cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7274/25604634.v1
title: Identifying Groups with Different Dynamic Patterns Using Cluster Analysis

description: Clustering is an exploratory analysis technique to uncover subgroups within the population and it facilitates the development of subgroup-specific intervention or treatment. Although it is commonly used for cross-sectional data, several researchers have used it for multivariate time series with the goal of grouping together individuals with similar dynamic patterns (Aghabozorgi, Shirkhorshidi, & Wah, 2015).
The common raw data-based approach may fail to identify subgroups with distinctive dynamic factor structures that are often the focus of psychological research and not directly visible in the time series patterns. In the dissertation, I develop a model-based clustering method to identify subgroups characterized by their dynamic patterns of latent factors. In particular, it first fits a dynamic factor analysis model (Molenaar, 1985; Nesselroade, McArdle, Aggen, & Meyers, 2002; Browne & Zhang, 2007) to each individual's time series, and then calculates distances between parameter estimates of the fitted models and groups individuals based on the distances. 
I present an empirical illustration of four clustering methods. The methods are model-based clustering with K-means algorithm, model-based clustering with hierarchical algorithm, raw data-based clustering with K-means algorithm, and raw data-based clustering with hierarchical algorithm. I conduct the simulation study to compare the performances of the four methods with multivariate time series. 
The simulation results indicate that (1) the model-based approach had higher cluster recovery rates and adjusted Rand indices compared to the raw data-based approach. (2) Under the same clustering approach, the K-means clustering algorithm had slightly higher cluster recovery rates and adjusted rand indices compared to the hierarchical clustering algorithm in most conditions. (3) The cluster recovery rates of clustering validation indices vary depending on the number of population clusters. 
I address methodological and applied implications, limitations and future studies, and conclusions of the study.
DOI: 10.7274/26122483
title: Efficient Assessment of Multidimensional Processes in Intensive Longitudinal Designs Using Adaptive Ecological Momentary Assessment

description: Intensive longitudinal designs, such as ecological momentary assessment, rely on frequent and repetitive measurement to capture psychological processes in naturalistic settings over micro-longitudinal timescales (e.g., days or weeks). However, these designs can impose substantial response burden on respondents which impacts data quality and study compliance. This forces researchers to limit designs to few variables measured by ultra-brief static measures resulting in a burden-fidelity tradeoff. Such limitations often preclude effective assessment of complex multidimensional processes (e.g., suicidal thoughts). The present work proposed and evaluated multidimensional computerized adaptive testing (MCAT) methods as a means improve the burden-fidelity tradeoff in intensive longitudinal measurement. Two studies examined the performance and efficiency of multidimensional adaptive testing for high dimensional tests with realistic intensive longitudinal burden constraints. The first study focused on contrasting MCAT item selection rules across test dimensionality and test structure. The second study focuses on a subset of test dimensionalities across intensive longitudinal data structures. Multiple test initialization strategies are also examined. Results generally supported MCAT as a viable assessment method for intensive longitudinal data. Test dimensionality, item selection rules, and underlying change dynamics are critical, however. Future directions and practical considerations for adaptive measurement in intensive longitudinal designs are discussed.
DOI: 10.7274/26122483.v1
title: Efficient Assessment of Multidimensional Processes in Intensive Longitudinal Designs Using Adaptive Ecological Momentary Assessment

description: Intensive longitudinal designs, such as ecological momentary assessment, rely on frequent and repetitive measurement to capture psychological processes in naturalistic settings over micro-longitudinal timescales (e.g., days or weeks). However, these designs can impose substantial response burden on respondents which impacts data quality and study compliance. This forces researchers to limit designs to few variables measured by ultra-brief static measures resulting in a burden-fidelity tradeoff. Such limitations often preclude effective assessment of complex multidimensional processes (e.g., suicidal thoughts). The present work proposed and evaluated multidimensional computerized adaptive testing (MCAT) methods as a means improve the burden-fidelity tradeoff in intensive longitudinal measurement. Two studies examined the performance and efficiency of multidimensional adaptive testing for high dimensional tests with realistic intensive longitudinal burden constraints. The first study focused on contrasting MCAT item selection rules across test dimensionality and test structure. The second study focuses on a subset of test dimensionalities across intensive longitudinal data structures. Multiple test initialization strategies are also examined. Results generally supported MCAT as a viable assessment method for intensive longitudinal data. Test dimensionality, item selection rules, and underlying change dynamics are critical, however. Future directions and practical considerations for adaptive measurement in intensive longitudinal designs are discussed.
DOI: 10.7274/26170387
title: Change Processes in Ecological Momentary Assessment: Addressing Zero-Inflation in Count Data

