Hairong Song
Biographic Data
| ID | 4416555 |
|---|---|
| NAME | Hairong Song |
| GIVEN NAMES | Hairong |
| FAMILY NAME | Song |
| SIGNATURE | SONG H |
| AFFILIATIONS | University of Oklahoma |
| ORCID | 0000-0001-5164-2159 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 10 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 2 |
Predicting Successful Treatment Completion Using Baseline Case Characteristics through Machine Learning and Ensemble Modeling: A Two-Step Approach
“Different Dialects”: Examining masculine and feminine honor across gender and ethnicity in an american context
It Matters: Reference Indicator Selection in Measurement Invariance Tests
Conventional approaches for selecting a reference indicator (RI) could lead to misleading results in testing for measurement invariance (MI). Several newer quantitative methods have been available for more rigorous RI selection. However, it is still unknown how well these methods perform in terms of correctly identifying a truly invariant item to be an RI. Thus, Study 1 was designed to address this issue in various conditions using simulated data…
Evaluating Factorial Invariance: An Interval Estimation Approach Using Bayesian Structural Equation Modeling
In this study, we introduce an interval estimation approach based on Bayesian structural equation modeling to evaluate factorial invariance. For each tested parameter, the size of noninvariance with an uncertainty interval (i.e. highest density interval [HDI]) is assessed via Bayesian parameter estimation. By comparing the most credible values (i.e. 95% HDI) with a region of practical equivalence (ROPE), the Bayesian approach allows researchers t…
The Development of Implicit Self-Esteem During Emerging Adulthood: A Longitudinal Analysis
Emerging adulthood is one of the most important life stages for self and identity development. The present research tracked the development of implicit self-esteem during emerging adulthood at both the group and individual levels. We used the implicit association test to assess implicit self-esteem with the improved D score as the index. We surveyed 327 students each year from the beginning of their first year of university until their graduation…
Bayesian SEM for Specification Search Problems in Testing Factorial Invariance
Specification search problems refer to two important but under-addressed issues in testing for factorial invariance: how to select proper reference indicators and how to locate specific non-invariant parameters. In this study, we propose a two-step procedure to solve these issues. Step 1 is to identify a proper reference indicator using the Bayesian structural equation modeling approach. An item is selected if it is associated with the highest li…
Examining the nature, causes, and consequences of profiles of organizational citizenship behavior
Research on organizational citizenship behavior (OCB) typically focuses on either one type of OCB or an aggregate of multiple types of OCB. We investigate a third conceptualization of OCB by examining how employees use conscientiousness, sportsmanship, civic virtue, courtesy, and altruism in distinct combinations. In Study 1, we identify 5 profiles of citizenship in a sample of 129 workers in a medium‐sized firm. Some employees used either high l…
Analyzing Multiple Multivariate Time Series Data Using Multilevel Dynamic Factor Models
Multivariate time series data offer researchers opportunities to study dynamics of various systems in social and behavioral sciences. Dynamic factor model (DFM), as an idiographic approach for studying intraindividual variability and dynamics, has typically been applied to time series data obtained from a single unit. When multivariate time series data are collected from multiple units, how to synchronize dynamical information becomes a silent is…
Distinguishing communal narcissism from agentic narcissism: A behavior genetics analysis on the agency–communion model of narcissism
Bayesian Estimation of Random Coefficient Dynamic Factor Models
Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across units. The aims of this study are (a) to propose a random coefficient DFM (RC-DFM) to statistically mo…
Examining the nature, causes, and consequences of profiles of organizational citizenship behavior
Research on organizational citizenship behavior (OCB) typically focuses on either one type of OCB or an aggregate of multiple types of OCB. We investigate a third conceptualization of OCB by examining how employees use conscientiousness, sportsmanship, civic virtue, courtesy, and altruism in distinct combinations. In Study 1, we identify 5 profiles of citizenship in a sample of 129 workers in a medium‐sized firm. Some employees used either high l…
Predicting Successful Treatment Completion Using Baseline Case Characteristics through Machine Learning and Ensemble Modeling: A Two-Step Approach
Distinguishing communal narcissism from agentic narcissism: A behavior genetics analysis on the agency–communion model of narcissism
Bayesian Estimation of Random Coefficient Dynamic Factor Models
Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across units. The aims of this study are (a) to propose a random coefficient DFM (RC-DFM) to statistically mo…
Analyzing Multiple Multivariate Time Series Data Using Multilevel Dynamic Factor Models
Multivariate time series data offer researchers opportunities to study dynamics of various systems in social and behavioral sciences. Dynamic factor model (DFM), as an idiographic approach for studying intraindividual variability and dynamics, has typically been applied to time series data obtained from a single unit. When multivariate time series data are collected from multiple units, how to synchronize dynamical information becomes a silent is…
Distinguishing communal narcissism from agentic narcissism: A behavior genetics analysis on the agency–communion model of narcissism
Bayesian SEM for Specification Search Problems in Testing Factorial Invariance
Specification search problems refer to two important but under-addressed issues in testing for factorial invariance: how to select proper reference indicators and how to locate specific non-invariant parameters. In this study, we propose a two-step procedure to solve these issues. Step 1 is to identify a proper reference indicator using the Bayesian structural equation modeling approach. An item is selected if it is associated with the highest li…
Examining the nature, causes, and consequences of profiles of organizational citizenship behavior
Research on organizational citizenship behavior (OCB) typically focuses on either one type of OCB or an aggregate of multiple types of OCB. We investigate a third conceptualization of OCB by examining how employees use conscientiousness, sportsmanship, civic virtue, courtesy, and altruism in distinct combinations. In Study 1, we identify 5 profiles of citizenship in a sample of 129 workers in a medium‐sized firm. Some employees used either high l…
The Development of Implicit Self-Esteem During Emerging Adulthood: A Longitudinal Analysis
Emerging adulthood is one of the most important life stages for self and identity development. The present research tracked the development of implicit self-esteem during emerging adulthood at both the group and individual levels. We used the implicit association test to assess implicit self-esteem with the improved D score as the index. We surveyed 327 students each year from the beginning of their first year of university until their graduation…
Evaluating Factorial Invariance: An Interval Estimation Approach Using Bayesian Structural Equation Modeling
In this study, we introduce an interval estimation approach based on Bayesian structural equation modeling to evaluate factorial invariance. For each tested parameter, the size of noninvariance with an uncertainty interval (i.e. highest density interval [HDI]) is assessed via Bayesian parameter estimation. By comparing the most credible values (i.e. 95% HDI) with a region of practical equivalence (ROPE), the Bayesian approach allows researchers t…
It Matters: Reference Indicator Selection in Measurement Invariance Tests
Conventional approaches for selecting a reference indicator (RI) could lead to misleading results in testing for measurement invariance (MI). Several newer quantitative methods have been available for more rigorous RI selection. However, it is still unknown how well these methods perform in terms of correctly identifying a truly invariant item to be an RI. Thus, Study 1 was designed to address this issue in various conditions using simulated data…
“Different Dialects”: Examining masculine and feminine honor across gender and ethnicity in an american context
Predicting Successful Treatment Completion Using Baseline Case Characteristics through Machine Learning and Ensemble Modeling: A Two-Step Approach
Computer Science (6 works) · Mathematics (6 works) · Statistics (6 works) · Psychology (5 works) · Artificial Intelligence (4 works) · Data mining (4 works) · Machine learning (4 works) · Social Psychology (4 works) · Artificial Intelligence (3 works) · Bayesian probability (3 works)