Jeffrey R Harring
Biographic Data
| ID | 4270348 |
|---|---|
| NAME | Jeffrey R Harring |
| GIVEN NAMES | Jeffrey R |
| FAMILY NAME | Harring |
| SIGNATURE | HARRING J R |
| AFFILIATIONS | University of Maryland, College Park, MD, USA |
| ORCID | 0000-0002-7102-0303 |
| VERIFIED | Yes |
| TOTAL WORKS | 30 |
| TOTAL CITATIONS | 32 |
| AUTHOR COUNT | 30 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2006 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Sensitivity Analyses for Omitted Confounders in Structural Equation Models with Tabu Search Optimization
Structural equation modeling (SEM) is a popular methodological approach for representing and testing hypothesized relationships among observed and unobserved, or latent, variables. Researchers in the social and behavioral sciences commonly encounter three general situations for testing such structural equation models—strictly confirmatory, testing alternative or competing hypothesized models, and model generation. However, none of these involve t…
Leveraging Bayesian Statistics in Educational Leadership and Policy Studies
Purpose This paper examines the application of Bayesian statistics in educational leadership and policy studies. It explores the philosophical and methodological foundations, highlights the contributions to estimation thinking in quantitative research, demonstrates the implementation of Bayesian methods through a detailed case study, and proposes a heuristic for applying Bayesian techniques in educational research. Research Approach Building on t…
Detecting Preknowledge Cheating via Innovative Measures: A Mixture Hierarchical Model for Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts
Preknowledge cheating jeopardizes the validity of inferences based on test results. Many methods have been developed to detect preknowledge cheating by jointly analyzing item responses and response times. Gaze fixations, an essential eye-tracker measure, can be utilized to help detect aberrant testing behavior with improved accuracy beyond using product and process data types in isolation. As such, this study proposes a mixture hierarchical model…
Using Simulated Annealing to Investigate Sensitivity of SEM to External Model Misspecification
Sensitivity analyses encompass a broad set of post-analytic techniques that are characterized as measuring the potential impact of any factor that has an effect on some output variables of a model. This research focuses on the utility of the simulated annealing algorithm to automatically identify path configurations and parameter values of omitted confounders in structural equation modeling (SEM). An empirical example based on a past published st…
Latent Growth Modeling with Categorical Response Data: A Methodological Investigation of Model Parameterization, Estimation, and Missing Data
Measuring change in an educational or psychological construct over time is often achieved by repeatedly administering the same items to the same examinees over time and fitting a second-order latent growth curve model. However, latent growth modeling with full information maximum likelihood (FIML) estimation becomes computationally challenging when the observed response data are categorical. This study first discusses some possible options that r…
Using Ant Colony Optimization for Sensitivity Analysis in Structural Equation Modeling
Studies using structural equation modeling (SEM) to evaluate theories against observed data rely on multiple sources of evidence to support a proposed model, such as fit indices, variance explained, and comparison of alternative models. Additional evidence can be obtained by evaluating the model results’ sensitivity to an omitted confounder. The phantom variable approach to SEM sensitivity analysis requires manual specification of sensitivity par…
A Comparison of Label Switching Algorithms in the Context of Growth Mixture Models
Simulation studies involving mixture models inevitably aggregate parameter estimates and other output across numerous replications. A primary issue that arises in these methodological investigations is label switching. The current study compares several label switching corrections that are commonly used when dealing with mixture models. A growth mixture model is used in this simulation study, and the design crosses three manipulated variables—num…
Assessing Preknowledge Cheating via Innovative Measures: A Multiple-Group Analysis of Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given this context, this study demonstrates the application of a new method for multiple-group analysis that …
Fitting Nonlinear Mixed-effects Models With Alternative Residual Covariance Structures
Nonlinear mixed-effects models are models in which one or more coefficients of the growth model enter in a nonlinear manner, such as appearing in the exponent of the growth function. In their applications, the within-individual residuals are often assumed to be independent with constant variance across time, an assumption that implies that the assumed growth function fully accounts for the dependencies and patterns of variation in the data. Studi…
Methods of Integrating Multi-Modal Data for Assessing Aberrant Test-Taking Behaviors
