Profile of Dr CHU, Man Ying Amanda 朱文英 - The Education University of Hong Kong


Assistant Professor	Department of Social Sciences and Policy Studies

Contact

ORCiD

0000-0002-9543-747X

Phone

(852) 2948 8941

amandachu@eduhk.hk

Address

10 Lo Ping Road, Tai Po, New Territories, Hong Kong

Website

https://pappl.eduhk.hk/rich/web/person.xhtml?pid=242043&name=CHU, Man Ying Amanda

Scopus ID

56154974100

Research Interests

Data Privacy, Business Ethics, Risk Management, Applied Statistics

Personal Profile

Dr. Amanda Chu is currently an assistant professor at The Education University of Hong Kong (EdUHK). She received her Ph.D. from The University of Hong Kong, Master’s degree in Business Administration from The Chinese University of Hong Kong, and Bachelor’s degree in Social Sciences (Statistics) from The University of Hong Kong. She is also a certified Financial Risk Manager of Global Association of Risk Professionals (GARP) and a certified Professional Risk Manager of the Professional Risk Managers’ International Association (PRMIA). Her research interests include risk management, health care analytics, and applied statistics. She has papers in journals like Annals of Applied Statistics, Journal of Econometrics, Decision Support Systems, Journal of Business Ethics, Statistical Methods and Medical Research, among others.

Before starting her academic career, Dr. Chu has obtained 10 years of experience in consulting, market research, risk management, and business development. She managed over five government-funded research projects and more than 10 industry collaborative projects with various associations and global companies when she was a consultant in the industry.

