Matching Items (15)

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Civil Court Mediation in the 21st Century

Description

Tempe, and the greater justice system, consistently seeks to re-evaluate its operations and processes to meet the ever-increasing conflicts that are brought into the courts purview. Nationally, municipal courts

Tempe, and the greater justice system, consistently seeks to re-evaluate its operations and processes to meet the ever-increasing conflicts that are brought into the courts purview. Nationally, municipal courts have seen a decrease in civil matters, however, this is not the case in Tempe. My goal for this project was to assess and reflect on the circumstances that surround civil matters within the municipal court. As a case study, I observed and evaluated several civil court cases. In doing so, I analyzed the ways in which legal consciousness and discourse are used to solve existing civil court matters. I then took these data and considered the ways in which mediation could be used as a justice alternative. In proposing mediation as an alternative, I focus on the ways in which mediation better serves to build positive legal consciousness and address all forms of discourse that can be presented in specific civil cases. Finally, I discuss a strategy that can be used within the Tempe Courts to implement mediation as a long-term problem-solving court strategy.

Contributors

Agent

Created

Date Created
  • 2019-05

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Estimating causal direct and indirect effects in the presence of post-treatment confounders: a simulation study

Description

In investigating mediating processes, researchers usually use randomized experiments and linear regression or structural equation modeling to determine if the treatment affects the hypothesized mediator and if the mediator affects

In investigating mediating processes, researchers usually use randomized experiments and linear regression or structural equation modeling to determine if the treatment affects the hypothesized mediator and if the mediator affects the targeted outcome. However, randomizing the treatment will not yield accurate causal path estimates unless certain assumptions are satisfied. Since randomization of the mediator may not be plausible for most studies (i.e., the mediator status is not randomly assigned, but self-selected by participants), both the direct and indirect effects may be biased by confounding variables. The purpose of this dissertation is (1) to investigate the extent to which traditional mediation methods are affected by confounding variables and (2) to assess the statistical performance of several modern methods to address confounding variable effects in mediation analysis. This dissertation first reviewed the theoretical foundations of causal inference in statistical mediation analysis, modern statistical analysis for causal inference, and then described different methods to estimate causal direct and indirect effects in the presence of two post-treatment confounders. A large simulation study was designed to evaluate the extent to which ordinary regression and modern causal inference methods are able to obtain correct estimates of the direct and indirect effects when confounding variables that are present in the population are not included in the analysis. Five methods were compared in terms of bias, relative bias, mean square error, statistical power, Type I error rates, and confidence interval coverage to test how robust the methods are to the violation of the no unmeasured confounders assumption and confounder effect sizes. The methods explored were linear regression with adjustment, inverse propensity weighting, inverse propensity weighting with truncated weights, sequential g-estimation, and a doubly robust sequential g-estimation. Results showed that in estimating the direct and indirect effects, in general, sequential g-estimation performed the best in terms of bias, Type I error rates, power, and coverage across different confounder effect, direct effect, and sample sizes when all confounders were included in the estimation. When one of the two confounders were omitted from the estimation process, in general, none of the methods had acceptable relative bias in the simulation study. Omitting one of the confounders from estimation corresponded to the common case in mediation studies where no measure of a confounder is available but a confounder may affect the analysis. Failing to measure potential post-treatment confounder variables in a mediation model leads to biased estimates regardless of the analysis method used and emphasizes the importance of sensitivity analysis for causal mediation analysis.

