Callous Unemotional Meta-Analysis

A theoretically driven meta-analysis of the correlates of callous and unemotional traits among youth

Gaussian Process Imputation Models

Understanding new approaches to old imputations problems

IBI VizEdit

A brand-new, open-source, RShiny application for processing and editing heart rate data

Individual Risk for Anxiety and Depression

Understanding the daily emotional lives of individuals who vary in dispositional risk for anxiety and depression

Preventing Anxiety in Early Childhood

Investigating a recently developed intervention for inhibited and anxious preschoolers

Social Withdrawal Meta-Analysis

A quantiative synthesis of 40 years of research on the correlates and consequences of childhood social withdrawal

Recent Posts

More Posts

Spurred on by my boss Alex Shackman, I have been working to figure out a good way to visualize different sources of variation in momentary mood. The most common way of visually depicting variance decompositions from the sort of multilevel models we used to analyze our data is a stacked bar plot. So that seemed like a good place to start. Figure 1 - Stacked Barplot of Model Variance Decomposition


In the first post in this series, I described the impetus for this trek through statistical modeling, machine learning and artificial intelligence. I also provided an initial set of comparisons for three different approaches to classification: k-means, k-nearest neighbor, and latent profile analysis (model-based clustering). If you want to check those mini-walkthroughs out click here. As a reminder, my goal here is to compare and contrast different approaches to data analysis and predictive modeling that are, in my mind, arbitrarily lumped into statistical modeling and machine learing/artificial intelligence categories.


I was recently interviewing for a job and a recruiter asked me if I wanted to enhance aspects of my machine learning background on my resume before she passed it on for the next round of reviews. I resisted the urge to chide her in the moment by pointing out the flawed distinction between statistics and machine learning, an unnecessary admonishment that would have been to no one’s benefit. The modal outcome would have been me sounding as if I was speaking with all of the arrogance, jackassery, and superiority that a recently minted Ph.


Overview: This is the second post in a three-part blog series I am putting together. If you have not read the first post in this series, you may want to go back and check it out. In this post, I will focus on running and evaluating the imputation model itself, having identified the appropriate covariates that help account for missingness in the first post. Data Brief Description: The data in question come from a study that involved a one-week ecological momentary assessment (EMA) protocol.


It is official. The program I have spent the better part of a year working on, the very centerpiece of my dissertation, works. Or at least, early indicators are in, and based on 22 cases, some of which required a great deal of manual editing, the program is returning estimates in line with expectations. Backing up, as I trip a little over my excitement, IBI VizEdit is an Rshiny application I created to help our lab process and edit heart rate data.


Selected Publications

Considerable evidence has accumulated supporting transactional influences between early childhood behavioral inhibition (BI), parent-child and child-peer relationships, and the development of anxiety disorders in adolescence and adulthood. Drawing from this literature, the Turtle Program was designed to treat children high in BI by intervening at the level of both parents and peers. In this pilot study, we sought to determine whether benefits of participating in the Turtle Program extended to children’s classrooms in the form of increased positive social interactions with peers. Forty inhibited children (42-60 months) and their parent(s) were randomized to either the Turtle Program (n = 18) or a waitlist control group (WLC; n = 22). The Turtle Program involved 8 weeks of concurrent parent and child treatment. Trained research assistants, blind to treatment condition, coded participants’ social interactions with peers during free play at each child’s preschool at the beginning and end of treatment. Teachers unaware of group assignment also provided reports of social behaviors at these time points. Reliable change index scores revealed that both Turtle Program and WLC participants experienced relatively high rates of reliable increases in observed peer play interactions from pre- to post-treatment (73.3% and 42.1% respectively). Additionally, Turtle Program participants experienced high rates of reliable increase in observed initiations to peers (73.3%) as well as a moderate degree of reliable decrease in teacher-reported displays of fear/anxiety (33.3%). These data provide preliminary, but promising, evidence that increases in children’s social behaviors as a result of participation in the Turtle Program generalize to their preschool classrooms.
Journal of Child and Family Studies, 2018

In many ways this chapter concerns a topic unlike most that appear in this Handbook. Rather than focusing on the ways in which children and adolescents may interact with their peers, this chapter is centered on those youth who, for whatever reason, engage in comparatively little peer interaction. As noted throughout this Handbook, children who are socially engaging and competent interact with peers in ways that allow the establishment and maintenance of positive relationships. Such children fare well in their social and academic lives. However, their socially unskilled counterparts often suffer from peer rejection, friendlessness, and loneliness; furthermore, they are thought to be at risk for a wide range of socioemotional and academic difficulties (see Rubin, Bukowski, & Bowker, 2015 for a review). In this chapter, we focus on children who avoid and rarely interact with their peers and who may suffer deeply for their withdrawal.
In the Handbook of Peer Interactions, Relationships, and Groups, 2018

Recent Publications

. Generalization of an early intervention for inhibited preschoolers to the classroom setting. Journal of Child and Family Studies, 2018.


. Withdrawing from the peer group. In the Handbook of Peer Interactions, Relationships, and Groups, 2018.

Book Site

. Dispositional negativity in the wild: Social environment governs momentary emotional experience. Emotion, 2017.

Preprint PubMed

. Interpersonal predictors of stress generation: Is there a super factor?. British Journal of Psychology, 2017.

Preprint Journal Site

. Shyness, preference for solitude and adolescent internalizing: The roles of maternal, paternal, and best-friend support. Journal of Research on Adolescence, 2017.

Preprint Journal Site