Research Interests

Data Privacy, Business Ethics, Risk Management, Applied Statistics

Research Outputs


Journal Publications Chu, A. M. Y., Lam, B. S. Y., Tsang, J. T. Y., Tiwari, A., Chan, J. N. L., So, M. K. P. (2026). Psychosocial Stress in the Chinese Community: Speech Analytics Through Linguistic and Acoustic Fusion Using Machine Learning. JMIR Biomedical Engineering, 11(1), Article e91138. https://doi.org/10.2196/91138 SDGs infomation: 3 - Good Health and Well-Being Chu, A. M. Y., So, H.-y., Yu, L. W. L., Ho, B. P. Y., Chang, S. S. Y., Chan, L. S. H. Or, C. K. L., and So, M. K. P. (2025). Nurses’ knowledge, attitudes, and role perception in medication administration: Do hospital context and nurses’ level of professional experience make a difference?. BMC Nursing, 25, Article 37. https://doi.org/10.1186/s12912-025-04110-9 SDGs infomation: 3 - Good Health and Well-Being Chu, A. M. Y., Omori, Y., So, H-y., & So, M. K. P. (2025). A multivariate randomized response model for mixed-type data. Journal of Applied Statistics, 52(14), 2597-2635. https://doi.org/10.1080/02664763.2025.2480865 Chu, A. M. Y., Tsang, J. T. Y., Chan, S. S. C., Chan, L. S. H., & So, M. K. P. (2025). Utilizing Google Trends data to enhance forecasts and monitor long COVID prevalence.. Communications Medicine, 5, Article 179. https://doi.org/10.1038/s43856-025-00896-6 Chan, L. S. H., Chu, A. M. Y., & So, M. K. P. (2025). A Hybrid Markov Chain Monte Carlo Approach for Structural Learning in Bayesian Networks Based on Variable Blocking. Bayesian Analysis, Advance Publication, 1-27. https://doi.org/10.1214/25-BA1521 Chu, A. M. Y., Kwok, P. W. H., Chan, J. N. L., So, M. K. P. (2024). COVID-19 pandemic risk assessment: Systematic review. Risk Management and Healthcare Policy, 17, 903-925. https://doi.org/10.2147/RMHP.S444494 SDGs infomation: 3 - Good Health and Well-Being So, M. K. P., Chan, T. W. C., and Chu, A. M. Y. (2024). Bayesian systemic risk analysis using latent space network models. Data Science in Science, 3(1), Article 2381724. https://doi.org/10.1080/26941899.2024.2381724 Chu, A. M. Y., Damen, H. Y. Woo, Tiwari, A., Yuk, H., & So, M. K. P. (2024). Which types of family caregivers are more prone to developing depression? Leveraging non-financial social support to mitigate depression. Current Psychology, 44, 73-84. https://doi.org/10.1007/s12144-024-07110-1 Leung, E., Guan, J., Chu, A. M. Y., Ching, S. C. C., Liu, Y., & Chen, F. Y. (2024). The valuation of older adult homecare services under a joint medical-social budgetary perspective. Frontiers in Public Health, 12, Article 1428130. https://doi.org/10.3389/fpubh.2024.1428130 Chu, A. M. Y., Tsang, J. T. Y, Tiwari, A., Yuk, H., & So, M. K. P. (2024). Child-friendly family reduces parenting stress in Chinese families: The mediating role of family resilience. Frontiers in Psychology, 15, Article 1430005. https://doi.org/10.3389/fpsyg.2024.1430005 Asai, M., Chu, A. M. Y., & So, M. K. P. (2024). Dynamic network Poisson autoregression with application to COVID-19 count data. Journal of Data Science, 23(1), 208-224. https://doi.org/10.6339/24-JDS1124 Chu, A. M. Y., Chan, L. S. H., Chang, S. S. Y., Tiwari, A., Yuk, H., and So, M. K. P. (2024). Applications of Bayesian networks in assessing the effects of family resilience on caregiver behavioral problems, depressive symptoms, and burdens. Journal of Computational Social Science, 7, 1275-1303. https://doi.org/10.1007/s42001-024-00270-x Chu, A. M. Y., Kwok, P. W. H., Chan, J. N. L., and So, M. K. P. (2024). COVID-19 Pandemic Risk Assessment: Systematic Review. Risk Management and Healthcare Policy, 17, 903-925. Lam, B. S. Y., Chu, A. M. Y., Chan, J. N. L., and So, M. K. P. (2024). Do Scholars Respond Faster Than Google Trends in Discussing COVID-19 Issues? An Approach to Textual Big Data. Health Data Science, 4, 0116. Lam, B. S. Y., Chu, A. M. Y., Chan, J. N. L., and So, M. K. P. (2024). Do scholars respond faster than Google trends in discussing COVID-19 issues? An approach to textual big data. Health Data Science, 4, Article 0116. https://doi.org/10.34133/hds.0116 SDGs infomation: 3 - Good Health and Well-Being Chu, A. M. Y., Lam, B. S. Y., Tsang, J. T. Y., Tiwari, A., Yuk, H., Chan, J. N. L., and So, M. K. P. (2023). An automatic speech analytics program for digital assessment of stress burden and psychosocial health. npj Mental Health Research, 2, Article 15. https://doi.org/10.1038/s44184-023-00036-9 SDGs infomation: 3 - Good Health and Well-Being So, M. K. P., Mak, A. S. W., Chan, J. N. L., and Chu, A. M. Y. (2023). Standardized local assortativity in networks and systemic risk in financial markets. PLoS ONE, 18(10), e0292327. So, M. K. P., Mak, A. S. W., Chan, J. N. L., and Chu, A. M. Y. (2023). Standardized local assortativity in networks and systemic risk in financial markets. PLoS One, 18(10), Article e0292327. https://doi.org/10.1371/journal.pone.0292327 Chu, A. M. Y., Chong, A. C. Y., Lai, N. H. T., Tiwari, A., and So, M. K. P. (2023). Enhancing the Predictive Power of Google Trends Data Through Network Analysis: Infodemiology Study of COVID-19. JMIR Public Health and Surveillance, 9, e42446. Chu, A. M. Y., Lam, B. S. Y., Tsang