The Impact of Item Misspecification and Dichotomization on Class and Parameter Recovery in LCA of Count Data

Mixture analysis of count data has become increasingly popular among researchers of substance use, behavioral analysis, and program evaluation. However, this increase in popularity seems to have occurred along with adoption of some conventions in model specification based on arbitrary heuristics that may impact the validity of results. Findings from a systematic review of recent drug and alcohol publications suggested count variables are often dichotomized or misspecified as continuous normal indicators in mixture analysis. Prior research suggests that misspecifying skewed distributions of continuous indicators in mixture analysis introduces bias, though the consequences of this practice when applied to count indicators has not been studied. The present work describes results from a simulation study examining bias in mixture recovery when count indicators are dichotomized (median split; presence vs. absence), ordinalized, or the distribution is misspecified (continuous normal; incorrect count distribution). All distributional misspecifications and methods of categorizing resulted in greater bias in parameter estimates and recovery of class membership relative to specifying the true distribution, though dichotomization appeared to improve class enumeration accuracy relative to all other specifications. Overall, results demonstrate the importance of accurately modeling count indicators in mixture analysis, as misspecification and categorizing data can distort study outcomes.     

The contagious impact of playing violent video games on aggression: Longitudinal evidence

Meta-analyses have shown that violent video game play increases aggression in the player. The present research suggests that violent video game play also affects individuals with whom the player is connected. A longitudinal study (N = 980) asked participants to report on their amount of violent video game play and level of aggression as well as how they perceive their friends and examined the association between the participant's aggression and their friends’ amount of violent video game play. As hypothesized, friends’ amount of violent video game play at Time 1 was associated with the participant's aggression at Time 2 even when controlling for the impact of the participant's aggression at Time 1. Mediation analyses showed that friends’ aggression at Time 1 accounted for the impact of friends’ amount of violent video game play at Time 1 on the participant's aggression at Time 2. These findings suggest that increased aggression in video game players has an impact on the player's social network.     

Terror in time: extending culturomics to address basic terror management mechanisms

Building on Google's efforts to scan millions of books, this article introduces methodology using a database of annual word frequencies of the 40,000 most frequently occurring words in the American literature between 1800 and 2009. The current paper uses this methodology to replicate and identify terror management processes in historical context. Variation in frequencies of word usage of constructs relevant to terror management theory (e.g. death, worldview, self-esteem, relationships) are investigated over a time period of 209 years. Study 1 corroborated previous TMT findings and demonstrated that word use of constructs related to death and of constructs related to patriotism and romantic relationships significantly co-vary over time. Study 2 showed that the use of the word “death” most strongly co-varies over time with the use of medical constructs, but also co-varies with the use of constructs related to violence, relationships, religion, positive sentiment, and negative sentiment. Study 3 found that a change in the use of death related words is associated with an increase in the use of fear related words, but not in anxiety related words. Results indicate that the described methodology generates valuable insights regarding terror management theory and provide new perspectives for theoretical advances.     

Using Dynamic Panel Models to Study Age‐related Differences and Time‐related Changes in Personality

Along with an increasing interest in the plasticity and role of personality across the adult lifespan comes the need for a diverse set of innovative statistical approaches to study it. With this paper, we set out to illustrate some of the possibilities and challenges in modelling age‐related differences and time‐related changes in personality psychology by means of dynamic panel models. To this end, we first distinguish between the study of age‐related differences and time‐related changes and demonstrate how the treatment of age and time as either discrete or continuous variables implies important modelling choices. Second, we present a selection of four example cases that address the topic of age moderation in diverse matters and with different objectives. Based on our cross‐tabulation of age and time as discrete and continuous variables, the first two example cases represent fairly well‐established models (cases A and B), whereas the remaining cases are used to illustrate current developments in the field (cases C and D). We close the paper with some final remarks on current limitation and future research directions. © 2019 European Association of Personality Psychology     

A Systematic Review of Online Response Rates in Four Counseling Journals

This systematic review of articles published in 4 counseling journals found 207 articles that used online recruitment, of which 98 (47.3%) reported a response rate. These 98 studies collectively contained 22,466 individual participants. Results showed that nearly one third of all empirical articles used online recruitment, and the average response rate was 34.2% (SD = 22.6). Response rates are further described by journal, population, research methodology, and recruitment strategy. Researcher‐reported issues with online recruitment and data collection were also analyzed qualitatively, and recommendations for researchers are discussed.     

Why Care about Being an Agent?

The question ‘Why care about being an agent?’ asks for reasons to be something that appears to be non-optional. But perhaps it is closer to the question ‘Why be moral?’; or so I shall argue. Here the constitutivist answer—that we cannot help but have this aim—seems to be the best answer available. I suggest that, regardless of whether constitutivism is true, it is an incomplete answer. I argue that we should instead answer the question by looking at our evaluative commitments to the exercise of our other capacities for which being a full-blown agent is a necessary condition. Thus, the only kind of reason available is hypothetical rather than categorical. The status of this reason may seem to undermine the importance of this answer. I show, however, that it both achieves much of what we want when we cite categorical reasons and highlights why agency is valuable.     

A Monte Carlo evaluation of masked visual analysis in response‐guided versus fixed‐criteria multiple‐baseline designs

We developed masked visual analysis (MVA) as a structured complement to traditional visual analysis. The purpose of the present investigation was to compare the effects of computer‐simulated MVA of a four‐case multiple‐baseline (MB) design in which the phase lengths are determined by an ongoing visual analysis (i.e., response‐guided) versus those in which the phase lengths are established a priori (i.e., fixed criteria). We observed an acceptably low probability (less than .05) of false detection of treatment effects. The probability of correctly detecting a true effect frequently exceeded .80 and was higher when: (a) the masked visual analyst extended phases based on an ongoing visual analysis, (b) the effects were larger, (c) the effects were more immediate and abrupt, and (d) the effects of random and extraneous error factors were simpler. Our findings indicate that MVA is a valuable combined methodological and data‐analysis tool for single‐case intervention researchers.