scholarly journals Sexual Consent Perceptions of a Fictional Vignette: A Latent Growth Curve Model

2021 ◽  
Author(s):  
Malachi Willis ◽  
Kristen N. Jozkowski
Keyword(s):  
Growth Curve ◽  
Structural Equation ◽  
Sexual Consent ◽  
Latent Growth Curve ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Latent Growth ◽  
Growth Curve Models ◽  
Mean Differences ◽  
Multilevel Structural Equation

AbstractSexual consent can be conceptualized as a process of accumulating cues that build toward and continue throughout a consensual sexual encounter. How people perceive the cues of others during this process is an important aspect of consent. However, previous research has not investigated the trajectories of people’s consent perceptions throughout such a process. Using a novel staggered vignette protocol, we examined participants’ (N = 1218; 64.4% female) perceptions of fictional targets’ sexual consent at 11 time points. We tested latent growth curve models using multilevel structural equation modeling to examine trajectories in consent perceptions over the course of the vignette. We hypothesized that mean differences and rates of change would be associated with several constructs relevant to sexual consent. We found that initial consent perceptions and trends over the course of the vignette varied by whether the participant was a university student, by an alcohol manipulation in the vignette, by the fictional target’s sex, and by type of sexual behavior. Researchers should examine whether our findings on consent perceptions of a fictional vignette extend to people’s actual sexual encounters, including potential associations between the three primary aspects of sexual consent: perceptions, feelings, and communication.

scholarly journals A magnifying glass for the study of coupled developmental changes: Combining psychological networks and latent growth models

2021 ◽  
Author(s):  
Marie Katharina Deserno ◽  
Maien Sachisthal ◽  
Sacha Epskamp ◽  
Maartje Eusebia Josefa Raijmakers
Keyword(s):  
Growth Curve ◽  
Structural Equation ◽  
Growth Parameter ◽  
Developmental Theory ◽  
Latent Growth Curve ◽  
Developmental Changes ◽  
Equation Modeling ◽  
Latent Growth ◽  
Growth Curve Models ◽  
Latent Growth Curve Models

In recent years, methodological advances for analyzing developmental data are coming thick and fast. Two of the most popular and rapidly developing frameworks are (i) longitudinal structural equation modeling and (ii) network modeling. The present paper outlines the incremental gain in what we can learn from data about co-developing skills and challenges when using these two frameworks in tandem. First, we discuss the proposed analytic paradigm in the context of fundamental questions in developmental psychology. Second, we present two different paths to formalize such questions, introducing, first, a recently developed network model for longitudinal panel data and, second, the notion of growth parameter networks based on latent growth curve models. Used in tandem, they can provide new insights into the longitudinal co-development of developmental domains. Specifically, we focus on integrating growth parameters from latent growth curve models into networks and analyzing them as such. Third, we illustrate these analytic steps with an empirical example using longitudinal data from the Millenium Cohort Study (N=7623). As illustrated and discussed in the real data example, the proposed approach offers a magnifying glass to the study of coupled developmental changes. Teasing apart the processes underlying the heterogeneity of childhood development can, in turn, add to substantive developmental theory.

scholarly journals Analyzing Organizational Growth in Repeated Cross-Sectional Designs Using Multilevel Structural Equation Modeling

Methodology ◽  
2017 ◽  
Vol 13 (3) ◽  
pp. 83-97 ◽  
Author(s):  
Jan Hochweber ◽  
Johannes Hartig
Keyword(s):  
Structural Equation Modeling ◽  
Growth Curve ◽  
Cross Sections ◽  
Structural Equation ◽  
Organizational Level ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Organizational Growth ◽  
Multilevel Structural Equation ◽  
Level Variable

Abstract. In repeated cross-sections of organizations, different individuals are sampled from the same set of organizations at each time point of measurement. As a result, common longitudinal data analysis methods (e.g., latent growth curve models) cannot be applied in the usual way. In this contribution, a multilevel structural equation modeling approach to analyze data from repeated cross-sections is presented. Results from a simulation study are reported which aimed at obtaining guidelines on appropriate sample sizes. We focused on a situation where linear growth occurs at the organizational level, and organizational growth is predicted by a single organizational level variable. The power to identify an effect of this organizational level variable was moderately to strongly positively related to number of measurement occasions, number of groups, group size, intraclass correlation, effect size, and growth curve reliability. The Type I error rate was close to the nominal alpha level under all conditions.

Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

2019 ◽  
Vol 50 (1) ◽  
pp. 24-37
Author(s):  
Ben Porter ◽  
Camilla S. Øverup ◽  
Julie A. Brunson ◽  
Paras D. Mehta
Keyword(s):  
Structural Equation Modeling ◽  
Social Relations ◽  
Latent Variables ◽  
Structural Equation ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Complete Understanding ◽  
Social Relations Model ◽  
Flexible Framework ◽  
Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

Impulsivity, Affect, and Stress in Daily Life: Examining a Cascade Model of Urgency

2019 ◽  
Author(s):  
Brinkley M. Sharpe ◽  
Leonard Simms ◽  
Aidan G.C. Wright
Keyword(s):  
Negative Affect ◽  
Structural Equation ◽  
Psychiatric Patients ◽  
Cascade Model ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Daily Stress ◽  
Daily Diary Study ◽  
Daily Affect ◽  
Multilevel Structural Equation

Using multilevel structural equation modeling, we examined within- and between-person predictors of daily impulsivity, with a particular focus on testing a cascade model of affect and daily stress in a 100-day daily diary study of 101 psychiatric patients with personality disorder diagnoses. On average (i.e., fixed effect), within-person increases in daily stress were associated with increased daily impulsivity, both independently and as accounted for by positive associations with increased negative and positive affect. Higher Personality Inventory for DSM-5 (PID-5) Impulsivity scores were associated with amplified within-person links between impulsivity and daily stress and negative affect, but not the links between daily stress and either positive or negative affect. The results of this cascade model are consistent with the hypothesized link between daily affect and stress and daily impulsivity while providing further evidence for the validity of the PID-5 Impulsivity scale and its ability to predict daily impulsivity above and beyond fluctuations in affect and stress.

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