Fluency is an important construct in clinical assessment and in cognitive taxonomies. In the Cattell-Horn-Carroll (CHC) model, Fluency is represented by several narrow factors that form a subset of the long-term memory encoding and retrieval (Glr) broad factor. The CHC broad classification of Fluency was evaluated in five data sets, and the CHC…

The present study examined the factor structure of the Luria interpretive model for the Kaufman Assessment Battery for Children-Second Edition (KABC-II) with normative sample participants aged 7-18 (N = 2,025) using confirmatory factor analysis with maximum-likelihood estimation. For the eight subtest Luria configuration, an alternative…

The examinee-selected-item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set of items (e.g., choose one item to respond from a pair of items), always yields incomplete data (i.e., only the selected items are answered and the others have missing data) that are likely nonignorable. Therefore, using…

The current study represents the first longitudinal investigation of the potential effects of breastfeeding duration on maternal sensitivity over the following decade. This study also examined whether infant attachment security at 24 months would mediate longitudinal relations between breastfeeding duration and changes in maternal sensitivity over…

Questions concerning longitudinal stability and multi-method consistency are critical to temperament research. Latent State-Trait (LST) analyses address these directly, and were utilized in this study. Thus, our primary objective was to apply LST analyses in a temperament context, using longitudinal and multi-method data to determine the amount of…

Unidimensionality and local independence are two common assumptions of item response theory. The former implies that all items measure a common latent trait, while the latter implies that responses are independent, conditional on respondents' location on the latent trait. Yet, few tests are truly unidimensional. Unmodeled dimensions may result in…

Social class mobility from grandparent to grandchild is a relatively neglected topic. Grandparents today are often healthier and more active, and have longer relationships with their grandchildren than in previous generations. We used data from the UK's Millennium Cohort Study (n = 8570) to investigate the influence of maternal and paternal…

Multilevel models (MLMs) have proven themselves to be very useful in social science research, as data from a variety of sources is sampled such that individuals at level-1 are nested within clusters such as schools, hospitals, counseling centers, and business entities at level-2. MLMs using restricted maximum likelihood estimation (REML) provide…

The item-position effect describes how an item's position within a test, that is, the number of previous completed items, affects the response to this item. Previously, this effect was represented by constraints reflecting simple courses, for example, a linear increase. Due to the inflexibility of these representations our aim was to examine…

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the…

The current study examined the factor structure of the Schutte Self-Report Emotional Intelligence (SSREI) scale with an American college sample (n = 404, 322 females, 88.9% Whites). Data were collected through an online survey, and confirmatory factor analyses were conducted to test several proposed factor models from previous studies. The results…

The uncertainty arising from item parameter estimation is often not negligible and must be accounted for when calculating latent variable (LV) scores in item response theory (IRT). It is particularly so when the calibration sample size is limited and/or the calibration IRT model is complex. In the current work, we treat two-stage IRT scoring as a…

The purpose of this study is to analyze whether self-directedness in learning has positive effects on employment readiness of undergraduates. The subject of this study has little precedent research and we generated a research model. This study shows the following results: First, intrinsic motivation factor of self-directedness in learning has a…

Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…

This article illustrates five different methods for estimating Angoff cut scores using item response theory (IRT) models. These include maximum likelihood (ML), expected a priori (EAP), modal a priori (MAP), and weighted maximum likelihood (WML) estimators, as well as the most commonly used approach based on translating ratings through the test…