J. T. Y., Tiwari, A., Yuk, H., Chan, J. N. L., and So, M. K. P. (2023). An automatic speech analytics program for digital assessment of stress burden and psychosocial health. npj Mental Health Research, 2, 15. Chu, A. M. Y., Omori, Y, So, H., & So, M. K. P. (2023). A multivariate randomized response model for sensitive binary data. Econometrics and Statistics, 27, 16-35. Ho, K. T. H., Kwok, P. W. H., Chang, S. S. Y., & Chu, A. M. Y. (2023). Gaps between attitudes and behavior in the use of disposable plastic tableware (DPT) and factors influencing sustainable DPT consumption: A study of Hong Kong undergraduates. Sustainability, 15(11), 8958. https://doi.org/10.3390/su15118958 So, M. K. P., Chu, A. M. Y. & Tiwari, A. (2023). Interviewer bias when using multiple mini-interviews in selecting student nurses in a Chinese setting. Nurse Education Today, 121, Article 105676. https://doi.org/10.1016/j.nedt.2022.105676 Chan, L. S. H., Chu, A. M. Y., & So, M. K. P. (2023). A moving-window bayesian network model for assessing systemic risk in financial markets. PLoS One, 18(1), Article e0279888. https://doi.org/10.1371/journal.pone.0279888 Chu, A. M. Y., Ip, C. Y., Lam, B. S. Y., & So, M. K. P. (2022). Vine copula statistical disclosure control for mixed-type data. Computational Statistics and Data Analysis, 176, Article 107561. https://doi.org/10.1016/j.csda.2022.107561 So, M. K. P., Chu, A. M. Y., & Tiwari, A. (2022). Persistent symptoms after SARS-CoV-2 infection: Long-term implications for health and quality of life. The Lancet Regional Health - Europe, 100373. https://doi.org/10.1016/j.lanepe.2022.100373 Mumtaz, S., Chu, A. M. Y, Attiq, S., Shah, H. J., & Wong W-K. (2022). Habit—Does It matter? Bringing habit and emotion into the development of consumer’s food waste reduction behavior with the lens of the theory of interpersonal behavior. International Journal of Environmental Research and Public Health, 19(10), 6312. So, M. K. P., Chan, J. N. L., & Chu, A. M. Y. (2022). Dynamic causality analysis of COVID-19 pandemic risk and oil market changes. Journal of Risk and Financial Management, 15(6), 240. So, M. K. P., Yuk, H., Tiwari, A., Cheung, S. T. Y., & Chu, A. M. Y. (2022). Predicting the burden of family caregivers from their individual characteristics. Informatics for Health and Social Care, 47(2), 211-222. So, M. K. P., Chan, T. W. C., Chu, A. M. Y. (2022). Efficient estimation of high-dimensional dynamic covariance by risk factor mapping: Applications for financial risk management. Journal of Econometrics, 227(1), 151-167. So, M. K. P., Chu, A. M. Y., & Tiwari, A. (2022). Persistent symptoms after SARS-CoV-2 infection: Long-term implications for health and quality of life. The Lancet Regional Health–Europe, 17, 100373. Chu, A. M. Y., Tsang, J. T. Y, Tiwari, A., Yuk, H., & So, M. K. P. (2022). Measuring family resilience of Chinese family caregivers: Psychometric evaluation of the family resilience assessment scale. Family Relations, 17(1), 130-146. Chu, A. M. Y., Tsang, J. T. Y., Tiwari, A., Yuk, H., & So, M. K. P. (2022). Measuring family resilience of Chinese family caregivers: Psychometric evaluation of the Family Resilience Assessment Scale. Family Relations, 1(130-146). https://doi.org/10.1111/fare.12601 So, M. K. P., Mak, A. S. W., & Chu, A. M. Y. (2022). Assessing systemic risk in financial markets using dynamic topic networks. Scientific Reports. https://doi.org/10.1038/s41598-022-06399-x So, M. K. P., Mak, A. S. W., & Chu, A. M. Y. (2022). Assessing systemic risk in financial markets using dynamic topic networks. Scientific Reports, 12, 2668. Chu, A. M. Y., Chan, T. W. C., & So, M. K. P. (2022). Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words. PLoS One, 1, e0261969, Article 1178. https://doi.org/10.1371/journal.pone.0261969 Chu, A. M. Y., Chan, T. W. C., & So, M. K. P. (2022). Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words. PLoS ONE, 17(1), e0261969. Attiq, S., Chu, A. M. Y., Azam, R. I., Wong, W. K., & Mumtaz, S. (2021). Antecedents of consumer food waste reduction behavior: Psychological and financial concerns through the lens of the theory of interpersonal behavior. International Journal of Environmental Research and Public Health, 18(23), 12457. Chu, A. M. Y., Ip, C. Y., Lam B. S. Y., & So, M. K. P. (2022). Statistical disclosure control for continuous variables using an extended skew‐t copula. Applied Stochastic Models in Business and Industry, 38(1), 96-115. (2021). Statistical disclosure control for continuous variables using an extended skew‐t copula. Applied Stochastic Models in Business and Industry, 38(1), 96-115. Liu, W. K., So, M. K. P., & Chu, A. M. Y. (2022). (2021). Dynamic covariance modeling with artificial neural networks. Communications in Statistics: Case Studies, Data Analysis and Applications, 8(1), 15-42. Chu, A. M. Y. (2021). Illegal waste dumping under a municipal solid waste charging scheme: Application of the neutralization theory. Sustainability, 13(16), 9279. Tsang, J. T. Y., So, M. K. P., Chong, A. C. Y., Lam, B. S. Y., & Chu, A. M. Y. (2021). Higher education during the pandemic: The predictive factors of learning effectiveness in COVID-19 online learning. Education Sciences, 11(8), 