"Methods of Integrating Multi-Modal Data for Assessing Aberrant Test-Taking Behaviors." Multivariate Behavioral Research, 55(1), pp. 155–156
Heterogeneity in the dynamic arousal and modulation of fear in young foster children
Teaching Bilingual Learners: Effects of a Language‐Based Reading Intervention on Academic Language and Reading Comprehension in Grades 4 and 5
Students are expected to comprehend and produce increasingly complex texts in upper elementary school, and academic language and literacy skills are considered critical to meeting these expectations. Notions of academic language are also controversial and require careful deliberation when applied to traditionally minoritized populations, including bilingual learners who negotiate more than one language in their daily lives and have varied linguis…
Negative Binomial Models for Visual Fixation Counts on Test Items
With the development of technology-enhanced learning platforms, eye-tracking biometric indicators can be recorded simultaneously with students item responses. In the current study, visual fixation, an essential eye-tracking indicator, is modeled to reflect the degree of test engagement when a test taker solves a set of test questions. Three negative binomial regression models are proposed for modeling visual fixation counts of test takers solving…
Latent Growth Models with Floors, Ceilings, and Random Knots
In longitudinal/developmental studies, individual growth trajectories are sometimes bounded by a floor at the beginning of the observation period and/or a ceiling toward the end of the observation period (or vice versa), resulting in inherently nonlinear growth patterns. If the trajectories between the floor and ceiling are approximately linear, such longitudinal growth patterns can be described with a linear piecewise (spline) model in which seg…
The effects of getting a new teacher on the consistency of personality
OBJECTIVE: In the present research, we examined the effect of getting a new teacher on consistency in students' personality measures, including trait and social cognitive constructs. METHOD: To test the effect of this kind of situational transition, we analyzed two large longitudinal samples (N = 5,628; N = 2,458) with quasi-experimental study designs. We used two consistency measures (i.e., rank-order clations and changes in variance over time) …
A brief parent-focused intervention to improve preschoolers’ conversational skills and school readiness
Preschool children's use of decontextualized language, or talk about abstract topics beyond the here-and-now, is predictive of their kindergarten readiness and is associated with the frequency of parents' own use of decontextualized language. Does a brief, parent-focused intervention conveying the importance of decontextualized language cause parents to increase their use of these conversations, and as a result, their children's? We examined this…
Investigating Approaches to Estimating Covariate Effects in Growth Mixture Modeling: A Simulation Study
Researchers continue to be interested in efficient, accurate methods of estimating coefficients of covariates in mixture modeling. Including covariates related to the latent class analysis not only may improve the ability of the mixture model to clearly differentiate between subjects but also makes interpretation of latent group membership more meaningful. Very few studies have been conducted that compare the performance of various approaches to …
Correcting Model Fit Criteria for Small Sample Latent Growth Models With Incomplete Data
To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data–model fit. However, previous studies have demonstrated poor small sample performance of these global data–model fit criteria and three post hoc small sample correct…
Linguistic interdependence between Spanish language and English language and reading: A longitudinal exploration from second through fifth grade
This study explored effects of Spanish oral language skills (vocabulary and syntax) on the development of English oral language skills (vocabulary, morphology, semantics, syntax) and reading comprehension among 156 bilingual Latino children in second through fifth grade whose first language was Spanish and whose second language was English. Using a cohort-sequential design (Cohort 1: second–third grade; Cohort 2: third–fourth grade; Cohort 3: fou…
Understanding Individual-level Change Through the Basis Functions of a Latent Curve Model
Latent curve models have become a popular approach to the analysis of longitudinal data. At the individual level, the model expresses an individual's response as a linear combination of what are called 'basis functions' that are common to all members of a population and weights that may vary among individuals. This article uses differential calculus to define the basis functions of a latent curve model. This provides a meaningful interpretation o…
A Note on Recurring Misconceptions When Fitting Nonlinear Mixed Models
Nonlinear mixed-effects (NLME) models are used when analyzing continuous repeated measures data taken on each of a number of individuals where the focus is on characteristics of complex, nonlinear individual change. Challenges with fitting NLME models and interpreting analytic results have been well documented in the statistical literature. However, parameter estimates as well as fitted functions from NLME analyses in recent articles have been mi…
