Thesis advisor: Sara M. Moorman / There is much prior research on the benefits of marriage for adults, including for mental and physical health (Carr and Springer 2010). Further research has demonstrated that the quality of one’s marriage provides benefits, and not merely the status itself (see Carr and Springer 2010; Proulx, Helms, and Buehler 2007). A close, salient relationship such as marriage is not experienced in isolation, but is rather an interpersonal system, where the characteristics, feelings, and opinions of each partner can influence the other (Berscheid and Ammazzalorso 2001; Carr et al. 2014; Moorman 2016). However, less research has been performed that takes advantage of dyadic data to determine whether and how a partner’s marital quality may affect one’s own well-being (Carr et al. 2014; Kenny 1996). Moreover, emotional experiences rarely remain truly private; individuals unconsciously signal and express their feelings to others, and can even transmit these emotional experiences to close social partners (Christakis and Fowler 2013; Hatfield, Cacioppo, and Rapson 1994). The present dissertation examines the associations among older husbands’ and wives’ marital quality and well-being, using two sources of dyadic data, a range of measures of marital quality and well-being, and advanced analytic strategies appropriate for longitudinal and cross-sectional data. Older couples can differ from their younger and midlife counterparts, as both men and women trim their broader social networks in later life and increasingly focus on their closest and most rewarding relationships, such as marriage (Carstensen, Isaacowitz, and Charles 1999; Mancini and Bonanno 2006). Gendered roles may shift in later life, as well, as older adults cease activities such as child-rearing and full-time employment (Bookwala 2012). Thus, potential differences according to gender are also explicitly tested. The results of this dissertation will shed greater light on how older couples’ perceptions of marital quality influence various aspects of spouses’ well-being, cross-sectionally and over time. Mutual Influence and Older Married Adults’ Anxiety Symptoms: Results from The Irish Longitudinal Study on Ageing analyzes cross-sectional dyadic data from 1,114 married older couples surveyed in the initial wave of The Irish Longitudinal Study on Ageing (TILDA; Kenny 2014), 2009-2011. Dyadic structural equation models (SEM) examined the direct and indirect associations between husbands’ and wives’ reports of marital strain and generalized anxiety symptoms in later life. Findings revealed that perceptions of marital strain were related with husbands’ and wives’ own generalized anxiety symptoms. Further, husbands’ anxiety symptoms were significantly related with wives’ anxiety symptoms, and vice versa, illustrating bi-directional feedback. Lastly, husbands’ and wives’ perceptions of marital strain were significantly indirectly related with their partners’ anxiety symptoms, with these associations being mediated by spouses’ own anxiety symptoms. These results suggest that emotional contagion may be the pathway for partner effects of marital strain on spouses’ well-being. Findings also suggest that efforts to reduce anxiety symptoms may be most effective when taking marital context and quality into account. Two-Wave Dyadic Analysis of Marital Quality and Loneliness in Later Life: Results From The Irish Longitudinal Study on Ageing analyzes dyadic reports of marital quality and loneliness over a two-year period, using longitudinal dyadic data collected from 932 older married couples who participated in both of the first two waves of The Irish Longitudinal Study on Ageing (TILDA), collected from 2009-2013. Two-wave lagged dependent variable (LDV) models tested the cognitive perspective on loneliness, emotional contagion theory, and actor-partner interdependence by examining whether husbands’ and wives’ reports of marital quality and loneliness at baseline predicted both spouses’ loneliness two years later. Results indicated that one’s own perceptions of negative marital quality at baseline were related with greater loneliness after two years, supporting the cognitive perspective on loneliness. Further, both spouses’ reports of loneliness at baseline were related with loneliness two years later, supporting emotional contagion theory. Partners’ reports of marital quality were not related with future loneliness, failing to support actor-partner interdependence. Do “His” and “Her” Marriage Influence One Another? Older Spouses’ Marital Quality Over Four Years uses two-wave longitudinal data from the Disability and Use of Time (DUST) supplement to the Panel Study of Income Dynamics (PSID) to examine associations between husbands’ and wives’ reports of marital quality over a four-year period. The sample consisted of 209 older married couples who participated in both the 2009 and 2013 waves of DUST. Lagged dependent variable (LDV) models tested whether older husbands’ and wives’ perceptions of marital quality are themselves subject to emotional contagion, by examining whether baseline reports of marital quality were related with one’s own and a partner’s marital quality after four years. Results indicated that (a) husbands reported better marital quality than their wives in both 2009 and 2013, (b) for both husbands and wives, baseline marital quality was significantly related with both one’s own and one’s partner’s marital quality four years later, and (c) there were no differences in effects according to gender. These findings offer support for the framework of “his” and “her” marriage, as well as emotional contagion theory. Together, these papers examine whether and how older spouses’ reports of marital quality and well-being are associated with one another, with a particular emphasis on assessing emotional contagion as a potential explanation and mechanism for dyadic partner effects. The results of these articles contribute empirically and theoretically to the literature(s) on marital quality and well-being; spousal interdependence; and emotional contagion. I discuss the implications of these articles for theory and future research concerning marriage and well-being in later life.