446. Chu, A. M. Y., Chan, L. S. H., & So, M. K. P. (2021). Stochastic actor-oriented modelling of the impact of COVID-19 on financial network evolution. Stat, 10(1), e408. So, M. K. P., Chu, A. M. Y., Lo, C. C. Y., & Ip, C. Y. (2021). DOI: 10.1002/wics.1567. (2021). Volatility and dynamic dependence modeling: Review, applications, and financial risk management. WIREs Computational Statistics, /, e1567. Chu, A. M. Y., Liu, C. K. W., So, M. K. P., and Lam, B. S. Y. (2021). Factors for sustainable online learning in higher education during the COVID-19 pandemic. Sustainability, 13(9), 5038. Chu, A. M. Y., Chan J. N. L, Tsang, J. T. Y., Tiwari, A, So, M. K. P. (2021). Analyzing cross-country pandemic connectedness in COVID-19: Network analysis using a spatial-temporal database. JMIR Public Health and Surveillance, 7(3), e27317. Chu, A. M. Y., Tiwari, A., Chan, J. N. L., So, M. K. P. (2021). Are travel restrictions helpful to control the global COVID-19 outbreak?. Travel Medicine and Infectious Disease, 41, 102021. Lv, Z, Chu, A. M. Y, Wong, W. K., Chiang, T. C. (2021). The maximum-return-and-minimum-volatility effect: evidence from choosing risky and riskless assets to form a portfolio. Risk Management, 23(1), 97-122. So, M. K. P., Chu, A. M. Y., Tiwari, A, Chan, J. N. L. (2021). On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics. Scientific Reports, 11(1), 5112. Tiwari, A., So, M. K. P., Chong, A. C. Y., Chan, J. N. L., Chu, A. M. Y. (2021). Pandemic risk of COVID-19 outbreak in the United States: an analysis of network connectedness with air travel data. International Journal of Infectious Diseases, 103, 97-101. Chu, A. M. Y., Chan, T. W. C., So, M. K. P., Wong, W. K. (2021). Dynamic network analysis of COVID-19 with a latent pandemic space model. International Journal of Environmental Research and Public Health, 18(6), 3195. So, M. K. P., Chu, A. M. Y., Chan, T. W. C. (2021). Impacts of the COVID-19 pandemic on financial market connectedness. Finance Research Letters, 38, 101864. Chu, A. M. Y., Tsang, J. T. Y., Chan, J. N. L., Tiwari, A., So, M. K. P. (2020). Analysis of travel restrictions for COVID-19 control in Latin America through network connectedness.. Journal of Travel Medicine, 27(8), taaa176. So, M. K. P., Tiwari, A., Chu, A. M. Y., Tsang, J. T. Y., Chan, J. N. L. (2020). Visualizing COVID-19 pandemic risk through network connectedness. International Journal of Infectious Diseases, 96, 558-561. Chu, A. M. Y., Tiwari, A, So, M. K. P. (2020). Detecting early signals of COVID-19 global pandemic from network density. Journal of Travel Medicine, 27(5), taaa084. Chu, A. M. Y. and So, M. K. P. (2020). Organizational Information Security Management for Sustainable Information Systems: An Unethical Employee Information Security Behavior Perspective. Sustainability, 12(8), 3163. Chung, R. S. W., So, M. K. P., Chu, A. M. Y. & Chan, T. W. C. (2020). Regularization of Bayesian Quasi-likelihoods Constructed from Complex Estimating Functions. Computational Statistics & Data Analysis, 150, 106977. Lam, B. S. Y., Chu, A. M. Y. & Yan, H. (2020). Statistical Bootstrap-based Principal Mode Component Analysis for Dynamic Background Subtraction. Pattern Recognition, 100, 117153. Chu, A. M. Y., Lv, Z., Wagner, N. F. & Wong, W. K. (2020). Linear and Nonlinear Growth Determinants: The Case of Mongolia and Its Connection to China. Emerging Markets Review, 43, 100693. Chu, A. M. Y., So, M. K. P., Chan, T. W. C. & Tiwari, A. (2020). Estimating the Dependence of Mixed Sensitive Response Types in Randomized Response Technique. Statistical Methods in Medical Research, 29(3), 894-910. Chu, A. M. Y., Lam, B. S. Y., Tiwari, A., So, M. K. P. (2019). An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health Research. International Journal of Environmental Research and Public Health, 16(22), 4519. Lv, Z., Chu, A. M. Y., McAleer, M. & Wong, W. K. (2019). Modelling Economic Growth, Carbon Emissions, and Fossil Fuel Consumption in China: Cointegration and Multivariate Causality. International Journal of Environmental Research and Public Health, 16(21), 4176. Chong, A. C. Y., Chu, A. M. Y., So, M. K. P. & Chung R. S. W. (2019). Asking Sensitive Questions Using the Randomized Response Approach in Public Health Research: An Empirical Study on the Factors of Illegal Waste Disposal. International Journal of Environmental Research and Public Health, 16(6), 970. So, M. K. P., Liu, W. K. & Chu, A. M. Y. (2018). Bayesian Shrinkage Estimation of Time-varying Covariance Matrices in Financial Time Series. Advances in Decision Sciences, 22(A), 1-35. Chung, R. S. W., Chu, A. M. Y., & So, M. K. P. (2018). Bayesian Randomized Response Technique with Multiple Sensitive Attributes: The Case of Information Systems Resource Misuse. The Annals of Applied Statistics, 12(3), 1969-1992. Chu, A. M. Y., Li, R. W. M., & So, M. K. P. (2018). Bayesian Spatio-temporal Modeling of Air Pollution Data with Dynamic Variance and Leptokurtosis. Spatial Statistics, 26, 1-20. Chu, A. M. Y., So, M. K. P., & Chung, R. S. W. (2018). Applying the Randomized Response Technique in Business Ethics Research: The Misuse of Information Systems Resources in the Workplace. Journal of Business Ethics, 151(1), 195-212.