Assessing Spurious Interaction Effects in Structural Equation Modeling: A Cautionary Note
Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could result in Type I errors, Type II errors, or misleading interactions. Research investigating this issue…
A Note on the Specification of Error Structures in Latent Interaction Models
Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to their straightforward implementation and relative ease of estimation in mainstream structural equatio…
A Spline Regression Model for Latent Variables
Spline (or piecewise) regression models have been used in the past to account for patterns in observed data that exhibit distinct phases. The changepoint or knot marking the shift from one phase to the other, in many applications, is an unknown parameter to be estimated. As an extension of this framework, this research considers modeling the relation between endogenous and exogenous latent variables with a spline regression model, where each late…
Teachers' Instruction and Students' Vocabulary and Comprehension: An Exploratory Study With English Monolingual and Spanish-English Bilingual Students in Grades 3-5
The primary aim of this study was to explore the relationship between teachers' instruction and students' vocabulary and comprehension in grades 3–5. The secondary aim of this study was to investigate whether this relationship differed for English monolingual and Spanish–English bilingual students. To meet these aims, we observed and recorded reading/language arts instruction in 33 classrooms at three points during an academic year, and we assess…
Teaching Bilingual Learners: Effects of a Language‐Based Reading Intervention on Academic Language and Reading Comprehension in Grades 4 and 5
Students are expected to comprehend and produce increasingly complex texts in upper elementary school, and academic language and literacy skills are considered critical to meeting these expectations. Notions of academic language are also controversial and require careful deliberation when applied to traditionally minoritized populations, including bilingual learners who negotiate more than one language in their daily lives and have varied linguis…
A brief parent-focused intervention to improve preschoolers’ conversational skills and school readiness
Preschool children's use of decontextualized language, or talk about abstract topics beyond the here-and-now, is predictive of their kindergarten readiness and is associated with the frequency of parents' own use of decontextualized language. Does a brief, parent-focused intervention conveying the importance of decontextualized language cause parents to increase their use of these conversations, and as a result, their children's? We examined this…
Linguistic interdependence between Spanish language and English language and reading: A longitudinal exploration from second through fifth grade
This study explored effects of Spanish oral language skills (vocabulary and syntax) on the development of English oral language skills (vocabulary, morphology, semantics, syntax) and reading comprehension among 156 bilingual Latino children in second through fifth grade whose first language was Spanish and whose second language was English. Using a cohort-sequential design (Cohort 1: second–third grade; Cohort 2: third–fourth grade; Cohort 3: fou…
Teachers' Instruction and Students' Vocabulary and Comprehension: An Exploratory Study With English Monolingual and Spanish-English Bilingual Students in Grades 3-5
The primary aim of this study was to explore the relationship between teachers' instruction and students' vocabulary and comprehension in grades 3–5. The secondary aim of this study was to investigate whether this relationship differed for English monolingual and Spanish–English bilingual students. To meet these aims, we observed and recorded reading/language arts instruction in 33 classrooms at three points during an academic year, and we assess…
Fitting Partially Nonlinear Random Coefficient Models as SEMs
The nonlinear random coefficient model has become increasingly popular as a method for describing individual differences in longitudinal research. Although promising, the nonlinear model it is not utilized as often as it might be because software options are still somewhat limited. In this article we show that a specialized version of the model can be fit to data using SEM software. The specialization is to a model in which the parameters that en…
Latent Growth Modeling for Logistic Response Functions
Throughout much of the social and behavioral sciences, latent growth modeling (latent curve analysis) has become an important tool for understanding individuals' longitudinal change. Although nonlinear variations of latent growth models appear in the methodological and applied literature, a notable exclusion is the treatment of growth following logistic (sigmoidal; S-shape) response functions. Such trajectories are assumed in a variety of psychol…
Comparing Groups: Randomization and Bootstrap Methods Using R