Dyadic data analysis methods are underutilized in child and youth care, where much of the practice relies on relationships with individuals and groups. In this exploratory study, a dyadic data analysis approach was used to study the interdependence amongst client-counsellor dyads in a voluntary counselling setting. Ten counsellors and thirty-six clients from a Canadian voluntary counselling agency participated in this study. Counselling sessions ranged from two to 20 sessions. Clients completed a session rating scale, a measure of the therapeutic alliance. In addition, clients and counsellors completed an outcome rating scale and personal change questions. A one-with-many design was used to explore the similarity between client-counsellor dyads, the degree of consensus, assimilation, and uniqueness as well as the level of reciprocity for perceived client well-being. Multi-level modeling was used to partition the variance on the outcome rating scale to account for sources of non-independence in client-counsellor dyads, and the indirect relationships between multiple clients working with the same counsellor. Implications of the study and recommendations for future research are discussed. / Graduate

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While a single learned model is adequate for simple prediction problems, it may not be sufficient to represent heterogeneous populations that difficult classification or regression problems often involve. In such scenarios, practitioners often adopt a "divide and conquer" strategy that segments the data into relatively homogeneous groups and then builds a model for each group. This two-step procedure usually results in simpler, more interpretable and actionable models without any loss in accuracy. We consider prediction problems on bi-modal or dyadic data with covariates, e.g., predicting customer behavior across products, where the independent variables can be naturally partitioned along the modes. A pivoting operation can now result in the target variable showing up as entries in a "customer by product" data matrix. We present a model-based co-clustering framework that interleaves partitioning (clustering) along each mode and construction of prediction models to iteratively improve both cluster assignment and fit of the models. This Simultaneous CO-clustering And Learning (SCOAL) framework generalizes co-clustering and collaborative filtering to model-based co-clustering, and is shown to be better than independently clustering the data first and then building models. Our framework applies to a wide range of bi-modal and multi-modal data, and can be easily specialized to address classification and regression problems in domains like recommender systems, fraud detection and marketing. Further, we note that in several datasets not all the data is useful for the learning problem and ignoring outliers and non-informative values may lead to better models. We explore extensions of SCOAL to automatically identify and discard irrelevant data points and features while modeling, in order to improve prediction accuracy. Next, we leverage the multiple models provided by the SCOAL technique to address two prediction problems on dyadic data, (i) ranking predictions based on their reliability, and (ii) active learning. We also extend SCOAL to predictive modeling of multi-modal data, where one of the modes is implicitly ordered, e.g., time series data. Finally, we illustrate our implementation of a parallel version of SCOAL based on the Google Map-Reduce framework and developed on the open source Hadoop platform. We demonstrate the effectiveness of specific instances of the SCOAL framework on prediction problems through experimentation on real and synthetic data. / text