Journal Publications
Chu, A. M. Y., Lam, B. S. Y., Tsang, J. T. Y., Tiwari, A., Chan, J. N. L., So, M. K. P. (2026). Psychosocial Stress in the Chinese Community: Speech Analytics Through Linguistic and Acoustic Fusion Using Machine Learning. JMIR Biomedical Engineering, 11(1), Article e91138. https://doi.org/10.2196/91138
SDGs infomation: 3 - Good Health and Well-Being
Chu, A. M. Y., So, H.-y., Yu, L. W. L., Ho, B. P. Y., Chang, S. S. Y., Chan, L. S. H. Or, C. K. L., and So, M. K. P. (2025). Nurses’ knowledge, attitudes, and role perception in medication administration: Do hospital context and nurses’ level of professional experience make a difference?. BMC Nursing, 25, Article 37. https://doi.org/10.1186/s12912-025-04110-9
SDGs infomation: 3 - Good Health and Well-Being
Chu, A. M. Y., Omori, Y., So, H-y., & So, M. K. P. (2025). A multivariate randomized response model for mixed-type data. Journal of Applied Statistics, 52(14), 2597-2635. https://doi.org/10.1080/02664763.2025.2480865
Chu, A. M. Y., Tsang, J. T. Y., Chan, S. S. C., Chan, L. S. H., & So, M. K. P. (2025). Utilizing Google Trends data to enhance forecasts and monitor long COVID prevalence.. Communications Medicine, 5, Article 179. https://doi.org/10.1038/s43856-025-00896-6
Chan, L. S. H., Chu, A. M. Y., & So, M. K. P. (2025). A Hybrid Markov Chain Monte Carlo Approach for Structural Learning in Bayesian Networks Based on Variable Blocking. Bayesian Analysis, Advance Publication, 1-27. https://doi.org/10.1214/25-BA1521
Chu, A. M. Y., Kwok, P. W. H., Chan, J. N. L., So, M. K. P. (2024). COVID-19 pandemic risk assessment: Systematic review. Risk Management and Healthcare Policy, 17, 903-925. https://doi.org/10.2147/RMHP.S444494
SDGs infomation: 3 - Good Health and Well-Being
So, M. K. P., Chan, T. W. C., and Chu, A. M. Y. (2024). Bayesian systemic risk analysis using latent space network models. Data Science in Science, 3(1), Article 2381724. https://doi.org/10.1080/26941899.2024.2381724
Chu, A. M. Y., Damen, H. Y. Woo, Tiwari, A., Yuk, H., & So, M. K. P. (2024). Which types of family caregivers are more prone to developing depression? Leveraging non-financial social support to mitigate depression. Current Psychology, 44, 73-84. https://doi.org/10.1007/s12144-024-07110-1
Leung, E., Guan, J., Chu, A. M. Y., Ching, S. C. C., Liu, Y., & Chen, F. Y. (2024). The valuation of older adult homecare services under a joint medical-social budgetary perspective. Frontiers in Public Health, 12, Article 1428130. https://doi.org/10.3389/fpubh.2024.1428130
Chu, A. M. Y., Tsang, J. T. Y, Tiwari, A., Yuk, H., & So, M. K. P. (2024). Child-friendly family reduces parenting stress in Chinese families: The mediating role of family resilience. Frontiers in Psychology, 15, Article 1430005. https://doi.org/10.3389/fpsyg.2024.1430005
Asai, M., Chu, A. M. Y., & So, M. K. P. (2024). Dynamic network Poisson autoregression with application to COVID-19 count data. Journal of Data Science, 23(1), 208-224. https://doi.org/10.6339/24-JDS1124
Chu, A. M. Y., Chan, L. S. H., Chang, S. S. Y., Tiwari, A., Yuk, H., and So, M. K. P. (2024). Applications of Bayesian networks in assessing the effects of family resilience on caregiver behavioral problems, depressive symptoms, and burdens. Journal of Computational Social Science, 7, 1275-1303. https://doi.org/10.1007/s42001-024-00270-x
Chu, A. M. Y., Kwok, P. W. H., Chan, J. N. L., and So, M. K. P. (2024). COVID-19 Pandemic Risk Assessment: Systematic Review. Risk Management and Healthcare Policy, 17, 903-925.
Lam, B. S. Y., Chu, A. M. Y., Chan, J. N. L., and So, M. K. P. (2024). Do Scholars Respond Faster Than Google Trends in Discussing COVID-19 Issues? An Approach to Textual Big Data. Health Data Science, 4, 0116.
Lam, B. S. Y., Chu, A. M. Y., Chan, J. N. L., and So, M. K. P. (2024). Do scholars respond faster than Google trends in discussing COVID-19 issues? An approach to textual big data. Health Data Science, 4, Article 0116. https://doi.org/10.34133/hds.0116