description: Count or zero-inflated count data is often collected in Ecological Momentary Assessment (EMA) studies where understanding the mechanisms of the change process serves as the primary research goal. Traditional methods often fail to capture the complexities inherent in EMA data, leading to discrepancies between empirical findings and theoretical expectations. To address these limitations, this study presents two novel approaches. The first integrates autoregressive effects individually, and the second utilizes a model framework to pinpoint autoregressive effects among groups.
These approaches are extended for both count and zero-inflated count data. Through simulation studies and empirical applications, the proposed models show enhanced accuracy and interpretability at both individual and group levels. Furthermore, models tailored for zero-inflated data, referred to as ZIP-CAR, can distinguish zero patterns at both individual and group levels. The dissertation concludes with discussions on the practical implications, limitations, and future directions of the proposed methods. This work is expected to improve method development for EMA studies, ultimately enhancing the understanding of behavioral change processes in zero-inflated count data.
DOI: 10.7274/26211110
title: Sleep Disturbances and ADHD-Related Impairments among Adolescents

description: Attention Deficit Hyperactive Disorder (ADHD), a neurodevelopmental disorder characterized by age-inappropriate symptoms of inattention and/or hyperactivity/impulsivity, is one of the most prevalent childhood disorders with rates as high as 10.9% among children and adolescents within the U.S (Li et al., 2023). Despite behavioral therapies becoming more sophisticated overtime, many youth with ADHD continue to exhibit significant functional impairments such as underperformance in school and at work, conflict with family and peers, and lower self-concept. Considering that sleep disturbances are often comorbid with ADHD and often result in similar impairments, the concomitant sleep problems may explain some of the unexplained variance left over in the association between ADHD symptoms and impairments. However, additional basic research is needed to further understand the relation between these variables, especially during adolescence when sleep problems are prominent. This study hypothesized that adolescent sleep quality was associated with ADHD-related impairments while controlling for ADHD symptoms, ADHD medication usage, gender, and age. A community sample of 243 mother-adolescent dyads from across the U.S. were recruited via Facebook ads. Mothers and adolescents completed a series of parent- and 
self-report questionnaires assessing ADHD symptoms, ADHD-related impairments, and sleep quality. Utilizing structural equation modeling, multivariate models were used to examine if sleep quality was associated with ADHD-related impairments in the academic, social, work, family, life-skills, and self-care domains. Regardless of the reporter, the results of this study indicated that sleep quality was significantly associated with ADHD-related functional impairments in the academic and life skills domains. For the other domains of functioning, results varied depending on the reporter. Previous studies have shown that adolescent sleep disturbances are associated with academic underperformance and homework Problems (Cusick et al., 2018; Loram et al., 2021). This study expands upon these studies by supporting that adolescent sleep quality is also associated with other domains of functioning. This may suggest that targeting sleep may be helpful in lessen ADHD-related functional impairments in adolescents.
DOI: 10.7274/26211110.v1
title: Sleep Disturbances and ADHD-Related Impairments among Adolescents

description: Attention Deficit Hyperactive Disorder (ADHD), a neurodevelopmental disorder characterized by age-inappropriate symptoms of inattention and/or hyperactivity/impulsivity, is one of the most prevalent childhood disorders with rates as high as 10.9% among children and adolescents within the U.S (Li et al., 2023). Despite behavioral therapies becoming more sophisticated overtime, many youth with ADHD continue to exhibit significant functional impairments such as underperformance in school and at work, conflict with family and peers, and lower self-concept. Considering that sleep disturbances are often comorbid with ADHD and often result in similar impairments, the concomitant sleep problems may explain some of the unexplained variance left over in the association between ADHD symptoms and impairments. However, additional basic research is needed to further understand the relation between these variables, especially during adolescence when sleep problems are prominent. This study hypothesized that adolescent sleep quality was associated with ADHD-related impairments while controlling for ADHD symptoms, ADHD medication usage, gender, and age. A community sample of 243 mother-adolescent dyads from across the U.S. were recruited via Facebook ads. Mothers and adolescents completed a series of parent- and 
self-report questionnaires assessing ADHD symptoms, ADHD-related impairments, and sleep quality. Utilizing structural equation modeling, multivariate models were used to examine if sleep quality was associated with ADHD-related impairments in the academic, social, work, family, life-skills, and self-care domains. Regardless of the reporter, the results of this study indicated that sleep quality was significantly associated with ADHD-related functional impairments in the academic and life skills domains. For the other domains of functioning, results varied depending on the reporter. Previous studies have shown that adolescent sleep disturbances are associated with academic underperformance and homework Problems (Cusick et al., 2018; Loram et al., 2021). This study expands upon these studies by supporting that adolescent sleep quality is also associated with other domains of functioning. This may suggest that targeting sleep may be helpful in lessen ADHD-related functional impairments in adolescents.
DOI: 10.7274/26211131
title: Unitary Cognitive Control and Suicide Risk: An Emphasis on Interpersonal Stress