With the propagation of individuals' presence in various online environments from social networks (e.g., Facebook, Twitter) and dating websites (e.g., Match.com, eHarmony.com) to personal blogs (e.g., WordPress.com) and employment websites (e.g., linkedIn.com), the need to understand online social dynamics has grown. In many cases, people are experiencing introductions online rather than in-person. In the absence of non-verbal information, one potentially important source of information available in virtual environments and communication is in the way people use language. With the development of computerized word count tools, it has become increasingly feasible to analyze large samples of text-based stimuli (e.g., Ireland, et al., 2011; Mehl, Gosling, & Pennebaker, 2006; Pennebaker, Mehl, & Niederhoffer, 2003; Tausczik & Pennebaker, 2010). These analyses have been able to reliably reveal a number of traits (e.g., Big Five, gender) and states (e.g., depression) about the authors of the texts. In a study of approximately 500 dyads, participants were asked to spend 10 minutes in an online chat room getting to know an individual for whom they were unacquainted. Participants then rated one another on a number of personality and individual difference traits. Analyses focused on sample-level, pair-level, and trait-level self-other agreement within the sample. Additionally, linguistic mediators of the self-other agreement were investigated. A Brunswick Lens Model was employed in order to interpret the relationship between linguistic cues and overall judgmental accuracy. Results revealed that self-other agreement in the online chat environment was achieved slightly above chance. Traits that were perceived accurately included Extraversion, Political Liberalism, and Tradition. Results also revealed that there were a number of valid linguistic markers to predicting accurate personality judgment. These cues, however, were rarely utilized to achieve accuracy. Also, counter to hypotheses, linguistic style matching (or the degree to which individuals were mimicking each other linguistically) was not predictive of self-other agreement. It was, however, significantly related to interaction quality. Taken together, the findings revealed that computer-mediated environments are a valid context for forming impressions. However, valid cues are either not available or not detected by perceivers. Theoretical and practical implications are discussed as well as areas for future research. / text

abstract: Intercultural couples -partners from two different countries- may face increased levels of stress within their relationship (internal stress). Internal stress can negatively impact relationship satisfaction, whereas developing healthy ways to cope (dyadic coping; DC) can lower stress levels and improve relationship satisfaction (e.g., Bodenmann, 2005). Specifically, it may be important for partners to perceive that their partner as supporting them during times of stress through engaging in DC. This study examined whether intercultural couples experience internal stress and what effects, if any, perceived partner engagement in DC had on their reported relationship satisfaction. Cross-sectional data was gathered from 85 couples and was analyzed using Actor-Partner Interdependence Models (APIMs; Kenny & Cook, 1999). Separate APIMs were conducted to examine the association between the independent variables (perceived partner engagement in: positive DC, negative DC, delegated DC, and supportive DC) and the outcome variables of internal stress and relationship satisfaction, while controlling for years each partner lived in their country of birth, average and differences on identification with individualism-collectivism values and behaviors, and if partners did or did not identify as the same race and/or ethnicity. Additionally, APIMs of internal stress on relationship as moderated by perceived partner positive and negative DC were conducted. Results showed significant associations of all independent variables on internal stress and relationship satisfaction. There were no signification interactions between internal stress and DC on relationship satisfaction. Implications for relationship researchers and mental health professionals working with intercultural couples are discussed. / Dissertation/Thesis / Masters Thesis Counseling 2016

abstract: With the establishment of the emerging adult developmental period and the rise of helicopter parents, attachment theory provides foundation for conceptualizing the continued involvement of helicopter parents in their emerging adults’ emotion regulation processes. This study utilized dyadic data from 66 emerging adult children and their helicopter parents to examine the association of helicopter parent-emerging adult communication in mitigating the associations between experiences of affect and stress. Specifically, the purpose of the present study was to use dyadic data to examine how communication within the helicopter parent-emerging adult relationship associates with emerging adults’ ability to regulate experiences of negative and positive affect. Both associations within the emerging adult and helicopter parent individually (actor effects) and how helicopter parents impact construct associations for emerging adults’ (partner effects) were considered. Two multilevel mediation models using Actor-Partner Interdependence Models were conducted to assess the relations between affect, stress, and helicopter parent-emerging adult communication quality for negative and positive affect separately. The positive direct effect between negative affect and stress was statistically significant for emerging adults, but not for helicopter parents, suggesting that, for emerging adults, higher perceptions of negative affect were associated with higher levels of stress. The direct and indirect effects for the mediation model examining actor and partner effects between negative affect, communication quality, and stress were non-significant for both emerging adults and helicopter parents. The direct effect between positive affect and stress was statistically significant for helicopter parents but not for emerging adults; however, the directionality of the significant association was positive and not as hypothesized. Finally, the direct and indirect effects for the mediation model examining actor and partner effects between positive affect, communication quality, and stress were non-significant for emerging adults and helicopter parents. Considerations for future studies examining aspects of attachment within emotion regulation for the helicopter parent-emerging adult relationship and the importance of considering relationship characteristics, such the relational characteristics of social support and conflict, are discussed. / Dissertation/Thesis / Doctoral Dissertation Counseling Psychology 2017

