Xiaoxiao Zhou
Biographic Data
| ID | 4466000 |
|---|---|
| NAME | Xiaoxiao Zhou |
| GIVEN NAMES | Xiaoxiao |
| FAMILY NAME | Zhou |
| SIGNATURE | ZHOU X |
| AFFILIATIONS | Chinese University of Hong Kong |
| ORCID | 0000-0001-5208-673X |
| VERIFIED | Yes |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 9 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Bayesian Structural Equation Multi-State Model for Mediation Analysis
This study introduces a joint modeling framework that integrates structural equation model (SEM) with multi-state semi-competing risks model to investigate the complex causal mechanism among exposure, latent mediators, and multiple hierarchically correlated survival outcomes. The framework first employs a linear SEM to characterize latent mediators underlying highly correlated observable surrogates. These latent mediators are then incorporated in…
Unlocking spatiotemporal causal networks of the water-energy-food-carbon nexus in China
Carbon footprints in the context of financial innovation and human capital transformation
Climate change’s severity has escalated, necessitating low-carbon transitions and new financial solutions for governments and businesses. Nonetheless, the relationship between FinTech and labor components related to green innovation in selected Chinese industrial sectors remains understudied. This study investigates the interplay between financial innovation (FI) and workforce transformation on corporate carbon emissions (CCE) using data from Chi…
Moran process stochastic evolutionary game model for cooperative innovation strategies in green technology
Causal Mediation Analysis for Multivariate Longitudinal Data and Survival Outcomes
This study proposes a joint modeling approach to conduct causal mediation analysis that accommodates multivariate longitudinal data, dynamic latent mediator, and survival outcome. First, we introduce a confirmatory factor analysis model to characterize a time-varying latent mediator through multivariate longitudinal observable variables. Then, we establish a growth curve model to describe the linear trajectory of the dynamic latent mediator and s…
Bayesian Quantile Latent Factor on Image Regression
This paper considers a quantile latent factor-on-image (Q-LoI) regression model to comprehensively investigate the relationship between the latent factor of interest and scalar and imaging predictors at different quantiles. The latent factor is characterized by several manifest variables through a confirmatory factor analysis model and then regressed on scalar and imaging covariates. We propose a two-stage method to conduct statistical inference.…
Joint Hidden Markov Model for Longitudinal and Time-to-Event Data with Latent Variables
This study develops a new joint modeling approach to simultaneously analyze longitudinal and time-to-event data with latent variables. The proposed model consists of three components. The first component is a hidden Markov model for investigating a longitudinal observation process and its underlying transition process as well as their potential risk factors and dynamic heterogeneity. The second component is a factor analysis model for characteriz…
Bayesian Causal Mediation Analysis with Latent Mediators and Survival Outcome
This study develops a joint modeling approach that incorporates latent traits into causal mediation analysis with multiple mediators and a survival outcome. A linear structural equation model is used to characterize the latent mediators with several highly correlated observable surrogates and depicts the relationships among multiple parallel or causally ordered mediators and the exposure. A proportional hazards model is used to derive the path-sp…
Technological innovation and structural change for economic development in China as an emerging market
No prominent works on this page.
Bayesian Causal Mediation Analysis with Latent Mediators and Survival Outcome
This study develops a joint modeling approach that incorporates latent traits into causal mediation analysis with multiple mediators and a survival outcome. A linear structural equation model is used to characterize the latent mediators with several highly correlated observable surrogates and depicts the relationships among multiple parallel or causally ordered mediators and the exposure. A proportional hazards model is used to derive the path-sp…
Technological innovation and structural change for economic development in China as an emerging market
Joint Hidden Markov Model for Longitudinal and Time-to-Event Data with Latent Variables
This study develops a new joint modeling approach to simultaneously analyze longitudinal and time-to-event data with latent variables. The proposed model consists of three components. The first component is a hidden Markov model for investigating a longitudinal observation process and its underlying transition process as well as their potential risk factors and dynamic heterogeneity. The second component is a factor analysis model for characteriz…
Causal Mediation Analysis for Multivariate Longitudinal Data and Survival Outcomes
This study proposes a joint modeling approach to conduct causal mediation analysis that accommodates multivariate longitudinal data, dynamic latent mediator, and survival outcome. First, we introduce a confirmatory factor analysis model to characterize a time-varying latent mediator through multivariate longitudinal observable variables. Then, we establish a growth curve model to describe the linear trajectory of the dynamic latent mediator and s…
Bayesian Quantile Latent Factor on Image Regression
This paper considers a quantile latent factor-on-image (Q-LoI) regression model to comprehensively investigate the relationship between the latent factor of interest and scalar and imaging predictors at different quantiles. The latent factor is characterized by several manifest variables through a confirmatory factor analysis model and then regressed on scalar and imaging covariates. We propose a two-stage method to conduct statistical inference.…
Moran process stochastic evolutionary game model for cooperative innovation strategies in green technology
Bayesian Structural Equation Multi-State Model for Mediation Analysis
This study introduces a joint modeling framework that integrates structural equation model (SEM) with multi-state semi-competing risks model to investigate the complex causal mechanism among exposure, latent mediators, and multiple hierarchically correlated survival outcomes. The framework first employs a linear SEM to characterize latent mediators underlying highly correlated observable surrogates. These latent mediators are then incorporated in…
Unlocking spatiotemporal causal networks of the water-energy-food-carbon nexus in China
Carbon footprints in the context of financial innovation and human capital transformation
Climate change’s severity has escalated, necessitating low-carbon transitions and new financial solutions for governments and businesses. Nonetheless, the relationship between FinTech and labor components related to green innovation in selected Chinese industrial sectors remains understudied. This study investigates the interplay between financial innovation (FI) and workforce transformation on corporate carbon emissions (CCE) using data from Chi…
Bayesian probability (5 works) · Computer Science (5 works) · Artificial Intelligence (4 works) · Econometrics (4 works) · Latent variable (4 works) · Mathematics (4 works) · Statistical Methods and Bayesian Inference (4 works) · Statistical Methods and Inference (4 works) · Structural equation modeling (4 works) · Markov chain Monte Carlo (3 works)