"This book, written by three behavioral scientists for other behavioral scientists, addresses common issues in statistical analysis for the behavioral and educational sciences. Modern Statistical & Computing Methods for the Behavioral and Educational Sciences using R emphasizes the direct link between scientific research questions and data analysis. Purposeful attention is paid to the integration of design, statistical methodology, and computatio…
Piecewise Linear–Linear Latent Growth Mixture Models With Unknown Knots
Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear–linear latent growth mixture model (LGMM) for describing segmented change of individual behavior over time where the data come from a mixture of two or more unobserved subpopula…
Modeling Growth in Latent Variables Using a Piecewise Function
Latent growth curve models with piecewise functions for continuous repeated measures data have become increasingly popular and versatile tools for investigating individual behavior that exhibits distinct phases of development in observed variables. As an extension of this framework, this research study considers a piecewise function for describing segmented change of a latent construct over time where the latent construct is itself measured by mu…
A Note on the Specification of Error Structures in Latent Interaction Models
Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to their straightforward implementation and relative ease of estimation in mainstream structural equatio…
A Spline Regression Model for Latent Variables
Spline (or piecewise) regression models have been used in the past to account for patterns in observed data that exhibit distinct phases. The changepoint or knot marking the shift from one phase to the other, in many applications, is an unknown parameter to be estimated. As an extension of this framework, this research considers modeling the relation between endogenous and exogenous latent variables with a spline regression model, where each late…
Teachers' Instruction and Students' Vocabulary and Comprehension: An Exploratory Study With English Monolingual and Spanish-English Bilingual Students in Grades 3-5
The primary aim of this study was to explore the relationship between teachers' instruction and students' vocabulary and comprehension in grades 3–5. The secondary aim of this study was to investigate whether this relationship differed for English monolingual and Spanish–English bilingual students. To meet these aims, we observed and recorded reading/language arts instruction in 33 classrooms at three points during an academic year, and we assess…
Assessing Spurious Interaction Effects in Structural Equation Modeling: A Cautionary Note
Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could result in Type I errors, Type II errors, or misleading interactions. Research investigating this issue…
A Note on Recurring Misconceptions When Fitting Nonlinear Mixed Models
Nonlinear mixed-effects (NLME) models are used when analyzing continuous repeated measures data taken on each of a number of individuals where the focus is on characteristics of complex, nonlinear individual change. Challenges with fitting NLME models and interpreting analytic results have been well documented in the statistical literature. However, parameter estimates as well as fitted functions from NLME analyses in recent articles have been mi…
Investigating Approaches to Estimating Covariate Effects in Growth Mixture Modeling: A Simulation Study
Researchers continue to be interested in efficient, accurate methods of estimating coefficients of covariates in mixture modeling. Including covariates related to the latent class analysis not only may improve the ability of the mixture model to clearly differentiate between subjects but also makes interpretation of latent group membership more meaningful. Very few studies have been conducted that compare the performance of various approaches to …
Correcting Model Fit Criteria for Small Sample Latent Growth Models With Incomplete Data
To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data–model fit. However, previous studies have demonstrated poor small sample performance of these global data–model fit criteria and three post hoc small sample correct…
Linguistic interdependence between Spanish language and English language and reading: A longitudinal exploration from second through fifth grade
This study explored effects of Spanish oral language skills (vocabulary and syntax) on the development of English oral language skills (vocabulary, morphology, semantics, syntax) and reading comprehension among 156 bilingual Latino children in second through fifth grade whose first language was Spanish and whose second language was English. Using a cohort-sequential design (Cohort 1: second–third grade; Cohort 2: third–fourth grade; Cohort 3: fou…
Understanding Individual-level Change Through the Basis Functions of a Latent Curve Model
Latent curve models have become a popular approach to the analysis of longitudinal data. At the individual level, the model expresses an individual's response as a linear combination of what are called 'basis functions' that are common to all members of a population and weights that may vary among individuals. This article uses differential calculus to define the basis functions of a latent curve model. This provides a meaningful interpretation o…