Contributors

Agent

Created

Date Created
  • 2013

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Identifying mediators of youth anxiety and depression intervention outcomes: a meta-analytic path analysis

Description

Anxiety and depression are among the most prevalent disorders in youth, with prevalence rates ranging from 15% to 25% for anxiety and 5% to 14% for depression. Anxiety and depressive

Anxiety and depression are among the most prevalent disorders in youth, with prevalence rates ranging from 15% to 25% for anxiety and 5% to 14% for depression. Anxiety and depressive disorders cause significant impairment, fail to spontaneously remit, and have been prospectively linked to problematic substance use and legal problems in adulthood. These disorders often share a high-degree of comorbidity in both clinical and community samples, with anxiety disorders typically preceding the onset of depression. Given the nature and consequences of anxiety and depressive disorders, a plethora of treatment and preventative interventions have been developed and tested with data showing significant pre to post to follow-up reductions in anxiety and depressive symptoms. However, little is known about the mediators by which these interventions achieve their effects. To address this gap in the literature, the present thesis study combined meta-analytic methods and path analysis to evaluate the effects of youth anxiety and depression interventions on outcomes and four theory-driven mediators using data from 55 randomized controlled trials (N = 11,413). The mediators included: (1) information-processing biases, (2) coping strategies, (3) social competence, and (4) physiological hyperarousal. Meta-analytic results showed that treatment and preventative interventions reliably produced moderate effect sizes on outcomes and three of the four mediators (information-processing biases, coping strategies, social competence). Most importantly, findings from the path analysis showed that changes in information-processing biases and coping strategies consistently mediated changes in outcomes for anxiety and depression at both levels of intervention, whereas gains in social competence and reductions in physiological hyperarousal did not emerge as significant mediators. Knowledge of the mediators underlying intervention effects is important because they can refine testable models of treatment and prevention efforts and identify which anxiety and depression components need to be packaged or strengthened to maximize intervention effects. Allocating additional resources to significant mediators has the potential to reduce costs associated with adopting and implementing evidence-based interventions and improve dissemination and sustainability in real-world settings, thus setting the stage to be more readily integrated into clinical and non-clinical settings on a large scale.

Contributors

Agent

Created

Date Created
  • 2015

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Obtaining accurate estimates of the mediated effect with and without prior information

Description

Research methods based on the frequentist philosophy use prior information in a priori power calculations and when determining the necessary sample size for the detection of an effect, but not

Research methods based on the frequentist philosophy use prior information in a priori power calculations and when determining the necessary sample size for the detection of an effect, but not in statistical analyses. Bayesian methods incorporate prior knowledge into the statistical analysis in the form of a prior distribution. When prior information about a relationship is available, the estimates obtained could differ drastically depending on the choice of Bayesian or frequentist method. Study 1 in this project compared the performance of five methods for obtaining interval estimates of the mediated effect in terms of coverage, Type I error rate, empirical power, interval imbalance, and interval width at N = 20, 40, 60, 100 and 500. In Study 1, Bayesian methods with informative prior distributions performed almost identically to Bayesian methods with diffuse prior distributions, and had more power than normal theory confidence limits, lower Type I error rates than the percentile bootstrap, and coverage, interval width, and imbalance comparable to normal theory, percentile bootstrap, and the bias-corrected bootstrap confidence limits. Study 2 evaluated if a Bayesian method with true parameter values as prior information outperforms the other methods. The findings indicate that with true values of parameters as the prior information, Bayesian credibility intervals with informative prior distributions have more power, less imbalance, and narrower intervals than Bayesian credibility intervals with diffuse prior distributions, normal theory, percentile bootstrap, and bias-corrected bootstrap confidence limits. Study 3 examined how much power increases when increasing the precision of the prior distribution by a factor of ten for either the action or the conceptual path in mediation analysis. Power generally increases with increases in precision but there are many sample size and parameter value combinations where precision increases by a factor of 10 do not lead to substantial increases in power.

Contributors

Agent

Created

Date Created
  • 2014

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Case study: the closing of the Arizona interfaith alliance for worker justice and implications on barriers to civic engagement in its wake

Description

The Arizona Interfaith Alliance for Worker Justice (AIAWJ) was a mediating structure for those who wanted to be civically engaged in the labor movement and other coalitions in Phoenix, Arizona.

