Online measurement of mental representations of complex spatial decision problems: Comparison of CNET and hard laddering

This paper introduces the online Causal Network Elicitation Technique (CNET), as a technique for measuring components of mental representations of choice tasks and compares it with the more common technique of online ‘hard’ laddering (HL). While CNET works in basically two phases, one in open question format and one as guided linking of attributes and benefits, HL works completely structured with revealed attributes and benefits. Mental representations of two activity travel tasks were collected with both techniques among members of a nationwide Dutch household panel. The results confirm the hypothesis that the revealed format of variables in HL has an effect on the indication of variables as the elicited mental representations are almost twice as big for HL than for CNET. Furthermore, it turned out that CNET is more sensitive in measuring shifts among attributes in the mental representations for situational changes of the activity-travel task.     

Relationship between collectivism and corruption in American and Chinese books: A historical perspective

Previous research on the relationship between collectivism and corruption has not investigated their co‐variation over time. In this study, we use Google Ngram Viewer to track the frequency of words related to collectivism and corruption in American books (1800–2000) and in Chinese Books (1970–2008). The results demonstrate that a positive association between the usage of these terms during the periods in both Chinese and American books, with changes in words related to collectivism preceding changes in words related to corruption in American books. The theoretical and practical implications are also discussed.     

Secularity and Irreligion in Cross‐National Context: A Nonlinear Approach

As part of the conversation about the characteristics and scope of secularization in contemporary society, the implications of low levels of self‐defined atheism and explicit rejection of religion in nations with low levels of religious beliefs are not yet sufficiently explored. In response, this study uses aggregated data from the World Values Survey, the European Values Study, and Cross‐National Socio‐Economic and Religion Data from the Association of Religion Data Archives to investigate the relationships between nonbelief, atheism, and lack of confidence in churches or religious organizations. Regression findings show a concave curvilinear relationship between secularity (measured as the percentage of the population that does not believe in God) and irreligion (measured as (1) the percentage of self‐defined atheists in a country and (2) the percentage of individuals in a country who have no confidence at all in religious organizations). In other words, this study suggests that nonbelief is associated with an increase in self‐defined atheism and the lack of confidence in religious organizations, but that this effect wanes the more secular a society is. The findings further highlight the complexity of nonreligiosity and imply that a linear association cannot be assumed between measures of secularization, secularity, and irreligion.     

A New Multilevel CART Algorithm for Multilevel Data with Binary Outcomes

The multilevel logistic regression model (M-logit) is the standard model for modeling multilevel data with binary outcomes. However, many assumptions and restrictions should be considered when applying this model for unbiased estimation. To overcome these limitations, we proposed a multilevel CART (M-CART) algorithm which combines the M-logit and single level CART (S-CART) within the framework of the expectation-maximization. Simulation results showed that the proposed M-CART provided substantial improvements on classification accuracy, sensitivity, and specific over the M-logit, S-CART, and single level logistic regression model when modeling multilevel data with binary outcomes. This benefit of using M-CART was consistently found across different conditions of sample size, intra-class correlation, and when relationships between predictors and outcomes were nonlinear and nonadditive.     

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.