Matching Items (19)
Description
Psychologists report effect sizes in randomized controlled trials to facilitate interpretation and inform clinical or policy guidance. Since commonly used effect size measures (e.g., standardized mean difference) are not sensitive to heterogeneous treatment effects, methodologists have suggested the use of an alternative effect size δ, a between-subjects causal parameter describing the probability that the outcome of a random participant in the treatment group is better than the outcome of another random participant in the control group. Although this effect size is useful, researchers could mistakenly use δ to describe its within-subject analogue, ψ, the probability that an individual will do better under the treatment than the control. Hand’s paradox describes the situation where ψ and δ are on opposing sides of 0.5: δ may imply most are helped whereas the (unknown) underlying ψ indicates that most are harmed by the treatment. The current study used Monte Carlo simulations to investigate plausible situations under which Hand’s paradox does and does not occur, tracked the magnitude of the discrepancy between ψ and δ, and explored whether the size of the discrepancy could be reduced with a relevant covariate. The findings suggested that although the paradox should not occur under bivariate normal data conditions in the population, there could be sample cases with the paradox. The magnitude of the discrepancy between ψ and δ depended on both the size of the average treatment effect and the underlying correlation between the potential outcomes, ρ. Smaller effects led to larger discrepancies when ρ < 0 and ρ = 1, whereas larger effects led to larger discrepancies when 0 < ρ < 1. It was useful to consider a relevant covariate when calculating ψ and δ. Although ψ and δ were still discrepant within covariate levels, results indicated that conditioning upon relevant covariates is still useful in describing heterogeneous treatment effects.
ContributorsLiu, Xinran (Author) / Anderson, Samantha F (Thesis advisor) / McNeish, Daniel (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2023
Description
The proliferation of intensive longitudinal datasets has necessitated the development of analytical techniques that are flexible and accessible to researchers collecting dyadic or individual data. Dynamic structural equation models (DSEMs), as implemented in Mplus, provides the flexibility researchers require by combining components from multilevel modeling, structural equation modeling, and time series analyses. This dissertation project presents a simulation study that evaluates the performance of categorical DSEM using a probit link function across different numbers of clusters (N = 50 or 200), timepoints (T = 14, 28, or 56), categories on the outcome (2, 3, or 5), and distribution of responses on the outcome (symmetric/approximate normal, skewed, or uniform) for both univariate and multivariate models (representing individual data and dyadic longitudinal Actor-Partner Interdependence Model data, respectively). The 3- and 5-category model conditions were also evaluated as continuous DSEMs across the same cluster, timepoint, and distribution conditions to evaluate to what extent ignoring the categorical nature of the outcome impacted model performance. Results indicated that previously-suggested minimums for number of clusters and timepoints from studies evaluating continuous DSEM performance with continuous outcomes are not large enough to produce unbiased and adequately powered models in categorical DSEM. The distribution of responses on the outcome did not have a noticeable impact in model performance for categorical DSEM, but did affect model performance when fitting a continuous DSEM to the same datasets. Ignoring the categorical nature of the outcome lead to underestimated effects across parameters and conditions, and showed large Type-I error rates in the N = 200 cluster conditions.
ContributorsSavord, Andrea (Author) / McNeish, Daniel (Thesis advisor) / Grimm, Kevin J (Committee member) / Iida, Masumi (Committee member) / Levy, Roy (Committee member) / Arizona State University (Publisher)
Created2023
Description
Behavior challenges impact children and educational professionals on a daily basis; however, it is difficult for educators to obtain high quality training in behavior management. The purpose of this study was to compare cognitive apprenticeship and group work, two teaching methods, to determine which provides better knowledge and implementation outcomes for educators taking a course on behavior analysis. Seventeen educational professionals currently working with students who display challenging behavior were randomly assigned to the cognitive apprenticeship or group work conditions. The difference between the conditions is the introduction of a coach in the cognitive apprenticeship condition. The coach guides learners through the process of understanding and using behavior analysis throughout the course by providing feedback, scaffolding, and encouraging reflection and exploration. Participants completed pre-, post-, and post-posttests that measured their knowledge of behavior analysis and how well they implemented the skills taught in the course. Additionally, they completed weekly quizzes and reported how often they used the skills in real-life situations. Overall group differences across time points for knowledge and implementation scores were analyzed using a repeated measures analysis of variance (ANOVA). There were significant differences across time for both scores but not condition or time by condition. A covariance pattern model was used to determine if self-efficacy, self-confidence, previous behavior knowledge, or overall quiz performance predicted the variance in knowledge and implementation scores on the pre-, post-, and post-posttests across conditions. Time was the only significant predictor of knowledge scores, while time, condition and self-efficacy significantly predicted the variance in implementation scores. Additionally, one-way ANOVAs were used to find condition-based differences in quiz scores and practical skill use, neither of which were significant. Finally, a linear regression was used to determine if on quiz performance predicts the use of skills in real-world settings, which it did not. The courses impact on learning, skill use, and student behavior as well as future applications are discussed.