description: One way of understanding suicide, a global health concern is viewing it as a decision. Although theories on suicide differ on the critical components, they often conceptualize suicide as a choice between life and death, and propose that individuals endorse suicidal thoughts and behaviors (STB) when the pain of living outweighs the costs of dying. Understanding the intricate decision-making processes involved in suicide may begin by examining basic cognitive functions such as inhibition, cognitive flexibility, and working memory. A higher-order cognitive system that accounts for these basic functions and is crucial in goal-directed behaviors is cognitive control. Cognitive control has been associated with suicide as those with a history of STBs often exhibit difficulties in inhibiting attention from suicide related stimuli, demonstrating flexibility and switching cognitive strategies based on environmental feedback, and processing information in working memory. 

Thus far, subcomponents of cognitive control (i.e., inhibition, cognitive flexibility, and working memory) have often been used to represent the whole, which can be misleading and the whole may be greater than the sum of its parts. For example, the implications of cognitive flexibility, which is usually perceived as a positive construct, may change when examined in conjunction with inhibition. That is, if an individual has difficulty in inhibiting from negative information, then flexibility may indicate an increased ability to generate negative strategies that lead to maladaptive outcomes. Furthermore, past studies have not examined how specific contexts may alter the relationship between cognitive control and suicide even though cognitive control is significantly influenced by stress. 

This study aims to look at cognitive control as a unitary construct formed by three causal indicators: inhibition, working memory, and cognitive flexibility. Using casual indicator models in structural equation modeling, this study examines how susceptibility to interpersonal stress moderates the effects of cognitive control on suicide risk among individuals who endorse suicide. This study contributes to the existing literature by considering cognitive control as a system can considering specific contexts in which its effect on suicide may differ. The findings of this study have the potential of elucidating the decision-making processes that are involved in suicide and can provide important implications that can be used for prevention and intervention.
DOI: 10.7274/26211131.v1
title: Unitary Cognitive Control and Suicide Risk: An Emphasis on Interpersonal Stress

description: One way of understanding suicide, a global health concern is viewing it as a decision. Although theories on suicide differ on the critical components, they often conceptualize suicide as a choice between life and death, and propose that individuals endorse suicidal thoughts and behaviors (STB) when the pain of living outweighs the costs of dying. Understanding the intricate decision-making processes involved in suicide may begin by examining basic cognitive functions such as inhibition, cognitive flexibility, and working memory. A higher-order cognitive system that accounts for these basic functions and is crucial in goal-directed behaviors is cognitive control. Cognitive control has been associated with suicide as those with a history of STBs often exhibit difficulties in inhibiting attention from suicide related stimuli, demonstrating flexibility and switching cognitive strategies based on environmental feedback, and processing information in working memory. 

Thus far, subcomponents of cognitive control (i.e., inhibition, cognitive flexibility, and working memory) have often been used to represent the whole, which can be misleading and the whole may be greater than the sum of its parts. For example, the implications of cognitive flexibility, which is usually perceived as a positive construct, may change when examined in conjunction with inhibition. That is, if an individual has difficulty in inhibiting from negative information, then flexibility may indicate an increased ability to generate negative strategies that lead to maladaptive outcomes. Furthermore, past studies have not examined how specific contexts may alter the relationship between cognitive control and suicide even though cognitive control is significantly influenced by stress. 