SDGs infomation: 3 - Good Health and Well-Being
Chu, A. M. Y., Lam, B. S. Y., Tsang, J. T. Y., Tiwari, A., Yuk, H., Chan, J. N. L., and So, M. K. P. (2023). An automatic speech analytics program for digital assessment of stress burden and psychosocial health. npj Mental Health Research, 2, Article 15. https://doi.org/10.1038/s44184-023-00036-9
SDGs infomation: 3 - Good Health and Well-Being
So, M. K. P., Mak, A. S. W., Chan, J. N. L., and Chu, A. M. Y. (2023). Standardized local assortativity in networks and systemic risk in financial markets. PLoS ONE, 18(10), e0292327.
So, M. K. P., Mak, A. S. W., Chan, J. N. L., and Chu, A. M. Y. (2023). Standardized local assortativity in networks and systemic risk in financial markets. PLoS One, 18(10), Article e0292327. https://doi.org/10.1371/journal.pone.0292327
Chu, A. M. Y., Chong, A. C. Y., Lai, N. H. T., Tiwari, A., and So, M. K. P. (2023). Enhancing the Predictive Power of Google Trends Data Through Network Analysis: Infodemiology Study of COVID-19. JMIR Public Health and Surveillance, 9, e42446.
Chu, A. M. Y., Lam, B. S. Y., Tsang J. T. Y., Tiwari, A., Yuk, H., Chan, J. N. L., and So, M. K. P. (2023). An automatic speech analytics program for digital assessment of stress burden and psychosocial health. npj Mental Health Research, 2, 15.
Chu, A. M. Y., Omori, Y, So, H., & So, M. K. P. (2023). A multivariate randomized response model for sensitive binary data. Econometrics and Statistics, 27, 16-35.
Ho, K. T. H., Kwok, P. W. H., Chang, S. S. Y., & Chu, A. M. Y. (2023). Gaps between attitudes and behavior in the use of disposable plastic tableware (DPT) and factors influencing sustainable DPT consumption: A study of Hong Kong undergraduates. Sustainability, 15(11), 8958. https://doi.org/10.3390/su15118958
So, M. K. P., Chu, A. M. Y. & Tiwari, A. (2023). Interviewer bias when using multiple mini-interviews in selecting student nurses in a Chinese setting. Nurse Education Today, 121, Article 105676. https://doi.org/10.1016/j.nedt.2022.105676
Chan, L. S. H., Chu, A. M. Y., & So, M. K. P. (2023). A moving-window bayesian network model for assessing systemic risk in financial markets. PLoS One, 18(1), Article e0279888. https://doi.org/10.1371/journal.pone.0279888
Chu, A. M. Y., Ip, C. Y., Lam, B. S. Y., & So, M. K. P. (2022). Vine copula statistical disclosure control for mixed-type data. Computational Statistics and Data Analysis, 176, Article 107561. https://doi.org/10.1016/j.csda.2022.107561
So, M. K. P., Chu, A. M. Y., & Tiwari, A. (2022). Persistent symptoms after SARS-CoV-2 infection: Long-term implications for health and quality of life. The Lancet Regional Health - Europe, 100373. https://doi.org/10.1016/j.lanepe.2022.100373
Mumtaz, S., Chu, A. M. Y, Attiq, S., Shah, H. J., & Wong W-K. (2022). Habit—Does It matter? Bringing habit and emotion into the development of consumer’s food waste reduction behavior with the lens of the theory of interpersonal behavior. International Journal of Environmental Research and Public Health, 19(10), 6312.
So, M. K. P., Chan, J. N. L., & Chu, A. M. Y. (2022). Dynamic causality analysis of COVID-19 pandemic risk and oil market changes. Journal of Risk and Financial Management, 15(6), 240.
So, M. K. P., Yuk, H., Tiwari, A., Cheung, S. T. Y., & Chu, A. M. Y. (2022). Predicting the burden of family caregivers from their individual characteristics. Informatics for Health and Social Care, 47(2), 211-222.
So, M. K. P., Chan, T. W. C., Chu, A. M. Y. (2022). Efficient estimation of high-dimensional dynamic covariance by risk factor mapping: Applications for financial risk management. Journal of Econometrics, 227(1), 151-167.
So, M. K. P., Chu, A. M. Y., & Tiwari, A. (2022). Persistent symptoms after SARS-CoV-2 infection: Long-term implications for health and quality of life. The Lancet Regional Health–Europe, 17, 100373.