ContributorsSacchetta, Melissa (Author) / Gray, Shelley (Thesis advisor) / Braden, B. Blair (Committee member) / McNeish, Daniel (Committee member) / Zuiker, Steve (Committee member) / Arizona State University (Publisher)
Created2022
Description
Attendance and engagement in available parenting interventions in both research and community settings is often inconsistent. Recent research suggests that varying the delivery modality of the intervention (i.e., in-person, telehealth, or online) has the potential to increase engagement with evidence-based parenting programs. However, while it is known that both facilitator and parent characteristics also influence engagement, no study has evaluated whether those characteristics moderate the influence that modality has on engagement. Utilizing data from the randomized controlled comparative effectiveness trial of the After Deployment, Adaptive Parenting Tools intervention, this study aimed to assess whether facilitators’ gender, military background, and competence moderated the effect of modality on parents’ engagement. Results suggested that parents were significantly more likely to have attended when they were randomized to the telehealth condition. Additionally, while there were no moderating relationships, female facilitators and facilitators who were more competent had overall higher attendance. Additionally, in the group format, facilitators with military backgrounds had higher engagement than those who did not. Understanding the effects that delivery modality and facilitators have on parental engagement is critical to continue and amplify implementation efforts in community settings.
ContributorsBasha, Sydni A. J. (Author) / Gewirtz, Abigail H (Thesis advisor) / Berkel, Cady (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
Description
Mediation analysis is integral to psychology, investigating human behavior’s causal mechanisms. The diversity of explanations for human behavior has implications for the estimation and interpretation of statistical mediation models. Individuals can have similar observed outcomes while undergoing different causal processes or different observed outcomes while receiving the same treatment. Researchers can employ diverse strategies when studying individual differences in multiple mediation pathways, including individual fit measures and analysis of residuals. This dissertation investigates the use of individual residuals and fit measures to identify individual differences in multiple mediation pathways. More specifically, this study focuses on mediation model residuals in a heterogeneous population in which some people experience indirect effects through one mediator and others experience indirect effects through a different mediator. A simulation study investigates 162 conditions defined by effect size and sample size for three proposed methods: residual differences, delta z, and generalized Cook’s distance. Results indicate that analogs of Type 1 error rates are generally acceptable for the method of residual differences, but statistical power is limited. Likewise, neither delta z nor gCd could reliably distinguish between contrasts that had true effects and those that did not. The outcomes of this study reveal the potential for statistical measures of individual mediation. However, limitations related to unequal subpopulation variances, multiple dependent variables, the inherent relationship between direct effects and unestimated indirect effects, and minimal contrast effects require more research to develop a simple method that researchers can use on single data sets.
ContributorsSmyth, Heather Lynn (Author) / MacKinnon, David (Thesis advisor) / Tein, Jenn-Yun (Committee member) / McNeish, Daniel (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2022
Description
This project studied a four-variable single mediator model, a single mediator model: X (independent variable) to M (mediator) to Y (dependent variable), and a confounder (U) that influences M and Y. Confounding represents a threat to the causal interpretation in mediation analysis. For instance, if X represents random assignment to control and treatment conditions, the effect of X on M and the effect of X on Y have a causal interpretation under certain reasonable assumptions. However, the randomization of X does not allow for a causal interpretation of the M to Y effect unless certain confounding assumptions are satisfied. The aim of this project was to develop a significance test and an effect size comparison for two sensitivity to confounding analyses methods: Left Out Variables Error (L.O.V.E.) and the correlated residuals method. Further, the project assessed the accuracy of the methods for identifying confounding bias by simulating data with and without confounding bias.
ContributorsAlvarez Bartolo, Diana (Author) / Mackinnon, David P. (Thesis advisor) / Grimm, Kevin J. (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
Description
Scale scores play a significant role in research and practice in a wide range of areas such as education, psychology, and health sciences. Although the methods of scale scoring have advanced considerably over the last 100 years, researchers and practitioners have generally been slow to implement these advances. There are many topics that fall under this umbrella but the current study focuses on two. The first topic is that of subscores and total scores. Many of the scales in psychological and health research are designed to yield subscores, yet it is common to see total scores reported instead. Simplifying scores in this way, however, may have important implications for researchers and scale users in terms of interpretation and use. The second topic is subscore augmentation. That is, if there are subscores, how much value is there in using a subscore augmentation method? Most people using psychological assessments are unfamiliar with score augmentation techniques and the potential benefits they may have over the traditional sum score approach. The current study borrows methods from education to explore the magnitude of improvement of using augmented scores over observed scores. Data was simulated using the Graded Response Model. Factors controlled in the simulation were number of subscales, number of items per subscale, level of correlation between subscales, and sample size. Four estimates of the true subscore were considered (raw, subscore-adjusted, total score-adjusted, joint score-adjusted). Results from the simulation suggest that the score adjusted with total score information may perform poorly when the level of inter-subscore correlation is 0.3. Joint scores perform well most of the time, and the subscore-adjusted scores and joint-adjusted scores were always better performers than raw scores. Finally, general advice to applied users is provided.