A brief parent-focused intervention to improve preschoolers’ conversational skills and school readiness
Preschool children's use of decontextualized language, or talk about abstract topics beyond the here-and-now, is predictive of their kindergarten readiness and is associated with the frequency of parents' own use of decontextualized language. Does a brief, parent-focused intervention conveying the importance of decontextualized language cause parents to increase their use of these conversations, and as a result, their children's? We examined this…
Negative Binomial Models for Visual Fixation Counts on Test Items
With the development of technology-enhanced learning platforms, eye-tracking biometric indicators can be recorded simultaneously with students item responses. In the current study, visual fixation, an essential eye-tracking indicator, is modeled to reflect the degree of test engagement when a test taker solves a set of test questions. Three negative binomial regression models are proposed for modeling visual fixation counts of test takers solving…
Latent Growth Models with Floors, Ceilings, and Random Knots
In longitudinal/developmental studies, individual growth trajectories are sometimes bounded by a floor at the beginning of the observation period and/or a ceiling toward the end of the observation period (or vice versa), resulting in inherently nonlinear growth patterns. If the trajectories between the floor and ceiling are approximately linear, such longitudinal growth patterns can be described with a linear piecewise (spline) model in which seg…
The effects of getting a new teacher on the consistency of personality
OBJECTIVE: In the present research, we examined the effect of getting a new teacher on consistency in students' personality measures, including trait and social cognitive constructs. METHOD: To test the effect of this kind of situational transition, we analyzed two large longitudinal samples (N = 5,628; N = 2,458) with quasi-experimental study designs. We used two consistency measures (i.e., rank-order clations and changes in variance over time) …
Methods of Integrating Multi-Modal Data for Assessing Aberrant Test-Taking Behaviors
"Methods of Integrating Multi-Modal Data for Assessing Aberrant Test-Taking Behaviors." Multivariate Behavioral Research, 55(1), pp. 155–156
Heterogeneity in the dynamic arousal and modulation of fear in young foster children
Teaching Bilingual Learners: Effects of a Language‐Based Reading Intervention on Academic Language and Reading Comprehension in Grades 4 and 5
Students are expected to comprehend and produce increasingly complex texts in upper elementary school, and academic language and literacy skills are considered critical to meeting these expectations. Notions of academic language are also controversial and require careful deliberation when applied to traditionally minoritized populations, including bilingual learners who negotiate more than one language in their daily lives and have varied linguis…
A Comparison of Label Switching Algorithms in the Context of Growth Mixture Models
Simulation studies involving mixture models inevitably aggregate parameter estimates and other output across numerous replications. A primary issue that arises in these methodological investigations is label switching. The current study compares several label switching corrections that are commonly used when dealing with mixture models. A growth mixture model is used in this simulation study, and the design crosses three manipulated variables—num…
Assessing Preknowledge Cheating via Innovative Measures: A Multiple-Group Analysis of Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given this context, this study demonstrates the application of a new method for multiple-group analysis that …
Fitting Nonlinear Mixed-effects Models With Alternative Residual Covariance Structures
Nonlinear mixed-effects models are models in which one or more coefficients of the growth model enter in a nonlinear manner, such as appearing in the exponent of the growth function. In their applications, the within-individual residuals are often assumed to be independent with constant variance across time, an assumption that implies that the assumed growth function fully accounts for the dependencies and patterns of variation in the data. Studi…
Latent Growth Modeling with Categorical Response Data: A Methodological Investigation of Model Parameterization, Estimation, and Missing Data
Measuring change in an educational or psychological construct over time is often achieved by repeatedly administering the same items to the same examinees over time and fitting a second-order latent growth curve model. However, latent growth modeling with full information maximum likelihood (FIML) estimation becomes computationally challenging when the observed response data are categorical. This study first discusses some possible options that r…
Mathematics (22 works) · Computer Science (18 works) · Statistics (16 works) · Econometrics (12 works) · Psychology (10 works) · Psychometric Methodologies and Testing (10 works) · Machine learning (8 works) · Statistical Methods and Bayesian Inference (8 works) · Algorithm (7 works) · Artificial Intelligence (7 works)