Beyond Moderation: Exploring Person-Level Mediation with Residuals and Individual Model Fit

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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

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.
Date Created
2022
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Evaluating Person-Oriented Methods for Mediation

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Description
Statistical inference from mediation analysis applies to populations, however, researchers and clinicians may be interested in making inference to individual clients or small, localized groups of people. Person-oriented approaches focus on the differences between people, or latent groups of people,

Statistical inference from mediation analysis applies to populations, however, researchers and clinicians may be interested in making inference to individual clients or small, localized groups of people. Person-oriented approaches focus on the differences between people, or latent groups of people, to ask how individuals differ across variables, and can help researchers avoid ecological fallacies when making inferences about individuals. Traditional variable-oriented mediation assumes the population undergoes a homogenous reaction to the mediating process. However, mediation is also described as an intra-individual process where each person passes from a predictor, through a mediator, to an outcome (Collins, Graham, & Flaherty, 1998). Configural frequency mediation is a person-oriented analysis of contingency tables that has not been well-studied or implemented since its introduction in the literature (von Eye, Mair, & Mun, 2010; von Eye, Mun, & Mair, 2009). The purpose of this study is to describe CFM and investigate its statistical properties while comparing it to traditional and casual inference mediation methods. The results of this study show that joint significance mediation tests results in better Type I error rates but limit the person-oriented interpretations of CFM. Although the estimator for logistic regression and causal mediation are different, they both perform well in terms of Type I error and power, although the causal estimator had higher bias than expected, which is discussed in the limitations section.
Date Created
2019
Agent

Friending Your Future: "" An Ecological Approach to Increasing Future Self-Continuity

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Description
The benefits of earning a college degree are clear, yet nearly half of first-time, full-time college students do not complete their degree within 6 years. Completing college is no simple task and students must regularly make decisions not to prefer

The benefits of earning a college degree are clear, yet nearly half of first-time, full-time college students do not complete their degree within 6 years. Completing college is no simple task and students must regularly make decisions not to prefer the smaller, immediate rewards over the larger, future reward of graduation (i.e. temporal discounting). Recent research shows initial support that temporal discounting can be reduced by heightening future self-continuity. This thesis study pilot tested an ecological, scalable approach to increase future-self continuity by heightening three components, similarity, vividness and positivity, within the framework of social media. Participants completed measures of these components before and after simulating the creation of a social media profile for themselves 10 years after college graduation. A significant increase in perceived similarity to the future self from Time 1 to Time 2 was detected in a within-subjects test. The findings in this study are encouraging and may inform the development of interventions aimed at increasing future self-continuity in college students.
Date Created
2016-05
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