ContributorsGardner, Molly (Author) / Edwards, Michael C (Thesis advisor) / McNeish, Daniel (Committee member) / Levy, Roy (Committee member) / Arizona State University (Publisher)
Created2022
Description
Negative Urgency and Positive Urgency are important subfacets of a propensity to rash action. There is currently limited research on parental antecedents of Negative Urgency and Positive Urgency. The current study investigated whether parent personality and parenting behaviors predict adolescent Negative Urgency and Positive Urgency. Data were taken from a community sample with parent personality, positive parenting behaviors, and child Negative Urgency and Positive Urgency measured at separate timepoints. Structural equation models were used to examine whether parent personality predicted adolescent Negative Urgency and Positive Urgency and whether positive parenting mediated this relationship. There was no evidence for a relationship between parent personality and children’s Negative Urgency and Positive Urgency. In addition, there was no relationship between parenting behaviors and child Negative and Positive Urgency in cross-reporter models, but child-reported parenting predicted later adolescent-reported Negative and Positive Urgency. Greater positive parenting, as perceived by children, was related to less Negative and Positive Urgency when they were adolescents. More research is needed to understand whether the current results are due to reporter bias or whether child-perceived parenting behaviors influence the development of adolescent Negative and Positive Urgency.
ContributorsBui, Leena (Author) / Chassin, Laurie (Thesis advisor) / Corbin, William (Committee member) / Lemery-Chalfant, Kathryn (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
Description
Latent profile analysis (LPA), a type of finite mixture model, has grown in popularity due to its ability to detect latent classes or unobserved subgroups within a sample. Though numerous methods exist to determine the correct number of classes, past research has repeatedly demonstrated that no one method is consistently the best as each tends to struggle under specific conditions. Recently, the likelihood incremental percentage per parameter (LI3P), a method using a new approach, was proposed and tested which yielded promising initial results. To evaluate this new method more thoroughly, this study simulated 50,000 datasets, manipulating factors such as sample size, class distance, number of items, and number of classes. After evaluating the performance of the LI3P on simulated data, the LI3P is applied to LPA models fit to an empirical dataset to illustrate the method’s application. Results indicate the LI3P performs in line with standard class enumeration techniques, and primarily reflects class separation and the number of classes.
ContributorsHoupt, Russell Paul (Author) / Grimm, Kevin J (Thesis advisor) / McNeish, Daniel (Committee member) / Edwards, Michael C (Committee member) / Arizona State University (Publisher)
Created2022
Description
The current dissertation focused on the risks and rewards of the digital context in adolescent romantic relationships. Adolescent romantic relationships are a pivotal developmental milestone and a foundation for future relationship functioning. Thus, it is vital to understand how adolescents function within their romantic relationships to identify potential intervention points that can improve adolescents’ relationship skills. Adolescents frequently utilize technology within their relationships, with positive and negative implications. Thus, the digital context is an important area of research for adolescent romantic relationship functioning. The neo-ecological theory and the transformation framework help contextualize the digital context's impact on adolescent romantic relationships. The first study utilized two experiments to test the effects of an adolescent’s romantic partner hypothetically ”liking” a digital relationship threat’s Instagram post on their feelings of jealousy and digital dating abuse behaviors. Adolescents reported greater feelings of jealousy and engagement in digital dating abuse behaviors when their romantic partner “liked” a post from a different-gendered individual, and effects were exacerbated when that individual was high on attractiveness. While the digital context may serve as a risk context for adolescent relationships, the risk conferred may depend on the couple's functioning. Thus, the second study examined how sexting among adolescent couples was associated with their daily affect. Results demonstrate that while sexting may boost an adolescent’s affect on the same day, it is related to worse affect as the days pass. Lastly, the digital context can also be an external stressor that impacts the relationship. Thus, the third study examined how daily digital stress exposure during the COVID-19 pandemic is associated with late adolescent romantic couples’ substance use and mental health. This study examined actor and partner effects to assess the dyadic nature of stress contagion between romantic partners. This dissertation advances the current literature on associations between the digital context, adolescent development, and adolescent romantic relationship functioning.
ContributorsQuiroz, Selena (Author) / Ha, Thao (Thesis advisor) / Corbin, William R (Committee member) / McNeish, Daniel (Committee member) / Iida, Masumi (Committee member) / Arizona State University (Publisher)
Created2024