In many psychological and educational applications, it is imperative to obtain valid and reliable score estimates of multilevel processes. For example, in order to assess the quality and characteristics of high impact learning processes, one must compute accurate scores representative of student- and classroom-level constructs. Currently, there…

Cluster memberships associated with the mediation effect are often changed due to the temporal distance between the cause-and-effect variables in longitudinal data. Nevertheless, current practices in multilevel mediation analysis mostly assume a purely hierarchical data structure. A Monte Carlo simulation study is conducted to examine the…

The Q-matrix played a key role in implementations of diagnostic classification models (DCMs) or cognitive diagnostic models (CDMs) -- a family of psychometric models that are gaining attention in providing diagnostic information on students' mastery of cognitive attributes or skills. Using two Monte Carlo simulation studies, this dissertation…

Mixture modeling is a latent variable (i.e., a variable that cannot be measured directly) approach to quantitatively represent unobserved subpopulations within an overall population. It includes a range of cross-sectional (such as latent class [LCA] or latent profile analysis) and longitudinal (such as latent transition analysis) analyses and is…

Creativity and well-being are popular subjects in psychological and organizational studies. The recent literature presented mixed perspectives about the nature of the relationship between the two. Whereas the mad-genius hypothesis, which was often explored among eminently creative individuals, seems to imply a negative relationship between the…

The challenge and pleasures of studying child and adolescent peer experiences come from the complexity and the significance of these relationships for development in childhood and adolescence. In spite of the recognized strengths of the current literature on the effects of experiences with peers, research on peer experiences is often limited by an…

Multidimensionality and hierarchical data structure are common in assessment data. These design features, if not accounted for, can threaten the validity of the results and inferences generated from factor analysis, a method frequently employed to assess test dimensionality. In this article, we describe and demonstrate the application of the…

Professional learning (PL) encompasses the complexity of teacher learning and teacher agency in the process of learning. This paper aims to shed light on this complexity and proffers a conceptual meta-model of PL grounded in pragmatism to inform action in the design and evaluation of PL. It will firstly explore the aim and implications of the…

Learning processes often occur at a situational level. Changes in learning context have implications on how students are motivated or are able to cognitively process information. To study such situational phenomena, Experience Sampling Method (ESM) can help assess psychological variables in the moment and in context. However, data collected via…

Students in the Detroit Public Community Schools District (DPSCD) have the highest rate of chronic absence (missing 10% or more of school days) among large districts in the United States. Additionally, students in DPSCD are among the poorest students in the country, often lacking access to reliable personal transportation or public transit to…

Within-cluster variance homogeneity is one of the key assumptions of multilevel models; however, assuming a constant (i.e. equal) within-cluster variance may not be realistic. Moreover, existent within-cluster variance heterogeneity should be regarded as a source of additional information rather than a violation of a model assumption. This study…

Reliability indicates the internal consistency of a test. In educational studies, reliability is a key feature for a test. Researchers have proposed many traditional reliability estimates, such as coefficient alpha and coefficient omega. However, traditional reliability indices do not deal with the data hierarchy, even though the multilevel…

It is not always clear how to adjust for control data in causal inference, balancing the goals of reducing bias and variance. We show how, in a setting with repeated experiments, Bayesian hierarchical modeling yields an adaptive procedure that uses the data to determine how much adjustment to perform. The result is a novel analysis with increased…

While the family is a critical determinant of educational achievement, methodological difficulties and the availability of data limit estimation of the family contribution in school effectiveness models. This study uses multilevel modeling to estimate the proportion of variation in student educational achievement between families, family-level…

In Bayesian statistics, the most widely used criteria of Bayesian model assessment and comparison are Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). A multilevel mediation model is used as an illustrative example to compare different types of DIC and WAIC. More specifically, the study compares the…