A systematic review of Bayesian articles in psychology: The last 25 years

Although the statistical tools most often used by researchers in the field of psychology over the last 25 years are based on frequentist statistics, it is often claimed that the alternative Bayesian approach to statistics is gaining in popularity. In the current article, we investigated this claim by performing the very first systematic review of Bayesian psychological articles published between 1990 and 2015 (n = 1,579). We aim to provide a thorough presentation of the role Bayesian statistics plays in psychology. This historical assessment allows us to identify trends and see how Bayesian methods have been integrated into psychological research in the context of different statistical frameworks (e.g., hypothesis testing, cognitive models, IRT, SEM, etc.). We also describe take-home messages and provide “big-picture” recommendations to the field as Bayesian statistics becomes more popular. Our review indicated that Bayesian statistics is used in a variety of contexts across subfields of psychology and related disciplines. There are many different reasons why one might choose to use Bayes (e.g., the use of priors, estimating otherwise intractable models, modeling uncertainty, etc.). We found in this review that the use of Bayes has increased and broadened in the sense that this methodology can be used in a flexible manner to tackle many different forms of questions. We hope this presentation opens the door for a larger discussion regarding the current state of Bayesian statistics, as well as future trends.https://deepblue.lib.umich.edu/bitstream/2027.42/136925/1/A Systematic Review of Bayesian Articles in Psychology The Last 25 Years.pdfDescription of A Systematic Review of Bayesian Articles in Psychology The Last 25 Years.pdf : Main Articl

Pornography Use Profiles and the Emergence of Sexual Behaviors in Adolescence

This research longitudinally explored adolescent pornography (porn) consumption and its association with sexual development in early and middle adolescence. A four-wave design with half-year intervals investigated pornography consumption and different (sexual) activities, such as masturbation, French kissing, petting, giving/receiving manual and oral sex, and intercourse, among 630 respondents (47.9% female, mean age 13.7 years; SD = 0.48) years at T1). A latent growth mixture analysis of pornography consumption revealed two groups with relatively low pornography (LP; 51.8% of the boys, 91.4% of the girls) versus high pornography (HP; 48.2% of the boys; 8.6% of the girls) consumption across time. At T1, HP boys on average watched pornography less than once a month, but more than once a year at T1. At T4, their average pornography use had increased to almost one to two times a week. LP boys never watched pornography at T1. At T4, their average pornography use was still less than once a year. At T1, HP girls never watched pornography, but consumption increased to almost one to three times a month at T4. Across waves of the study, LP girls (almost) never watched pornography. A discrete-time survival mixture analysis of sexual developmental patterning indicated that, compared to their LP peers, both girls and boys in the HP groups showed accelerated development of masturbation, petting, and receiving manual sex. Girls in the HP group were also more inclined to receive oral sex, whereas boys in the HP group also showed earlier and more frequent manual sex and intercourse. Thus, whereas the HP group of boys was substantially larger compared to that of girls, pornography consumption was related to accelerated development of sexual activities for both genders across early and middle adolescence. The discussion deliberates on pornography as a driving force in adolescent sexual development versus pornography as a medium of choice for sexually advanced adolescents

Pushing the Limits : The Performance of Maximum Likelihood and Bayesian Estimation with Small and Unbalanced Samples in a Latent Growth Model

Longitudinal developmental research is often focused on patterns of change or growth across different (sub)groups of individuals. Particular to some research contexts, developmental inquiries may involve one or more (sub)groups that are small in nature and therefore difficult to properly capture through statistical analysis. The current study explores the lower-bound limits of subsample sizes in a multiple group latent growth modeling by means of a simulation study. We particularly focus on how the maximum likelihood (ML) and Bayesian estimation approaches differ when (sub)sample sizes are small. The results show that Bayesian estimation resolves computational issues that occur with ML estimation and that the addition of prior information can be the key to detect a difference between groups when sample and effect sizes are expected to be limited. The acquisition of prior information with respect to the smaller group is especially influential in this context

Where Do Priors Come From? : Applying Guidelines to Construct Informative Priors in Small Sample Research

This article demonstrates the usefulness of Bayesian estimation with small samples. In Bayesian estimation, prior information can be included, which increases the precision of the posterior distribution. The posterior distribution reflects likely parameter values given the current state of knowledge. An issue that has received little attention, however, is the acquisition of prior information. This study provides general guidelines to collect prior knowledge and formalize it in prior distributions. Moreover, this study demonstrates with an empirical application how prior knowledge can be acquired systematically. The article closes with a discussion that also warns against the misuse of prior information

Pushing the Limits : The Performance of Maximum Likelihood and Bayesian Estimation with Small and Unbalanced Samples in a Latent Growth Model

Longitudinal developmental research is often focused on patterns of change or growth across different (sub)groups of individuals. Particular to some research contexts, developmental inquiries may involve one or more (sub)groups that are small in nature and therefore difficult to properly capture through statistical analysis. The current study explores the lower-bound limits of subsample sizes in a multiple group latent growth modeling by means of a simulation study. We particularly focus on how the maximum likelihood (ML) and Bayesian estimation approaches differ when (sub)sample sizes are small. The results show that Bayesian estimation resolves computational issues that occur with ML estimation and that the addition of prior information can be the key to detect a difference between groups when sample and effect sizes are expected to be limited. The acquisition of prior information with respect to the smaller group is especially influential in this context

Longitudinal associations between prosocial behavior and behavioral problems across childhood: A robust random-intercept cross-lagged panel model