Chu, A. M. Y., Tsang, J. T. Y, Tiwari, A., Yuk, H., & So, M. K. P. (2022). Measuring family resilience of Chinese family caregivers: Psychometric evaluation of the family resilience assessment scale. Family Relations, 17(1), 130-146.
Chu, A. M. Y., Tsang, J. T. Y., Tiwari, A., Yuk, H., & So, M. K. P. (2022). Measuring family resilience of Chinese family caregivers: Psychometric evaluation of the Family Resilience Assessment Scale. Family Relations, 1(130-146). https://doi.org/10.1111/fare.12601
So, M. K. P., Mak, A. S. W., & Chu, A. M. Y. (2022). Assessing systemic risk in financial markets using dynamic topic networks. Scientific Reports. https://doi.org/10.1038/s41598-022-06399-x
So, M. K. P., Mak, A. S. W., & Chu, A. M. Y. (2022). Assessing systemic risk in financial markets using dynamic topic networks. Scientific Reports, 12, 2668.
Chu, A. M. Y., Chan, T. W. C., & So, M. K. P. (2022). Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words. PLoS One, 1, e0261969, Article 1178. https://doi.org/10.1371/journal.pone.0261969
Chu, A. M. Y., Chan, T. W. C., & So, M. K. P. (2022). Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words. PLoS ONE, 17(1), e0261969.
Attiq, S., Chu, A. M. Y., Azam, R. I., Wong, W. K., & Mumtaz, S. (2021). Antecedents of consumer food waste reduction behavior: Psychological and financial concerns through the lens of the theory of interpersonal behavior. International Journal of Environmental Research and Public Health, 18(23), 12457.
Chu, A. M. Y., Ip, C. Y., Lam B. S. Y., & So, M. K. P. (2022). Statistical disclosure control for continuous variables using an extended skew‐t copula. Applied Stochastic Models in Business and Industry, 38(1), 96-115. (2021). Statistical disclosure control for continuous variables using an extended skew‐t copula. Applied Stochastic Models in Business and Industry, 38(1), 96-115.
Liu, W. K., So, M. K. P., & Chu, A. M. Y. (2022). (2021). Dynamic covariance modeling with artificial neural networks. Communications in Statistics: Case Studies, Data Analysis and Applications, 8(1), 15-42.
Chu, A. M. Y. (2021). Illegal waste dumping under a municipal solid waste charging scheme: Application of the neutralization theory. Sustainability, 13(16), 9279.
Tsang, J. T. Y., So, M. K. P., Chong, A. C. Y., Lam, B. S. Y., & Chu, A. M. Y. (2021). Higher education during the pandemic: The predictive factors of learning effectiveness in COVID-19 online learning. Education Sciences, 11(8), 446.
Chu, A. M. Y., Chan, L. S. H., & So, M. K. P. (2021). Stochastic actor-oriented modelling of the impact of COVID-19 on financial network evolution. Stat, 10(1), e408.
So, M. K. P., Chu, A. M. Y., Lo, C. C. Y., & Ip, C. Y. (2021). DOI: 10.1002/wics.1567. (2021). Volatility and dynamic dependence modeling: Review, applications, and financial risk management. WIREs Computational Statistics, /, e1567.
Chu, A. M. Y., Liu, C. K. W., So, M. K. P., and Lam, B. S. Y. (2021). Factors for sustainable online learning in higher education during the COVID-19 pandemic. Sustainability, 13(9), 5038.
Chu, A. M. Y., Chan J. N. L, Tsang, J. T. Y., Tiwari, A, So, M. K. P. (2021). Analyzing cross-country pandemic connectedness in COVID-19: Network analysis using a spatial-temporal database. JMIR Public Health and Surveillance, 7(3), e27317.
Chu, A. M. Y., Tiwari, A., Chan, J. N. L., So, M. K. P. (2021). Are travel restrictions helpful to control the global COVID-19 outbreak?. Travel Medicine and Infectious Disease, 41, 102021.
Lv, Z, Chu, A. M. Y, Wong, W. K., Chiang, T. C. (2021). The maximum-return-and-minimum-volatility effect: evidence from choosing risky and riskless assets to form a portfolio. Risk Management, 23(1), 97-122.
So, M. K. P., Chu, A. M. Y., Tiwari, A, Chan, J. N. L. (2021). On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics. Scientific Reports, 11(1), 5112.
