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Menglan Pang
Menglan Pang
Biogen
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Cited by
Cited by
Year
Studying noncollapsibility of the odds ratio with marginal structural and logistic regression models
M Pang, JS Kaufman, RW Platt
Statistical methods in medical research 25 (5), 1925-1937, 2016
1002016
Can we train machine learning methods to outperform the high-dimensional propensity score algorithm?
ME Karim, M Pang, RW Platt
Epidemiology 29 (2), 191-198, 2018
452018
Confounding, effect modification and the odds ratio: common misinterpretations
I Shrier, M Pang
Journal of clinical epidemiology 68 (4), 470, 2015
392015
Targeted maximum likelihood estimation for pharmacoepidemiologic research
M Pang, T Schuster, KB Filion, M Eberg, RW Platt
Epidemiology 27 (4), 570-577, 2016
292016
Comparative effectiveness and safety of direct oral anticoagulants versus vitamin K antagonists in nonvalvular atrial fibrillation: a Canadian multicentre observational cohort …
M Durand, ME Schnitzer, M Pang, G Carney, S Eltonsy, KB Filion, ...
Canadian Medical Association Open Access Journal 8 (4), E877-E886, 2020
222020
Effect estimation in point-exposure studies with binary outcomes and high-dimensional covariate data–a comparison of targeted maximum likelihood estimation and inverse …
M Pang, T Schuster, KB Filion, ME Schnitzer, M Eberg, RW Platt
The international journal of biostatistics 12 (2), 20150034, 2016
192016
On the role of marginal confounder prevalence–implications for the high‐dimensional propensity score algorithm
T Schuster, M Pang, RW Platt
Pharmacoepidemiology and drug safety 24 (9), 1004-1007, 2015
172015
Flexible extension of the accelerated failure time model to account for nonlinear and time-dependent effects of covariates on the hazard
M Pang, RW Platt, T Schuster, M Abrahamowicz
Statistical Methods in Medical Research 30 (11), 2526-2542, 2021
142021
Spline‐based accelerated failure time model
M Pang, RW Platt, T Schuster, M Abrahamowicz
Statistics in medicine 40 (2), 481-497, 2021
112021
Effectiveness and safety among direct oral anticoagulants in nonvalvular atrial fibrillation: A multi‐database cohort study with meta‐analysis
M Durand, ME Schnitzer, M Pang, G Carney, S Eltonsy, KB Filion, ...
British Journal of Clinical Pharmacology 87 (6), 2589-2601, 2021
102021
Psychometric properties of the Alzheimer’s Disease Cooperative Study–Activities of Daily Living for Mild Cognitive Impairment (ADCS-MCI-ADL) scale: a post hoc analysis of the …
M Potashman, M Pang, M Tahir, S Shahraz, S Dichter, R Perneczky, ...
BMC geriatrics 23 (1), 124, 2023
92023
Effect of reduction in brain amyloid levels on change in cognitive and functional decline in randomized clinical trials: an instrumental variable meta‐analysis
M Pang, L Zhu, A Gabelle, AR Gafson, RW Platt, JE Galvin, ...
Alzheimer's & Dementia 19 (4), 1292-1299, 2023
72023
Graphic report of the results from propensity score method analyses
I Shrier, M Pang, RW Platt
Journal of clinical epidemiology 88, 154-159, 2017
72017
Mixing of confounding and non-collapsibility: a notable deficiency of the odds ratio
M Pang, JS Kaufman, RW Platt
American Journal of Cardiology 111 (2), 302-303, 2013
72013
Confounding of incidence density ratio in case-control studies
S Greenland
Epidemiology 24 (4), 624-625, 2013
42013
Evaluating hybrid controls methodology in early‐phase oncology trials: A simulation study based on the MORPHEUS‐UC trial
G Wang, M Poulin‐Costello, H Pang, J Zhu, HJ Helms, I Reyes‐Rivera, ...
Pharmaceutical Statistics 23 (1), 31-45, 2024
32024
“Translating” All-Cause Mortality Rate Ratios or Hazard Ratios to Age-, Longevity-, and Probability-Based Measures
M Pang, JA Hanley
American Journal of Epidemiology 190 (12), 2664-2670, 2021
32021
Confounding of incidence density ratio in case-control studies
M Pang, T Schuster
Epidemiology 24 (4), 625-627, 2013
32013
Precision medicine analysis of heterogeneity in individual‐level treatment response to amyloid beta removal in early Alzheimer's disease
M Pang, A Gabelle, P Saha‐Chaudhuri, W Huijbers, A Gafson, ...
Alzheimer's & Dementia 20 (2), 1102-1111, 2024
22024
Bootstrapping the Cross-Validation Estimate
B Cai, F Pellegrini, M Pang, C de Moor, C Shen, V Charu, L Tian
arXiv preprint arXiv:2307.00260, 2023
22023
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