The Arizona Interfaith Alliance for Worker Justice (AIAWJ) was a mediating structure for those who wanted to be civically engaged in the labor movement and other coalitions in Phoenix, Arizona. It not only served its constituents, but it integrated, educated, and empowered them. Due to lack of funding the AIAWJ closed in the summer of 2016. Many community members from marginalized neighborhoods, other concerned citizens, students, myself, and others participated in their first and only civic engagement opportunities through this organization and were subsequently left with no connections, a barrier to being civically engaged. Through interviews and secondary data research, the relationship between people, mediating structures, and civic engagement activity are examined. The key findings support existing research that emphasizes the importance of mediating structures when it comes to civic engagement.

Contributors

Agent

Created

Date Created
  • 2016

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Cultural socialization, interdependent self-construal, and ethnic identity in Latinx and Asian American emerging adults: a mediation analysis

Description

Research on cultural socialization, the process in which individuals learn messages regarding the traditions and values of their culture (Hughes et al., 2006), has dedicated little attention to Latinx and

Research on cultural socialization, the process in which individuals learn messages regarding the traditions and values of their culture (Hughes et al., 2006), has dedicated little attention to Latinx and Asian American groups. This study examined whether an interdependent self-construal (i.e., viewing oneself as connected to others and endorsing behaviors that depend on others; Singelis, 1994) was a mediator between cultural socialization and ethnic identity for these two groups. The current study utilized mediation analyses to explore the associations between cultural socialization via different agents (i.e., parents, teachers, romantic partners, peers), interdependent self-construal, and ethnic identity exploration and commitment for Latinx (N = 258, 68.6% female, Mage = 20.54) and Asian (N = 281, 66.5% female, Mage = 20.34) American college-attending emerging adults. Results revealed that for the Latinx sample, interdependent self-construal mediated the relation between cultural socialization and ethnic identity exploration or commitment in regards to parents and peers, but not teachers. In addition, interdependent self-construal mediated the association between cultural socialization from romantic partners and ethnic identity commitment, but not exploration. For the Asian American sample, interdependent self-construal mediated the association between cultural socialization and ethnic identity exploration or commitment in regards to romantic partners and peers, but not parents and teachers. These results highlight the important role of different cultural socialization agents in ethnic identity formation for these two groups and suggest that the endorsement of cultural values can be a mechanism through which ethnic identity is strengthened.

Contributors

Agent

Created

Date Created
  • 2017

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Evaluating Person-Oriented Methods for Mediation

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

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.

Contributors

Agent

Created

Date Created
  • 2019

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Procedural justice and legal socialization among serious adolescent offenders: a longitudinal examination

Description

Research on Tyler’s process-based model has found strong empirical support. The premise of this model is that legitimacy and legal cynicism mediate the relationship between procedural justice and compliance behaviors.

Research on Tyler’s process-based model has found strong empirical support. The premise of this model is that legitimacy and legal cynicism mediate the relationship between procedural justice and compliance behaviors. Procedural justice and legitimacy in particular have been linked to compliance and cooperation and a small, but growing body of literature has examined how these factors relate to criminal offending. There remains a number of unanswered questions surrounding the developmental processes and underlying mechanisms of procedural justice and legal socialization. The purpose of this study is twofold. First, this study will build upon recent trends in the literature to examine what factors influence changes in perceptions of procedural justice and legal socialization attitudes over time. In order to do so, the effects of a number of time-stable and time-varying covariates will be assessed. Second, this study will evaluate the effects of four possible mediating measures—legitimacy, legal cynicism, anger, and prosocial motivation—underlying the relationship between procedural justice and criminal offending. This section of the study will use a multilevel mediation method to assess whether mediation occurs between or within the individual.