Tiwari, A., So, M. K. P., Chong, A. C. Y., Chan, J. N. L., Chu, A. M. Y. (2021). Pandemic risk of COVID-19 outbreak in the United States: an analysis of network connectedness with air travel data. International Journal of Infectious Diseases, 103, 97-101.
Chu, A. M. Y., Chan, T. W. C., So, M. K. P., Wong, W. K. (2021). Dynamic network analysis of COVID-19 with a latent pandemic space model. International Journal of Environmental Research and Public Health, 18(6), 3195.
So, M. K. P., Chu, A. M. Y., Chan, T. W. C. (2021). Impacts of the COVID-19 pandemic on financial market connectedness. Finance Research Letters, 38, 101864.
Chu, A. M. Y., Tsang, J. T. Y., Chan, J. N. L., Tiwari, A., So, M. K. P. (2020). Analysis of travel restrictions for COVID-19 control in Latin America through network connectedness.. Journal of Travel Medicine, 27(8), taaa176.
So, M. K. P., Tiwari, A., Chu, A. M. Y., Tsang, J. T. Y., Chan, J. N. L. (2020). Visualizing COVID-19 pandemic risk through network connectedness. International Journal of Infectious Diseases, 96, 558-561.
Chu, A. M. Y., Tiwari, A, So, M. K. P. (2020). Detecting early signals of COVID-19 global pandemic from network density. Journal of Travel Medicine, 27(5), taaa084.
Chu, A. M. Y. and So, M. K. P. (2020). Organizational Information Security Management for Sustainable Information Systems: An Unethical Employee Information Security Behavior Perspective. Sustainability, 12(8), 3163.
Chung, R. S. W., So, M. K. P., Chu, A. M. Y. & Chan, T. W. C. (2020). Regularization of Bayesian Quasi-likelihoods Constructed from Complex Estimating Functions. Computational Statistics & Data Analysis, 150, 106977.
Lam, B. S. Y., Chu, A. M. Y. & Yan, H. (2020). Statistical Bootstrap-based Principal Mode Component Analysis for Dynamic Background Subtraction. Pattern Recognition, 100, 117153.
Chu, A. M. Y., Lv, Z., Wagner, N. F. & Wong, W. K. (2020). Linear and Nonlinear Growth Determinants: The Case of Mongolia and Its Connection to China. Emerging Markets Review, 43, 100693.
Chu, A. M. Y., So, M. K. P., Chan, T. W. C. & Tiwari, A. (2020). Estimating the Dependence of Mixed Sensitive Response Types in Randomized Response Technique. Statistical Methods in Medical Research, 29(3), 894-910.
Chu, A. M. Y., Lam, B. S. Y., Tiwari, A., So, M. K. P. (2019). An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health Research. International Journal of Environmental Research and Public Health, 16(22), 4519.
Lv, Z., Chu, A. M. Y., McAleer, M. & Wong, W. K. (2019). Modelling Economic Growth, Carbon Emissions, and Fossil Fuel Consumption in China: Cointegration and Multivariate Causality. International Journal of Environmental Research and Public Health, 16(21), 4176.
Chong, A. C. Y., Chu, A. M. Y., So, M. K. P. & Chung R. S. W. (2019). Asking Sensitive Questions Using the Randomized Response Approach in Public Health Research: An Empirical Study on the Factors of Illegal Waste Disposal. International Journal of Environmental Research and Public Health, 16(6), 970.
So, M. K. P., Liu, W. K. & Chu, A. M. Y. (2018). Bayesian Shrinkage Estimation of Time-varying Covariance Matrices in Financial Time Series. Advances in Decision Sciences, 22(A), 1-35.
Chung, R. S. W., Chu, A. M. Y., & So, M. K. P. (2018). Bayesian Randomized Response Technique with Multiple Sensitive Attributes: The Case of Information Systems Resource Misuse. The Annals of Applied Statistics, 12(3), 1969-1992.
Chu, A. M. Y., Li, R. W. M., & So, M. K. P. (2018). Bayesian Spatio-temporal Modeling of Air Pollution Data with Dynamic Variance and Leptokurtosis. Spatial Statistics, 26, 1-20.
Chu, A. M. Y., So, M. K. P., & Chung, R. S. W. (2018). Applying the Randomized Response Technique in Business Ethics Research: The Misuse of Information Systems Resources in the Workplace. Journal of Business Ethics, 151(1), 195-212.