will illustrate an instance of this problem that I recently encountered in child vocabulary data. I will show how censored ("tobit") regression models provide a reasonable solution to this problem, using the VGAM package in R (Yee et al., 2015). Using simulated datasets, I will also show how tobit model coefficients can be decomposed so that they can be read (almost) like more familiar OLS coefficients.

Abstract
Jaclyn will be presenting some crosstabs and preliminary regression results from an experimental vignette survey question. The vignette describes a dual-career couple in which one partner gets offered a job in another city. Respondents answer questions about what they think the couple should do. [She] needs feedback for thinking about how to analyze and interpret these data.

For the kickoff meeting, we'll get together, do some extended intros, and develop a gameplan for moving forward.