Data from the Pathways to Desistance Study—a longitudinal study of 1,354 adolescents adjudicated of a serious offense followed-up for seven years—are used to address this research agenda. Results from this study offer three general conclusions. First, results show that perceptions of procedural justice are malleable, that is, they can change over time and are influenced by a number of factors. Legal socialization beliefs, however, demonstrate only marginal change over time, suggesting these beliefs to be more stable. Second, analyses indicate differing pathways and effects for direct and vicarious experiences of procedural justice. Finally, the multilevel mediation analyses reveal that within-individual changes in direct experiences of procedural justice remains a robust predictor of offending, regardless of the presence of mediating variables. Legitimacy was found to have the strongest mediation effect on between-individual differences in direct procedural justice, whereas anger partially mediated the effects of between-individual differences in vicarious procedural justice. This study concludes with a discussion of policy implications and avenues for future research.

Contributors

Agent

Created

Date Created
  • 2016

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Comparison of methods for estimating longitudinal indirect effects

Description

Mediation analysis is used to investigate how an independent variable, X, is related to an outcome variable, Y, through a mediator variable, M (MacKinnon, 2008). If X represents a randomized

Mediation analysis is used to investigate how an independent variable, X, is related to an outcome variable, Y, through a mediator variable, M (MacKinnon, 2008). If X represents a randomized intervention it is difficult to make a cause and effect inference regarding indirect effects without making no unmeasured confounding assumptions using the potential outcomes framework (Holland, 1988; MacKinnon, 2008; Robins & Greenland, 1992; VanderWeele, 2015), using longitudinal data to determine the temporal order of M and Y (MacKinnon, 2008), or both. The goals of this dissertation were to (1) define all indirect and direct effects in a three-wave longitudinal mediation model using the causal mediation formula (Pearl, 2012), (2) analytically compare traditional estimators (ANCOVA, difference score, and residualized change score) to the potential outcomes-defined indirect effects, and (3) use a Monte Carlo simulation to compare the performance of regression and potential outcomes-based methods for estimating longitudinal indirect effects and apply the methods to an empirical dataset. The results of the causal mediation formula revealed the potential outcomes definitions of indirect effects are equivalent to the product of coefficient estimators in a three-wave longitudinal mediation model with linear and additive relations. It was demonstrated with analytical comparisons that the ANCOVA, difference score, and residualized change score models’ estimates of two time-specific indirect effects differ as a function of the respective mediator-outcome relations at each time point. The traditional model that performed the best in terms of the evaluation criteria in the Monte Carlo study was the ANCOVA model and the potential outcomes model that performed the best in terms of the evaluation criteria was sequential G-estimation. Implications and future directions are discussed.

Contributors

Agent

Created

Date Created
  • 2018

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Connecting pain intensity to work goal and lifestyle goal progress: examining mediation and moderation using multi-level modeling

Description

The present study examined the association of pain intensity and goal progress in a community sample of 132 adults with chronic pain who participated in a 21 day diary study.

The present study examined the association of pain intensity and goal progress in a community sample of 132 adults with chronic pain who participated in a 21 day diary study. Multilevel modeling was employed to investigate the effect of morning pain intensity on evening goal progress as mediated by pain's interference with afternoon goal pursuit. Moderation effects of pain acceptance and pain catastrophizing on the associations between pain and interference with both work and lifestyle goal pursuit were also tested. The results showed that the relationship between morning pain and pain's interference with work goal pursuit in the afternoon was significantly moderated by a pain acceptance. In addition, it was found that the mediated effect differed across levels of pain acceptance; that is: (1) there was a significant mediation effect when pain acceptance was at its mean and one standard deviation below the mean; but (2) there was no mediation effect when pain acceptance was one standard deviation above the mean. It appears that high pain acceptance significantly attenuates the power of nociception in disrupting one's work goal pursuit. However, in the lifestyle goal model, none of the moderators were significant nor was there a significant association between pain interference with goal pursuit and goal progress. Only morning pain intensity significantly predicted afternoon interference with lifestyle goal pursuit. Further interpretation of the present findings and potential explanations of those inconsistencies are elaborated on discussion. Limitations and the clinical implication of the current study were considered, along with suggestions for future studies.

Contributors

Agent

Created

Date Created
  • 2014