Research

Yin Bun’s current research areas include:

(a) Infection and nutrition in children in low-and-middle-income countries.

(b) Statistical methods for analysis of censored data, recurrent events, and zero-inflation.

(c) Study designs in vaccine and infectious disease research.

(d) Quantification of cognition, health utility and quality of life. 

 

Current / recent grants

Design and analysis methods for the evaluation of effectiveness of vaccines and chemoprevention against infectious diseases, National Medical Research Council, Singapore, 2017

Development and validation of a quality of life measurement scale in English and Chinese for caregivers of people living with dementia in Singapore, Lien Center for Palliative Care, 2019

Study designs and analytic methods for improving the evaluation of vaccines and other preventive measures against infectious diseases by using within-unit comparison, National Medical Research Council, Singapore, 2021

 

Publications

Cheung YB in PubMed

Cheung YB. Statistical Analysis of Human Growth and Development. Boca Raton, FL: CRC Press, 2014.

Machin D, Cheung YB, Parmar MKB. Survival Analysis: A Practical Approach, 2nd edn. Chichester: Wiley, 2006.

 

Questionnaires

Singapore Caregiver Quality of Life Scale (Cheung et al., Health Qual Life Outcomes, 2019)

The questionnaires and Stata program are distributed free of charge by the study’s co-funder, Lien Center for Palliative Care, after submitting an online request form.

– SCQOLS Request Form

10- and 15-item short forms of the Singapore Caregiver Quality of Life Scale (SCQOLS-10 and SCQOLS-15)  (Cheung et al., J Clin Epidemiol, 2020)

The questionnaires and Stata program are distributed free of charge by the study’s co-funder, Lien Center for Palliative Care, after submitting an online request form.

SCQOLS-10 and SCQOLS-15 Request Form

Singapore Caregiver Quality of Life Scale – Dementia and its short form (SCQOLS-D and SCQOLS-D-15) (Lee et al. J Patient-Rep Outcomes

SCQOLS-D and SCQOLS-D-15 Request Form

Quick-FLIC: Abbreviated version of Functional Living Index – Cancer (Cheung et al.,Br J Cancer, 2004, 2005)

– Quick-FLIC

 

Software codes

Stata codes used in Statistical Analysis of Human Growth and Development(Cheung, CRC Press, 2014)

– Human_Growth_and_Development_Appendices

Stata codes for Chinese MMSE standards (Cheung et al., Am J Geriatr Psychiatry, 2015)

– MMSE

Stata codes for analysis of fold-increase based on interval-censored data (Xu et al., J Biopharm Stat 2015)

– fold_increase

SAS macro for analysis of zero-inflated bivariate interval-censored data (Xu et al.,Stat Med, 2015)

– zero_inflate_fold_increase

R codes for inverse-variance weighted estimation using multiple dilution data (Cheung et al., J Immunol Methods, 2015)

– MulDiLv01

– Supplementary_note 

Stata codes for inverse-variance weighted estimation using multiple dilution data (Stata Journal 2016; 16(2):316-330)

– Installation in Stata: net describe st0434, from(http://www.stata-journal.com/software/sj16-2)

Stata codes for sample size determination for fold-increase analysis (Xu et al., J Biopharm Stat 2016)

– fold-increase_sampsi

R codes for 4-parameter models for estimating time-varying treatment effect (Xu et al., Stat Med 2017; Ma et al. J Biopharm Stat 2022)

NonLinear 

Stata codes for Mean Rank Method of mapping X to Y (Wee et al. Med Decis Making 2018; Cheung et al., Qual Life Res, 2019)

– MRM

Stata macro for analysis of recurrent events (Stata Journal 2018; 18(2): 477-484)

– Installation in Stata: net describe st0374, from(http://www.stata-journal.com/software/sj15-1)

R codes for bias reduction in conditional logistic regression (Cheung et al., Int J epidemiol 2019)

– MDS2

Stata codes for analysis of fold-increase, with covariate adjustment (Cheung et al.,Stat Biopharm Res 2019)

foldincrease_covar_adjust

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