Prior studies have indicated that prosocial behavior might be a protective factor for developing internalizing and externalizing behavioral problems. However, little research has been conducted on within-person changes of prosocial behavior and behavioral problems over time. With random-intercept crosslagged panel models (RI-CLPMs), the current study analyzed longitudinal associations between prosocial behavior and behavioral problems in two twin cohorts (98% Western European): in early childhood (age M = 4.77, SD =.58, 52% girls, N = 440) and middle childhood (age M = 7.94, SD =.67, 51% girls, N = 512). To obtain robust results, two parental reported questionnaires and an observational task were used as prosocial behavior assessments. In line with the literature, we found a significant between-person association between externalizing behavior and parent reported prosocial behavior in middle childhood, but not in early childhood. Some evidence indicated that changes in externalizing problems affect later prosocial behavior in middle childhood. Overall, however, the RI-CLPMs provided most support for the hypothesis that within-person changes in prosocial behavior are not related to within-person changes in behavioral problems. Thus, our findings did not support the hypothesis that increased prosocial behavior directly results in decreased behavioral problems, but emphasizes the need to take into account the multifaceted nature of prosocial behavio

Exploring meaning in life through a brief photo-ethnographic intervention using Instagram: a Bayesian growth modelling approach

The 4th Industrial Revolution has provided several digital platforms through which to disseminate scalable and cost-effective interventions (e.g. Apps and Social media). Instagram, a popular visual-ethnographic social media platform, could be employed to implement and scale interventions aimed at aiding individuals in discovering meaning in life and gratitude through capturing and reflecting upon photographs of meaningful moments. The purpose of this study was to evaluate the long-term effectiveness of a brief photo-ethnographic meaningful-moments intervention aimed at enhancing wellbeing (life satisfaction) and managing common mental health problems (stress/depression/anxiety) through Instagram. A 4 × 1 treatment-only intervention design was used to assess the immediate and long-term changes in meaning, gratitude, life satisfaction, and depression/stress/anxiety. Within-person development on the subscales was evaluated with Bayesian level and shape models. The results showed significant improvements in all factors directly after the intervention. Over the long term, significant changes with baseline measures for the presence of meaning, appreciation for others, and life satisfaction was found. Participants also reported a significant but small change in depression over the long term. Instagram could therefore be an interesting tool to consider when the aim is to enhance wellbeing and manage common mental health problems in the short-, medium- and long-term

Mother-Child Interactions and Externalizing Behavior Problems in Preschoolers over Time: Inhibitory Control as a Mediator

Previous research has shown links between parenting and externalizing behavior problems in young children over time. Associations between inhibitory control, one of the executive functions, and externalizing behavior problems are widely established as well. Yet, the role of inhibitory control in the maintenance and change of externalizing behavior problems over time remains unclear. We examined whether inhibitory control could explain the link between mother-child interactions measured on a moment-to-moment timescale and preschoolers' externalizing behavior problems as reported by teachers. With a sample of 173 predominantly clinically referred preschoolers (76.9% boys) we tested a longitudinal model proposing that affective dyadic flexibility and maternal negative affect predict as well as interact in predicting hyperactive/impulsive behavior and aggressive behavior, with preschoolers' inhibitory control as a mediator. Our results provide support for this model for preschoolers' hyperactive/impulsive behavior, but not for aggressive behavior. Hence, inhibitory control is identified as a mechanism linking the content and structure of mother-child interactions to preschoolers' hyperactivity and impulsivity over time

Systematically Defined Informative Priors in Bayesian Estimation: An Empirical Application on the Transmission of Internalizing Symptoms Through Mother-Adolescent Interaction Behavior

Background: Bayesian estimation with informative priors permits updating previous findings with new data, thus generating cumulative knowledge. To reduce subjectivity in the process, the present study emphasizes how to systematically weigh and specify informative priors and highlights the use of different aggregation methods using an empirical example that examined whether observed mother-adolescent positive and negative interaction behavior mediate the associations between maternal and adolescent internalizing symptoms across early to mid-adolescence in a 3-year longitudinal multi-method design. Methods: The sample consisted of 102 mother-adolescent dyads (39.2% girls, M age T1 = 13.0). Mothers and adolescents reported on their internalizing symptoms and their interaction behaviors were observed during a conflict task. We systematically searched for previous studies and used an expert-informed weighting system to account for their relevance. Subsequently, we aggregated the (power) priors using three methods: linear pooling, logarithmic pooling, and fitting a normal distribution to the linear pool by means of maximum likelihood estimation. We compared the impact of the three differently specified informative priors and default priors on the prior predictive distribution, shrinkage, and the posterior estimates. Results: The prior predictive distributions for the three informative priors were quite similar and centered around the observed data mean. The shrinkage results showed that the logarithmic pooled priors were least affected by the data. Most posterior estimates were similar across the different priors. Some previous studies contained extremely specific information, resulting in bimodal posterior distributions for the analyses with linear pooled prior distributions. The posteriors following the fitted normal priors and default priors were very similar. Overall, we found that maternal, but not adolescent, internalizing symptoms predicted subsequent mother-adolescent interaction behavior, whereas negative interaction behavior seemed to predict subsequent internalizing symptoms. Evidence regarding mediation effects remained limited. Conclusion: A systematic search for previous information and an expert-built weighting system contribute to a clear specification of power priors. How information from multiple previous studies should be included in the prior depends on theoretical considerations (e.g., the prior is an updated Bayesian distribution), and may also be affected by pragmatic considerations regarding the impact of the previous results at hand (e.g., extremely specific previous results)