This study aims to look at cognitive control as a unitary construct formed by three causal indicators: inhibition, working memory, and cognitive flexibility. Using casual indicator models in structural equation modeling, this study examines how susceptibility to interpersonal stress moderates the effects of cognitive control on suicide risk among individuals who endorse suicide. This study contributes to the existing literature by considering cognitive control as a system can considering specific contexts in which its effect on suicide may differ. The findings of this study have the potential of elucidating the decision-making processes that are involved in suicide and can provide important implications that can be used for prevention and intervention.
DOI: 10.7274/26288737
title: Sense of Agency as a Basis of Perceptual Decision-Making in Visual Search

description: Understanding how and why individuals make decisions during visual search has historically formed the basis of a large body of research. When presenting individuals with choice between visual contexts, such as in a two-alternative forced-choice paradigm, analyzing context selection can provide insight into motivation for context preference and decision-making. At the same time, these types of tasks inherently contain elements of volition that may affect the alignment of top-down information and feelings of agency during visual search. I presently assert that subject preference during two-alternative forced-choice visual search tasks is driven by a sense of agency, forming a basis for perceptual preference in visual search. Employing a choice paradigm, it was determined that instructing individuals to select contexts based on feelings of agency resulted in patterns of behavior statistically indistinguishable from behaviors seen when asking individuals to freely select contexts (Gibson et al., 2021). Additionally, using a within-subjects design to directly measure the alignment of top-down information with sense of agency found that in a force-choice task, patterns of context preference represent feelings of agency more consistent with an alignment of information and agency. These findings mirrored previous research supporting the inclusion of an element of volition as sufficient in moderating the relationship between information and agency in visual search. Finally, testing this notion further by manipulating the amount of volition present in our experimental paradigm, this manipulation was found to be sufficient in moderating feelings of agency reported under various values of top-down information.
DOI: 10.7274/26288737.v1
title: Sense of Agency as a Basis of Perceptual Decision-Making in Visual Search

description: Understanding how and why individuals make decisions during visual search has historically formed the basis of a large body of research. When presenting individuals with choice between visual contexts, such as in a two-alternative forced-choice paradigm, analyzing context selection can provide insight into motivation for context preference and decision-making. At the same time, these types of tasks inherently contain elements of volition that may affect the alignment of top-down information and feelings of agency during visual search. I presently assert that subject preference during two-alternative forced-choice visual search tasks is driven by a sense of agency, forming a basis for perceptual preference in visual search. Employing a choice paradigm, it was determined that instructing individuals to select contexts based on feelings of agency resulted in patterns of behavior statistically indistinguishable from behaviors seen when asking individuals to freely select contexts (Gibson et al., 2021). Additionally, using a within-subjects design to directly measure the alignment of top-down information with sense of agency found that in a force-choice task, patterns of context preference represent feelings of agency more consistent with an alignment of information and agency. These findings mirrored previous research supporting the inclusion of an element of volition as sufficient in moderating the relationship between information and agency in visual search. Finally, testing this notion further by manipulating the amount of volition present in our experimental paradigm, this manipulation was found to be sufficient in moderating feelings of agency reported under various values of top-down information.
DOI: 10.7274/26761573
title: Bayesian Inference for Growth Mixture Models with an Unknown Number of Classes

description: Growth mixture models (GMMs) have been widely used to capture different growth trajectories of unobserved subpopulations (or latent classes). The traditional GMM determines the optimal number of classes through a process called class enumeration, which involves fitting a sequence of models with an increasing number of classes and then selecting the best-fitting model using statistical criteria. Despite its popularity, class enumeration has long been criticized for introducing severe subjectivity when comparing the fitted models. 

Bayesian nonparametric (BNP) mixture modeling offers an alternative approach to detecting latent classes. The BNP approach circumvents the subjectivity inherent in class enumeration by placing a prior on the mixing distribution, which indirectly induces a prior on the number of classes. Consequently, the number of classes can be inferred directly from the data. However, the BNP approach remains understudied in the context of GMM. To reduce this research gap, the dissertation aims to: 1) propose two BNP-GMMs using the Dirichlet process mixture and the mixture of finite mixtures models; 2) compare the performance of the two proposed models in determining the number of classes $K$ with that of the traditional GMM; and 3) evaluate the performance of the two proposed models in choosing K when using the mode versus when using a loss function called variation of information (VI). 

Based on Monte Carlo simulations, Study 1 compares the proposed models and the traditional GMM in choosing K when there is no model misspecification, while Study 2 compares them in choosing K when there is model misspecification in the latent mean structure. Overall, simulation results showed that: 1) the proposed models using VI were more accurate than using the mode; 2) when the population was homogeneous (comprising only one class), the proposed models using VI yielded the highest accuracy in choosing K; whereas, when the population was heterogeneous (consisting of three classes), the proposed models using VI achieved superior accuracy in choosing K when class separation was large; and 3) the proposed models using VI demonstrated robustness against exacerbated overfitting caused by model misspecification. For illustration, the proposed BNP-GMMs were applied to data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99.