abstract: Guided by Alberts, Tracy and Trethewey's (2011) integrated theory of the division of domestic labor, this dissertation examined the influence of domestic labor response threshold (i.e., the point at which one is sufficiently disturbed by a task undone so as to feel compelled to attend to it) on domestic labor performance and domestic labor conflict. Three-hundred-ten heterosexual participants (155 marital dyads; average marriage length of 20 years) completed an online questionnaire about their performance of household labor, household labor conflict, and response thresholds. Response thresholds were assessed using traditional verbal measures as well as two visual (i.e., photographic) measures developed for this investigation. The data were analyzed using three methods of dyadic data analysis: structural equation modeling, repeated measures multivariate analysis of variance (MANOVA), and actor-partner interdependence models using multilevel modeling. Results indicate that the lower one's response threshold, and the higher one's partner's response threshold, the greater one's contributions to household tasks. Additionally, the lower one's response threshold, and the higher one's partner's response thresholds, the more likely the demand-withdrawal pattern is to emerge in domestic labor conflicts. Finally, mutual avoidance is more likely when one partner perceives that it is less costly to complete domestic work than to engage in conflict about it, or when one partner perceives that domestic labor is not a worthwhile or appropriate conflict topic. Contributions of this investigation include support for the integrated theory of the division of domestic labor, increased understanding of how individual differences (working in concert with actor sex) contribute to domestic labor allocation and conflict, a more sensitive measure of response threshold, and preliminary evidence of the "logics" of avoidance of domestic labor conflict. / Dissertation/Thesis / Ph.D. Communication 2012

abstract: This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive (ICAP) framework. The current work combined these two cognitive-based approaches to design collaborative learning activities that can serve as alternatives to existing methods, which carry limitations and challenges. The "preparing-to-interact" method avoids the need for training students in specific collaboration skills or guiding/scripting their dialogic behaviors, while providing the opportunity for students to acquire the necessary prior knowledge for maximizing their discussions towards learning. The study used a 2x2 experimental design, investigating the factors of Preparation (No Prep and Prep) and Type of Activity (Active and Constructive) on deep and shallow learning. The sample was community college students in introductory psychology classes; the domain tested was "memory," in particular, concepts related to the process of remembering/forgetting information. Results showed that Preparation was a significant factor affecting deep learning, while shallow learning was not affected differently by the interventions. Essentially, equalizing time-on-task and content across all conditions, time spent individually preparing by working on the task alone and then discussing the content with a partner produced deeper learning than engaging in the task jointly for the duration of the learning period. Type of Task was not a significant factor in learning outcomes, however, exploratory analyses showed evidence of Constructive-type behaviors leading to deeper learning of the content. Additionally, a novel method of multilevel analysis (MLA) was used to examine the data to account for the dependency between partners within dyads. This work showed that "preparing-to-interact" is a way to maximize the benefits of collaborative learning. When students are first cognitively prepared, they seem to make the most efficient use of discussion towards learning, engage more deeply in the content during learning, leading to deeper knowledge of the content. Additionally, in using MLA to account for subject nonindependency, this work introduces new questions about the validity of statistical analyses for dyadic data. / Dissertation/Thesis / Ph.D. Educational Psychology 2013