Lifeng Lin
Lifeng Lin
Assistant Professor of Statistics, Florida State University
Verified email at stat.fsu.edu
Title
Cited by
Cited by
Year
Quantifying publication bias in meta‐analysis
L Lin, H Chu
Biometrics 74 (3), 785-794, 2018
852018
The effect of publication bias magnitude and direction on the certainty in evidence
MH Murad, H Chu, L Lin, Z Wang
BMJ evidence-based medicine 23 (3), 84-86, 2018
412018
Performing arm-based network meta-analysis in R with the pcnetmeta package
L Lin, J Zhang, JS Hodges, H Chu
Journal of statistical software 80, 2017
412017
Empirical comparison of publication bias tests in meta-analysis
L Lin, H Chu, MH Murad, C Hong, Z Qu, SR Cole, Y Chen
Journal of general internal medicine 33 (8), 1260-1267, 2018
362018
Bias caused by sampling error in meta-analysis with small sample sizes
L Lin
PloS one 13 (9), e0204056, 2018
342018
An adaptive two-sample test for high-dimensional means
G Xu, L Lin, P Wei, W Pan
Biometrika 103 (3), 609-624, 2016
312016
The trim-and-fill method for publication bias: practical guidelines and recommendations based on a large database of meta-analyses
L Shi, L Lin
Medicine 98 (23), 2019
292019
Alternative measures of between‐study heterogeneity in meta‐analysis: reducing the impact of outlying studies
L Lin, H Chu, JS Hodges
Biometrics 73 (1), 156-166, 2017
242017
Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google. com
K Kalyanam, J McAteer, J Marek, J Hodges, L Lin
Quantitative Marketing and Economics 16 (1), 1-42, 2018
172018
Sensitivity to excluding treatments in network meta-analysis
L Lin, H Chu, JS Hodges
Epidemiology (Cambridge, Mass.) 27 (4), 562, 2016
132016
Performance of between-study heterogeneity measures in the Cochrane library
X Ma, L Lin, Z Qu, M Zhu, H Chu
Epidemiology (Cambridge, Mass.) 29 (6), 821, 2018
102018
When continuous outcomes are measured using different scales: guide for meta-analysis and interpretation
MH Murad, Z Wang, H Chu, L Lin
bmj 364, 2019
92019
P value–driven methods were underpowered to detect publication bias: analysis of Cochrane review meta-analyses
L Furuya-Kanamori, C Xu, L Lin, T Doan, H Chu, L Thalib, SAR Doi
Journal of clinical epidemiology 118, 86-92, 2020
72020
Graphical augmentations to sample‐size‐based funnel plot in meta‐analysis
L Lin
Research synthesis methods 10 (3), 376-388, 2019
62019
Borrowing of strength from indirect evidence in 40 network meta-analyses
L Lin, A Xing, MJ Kofler, MH Murad
Journal of clinical epidemiology 106, 41-49, 2019
62019
Comparison of four heterogeneity measures for meta‐analysis
L Lin
Journal of evaluation in clinical practice 26 (1), 376-384, 2020
52020
Real-world performance of meta-analysis methods for double-zero-event studies with dichotomous outcomes using the Cochrane Database of Systematic Reviews
Y Ren, L Lin, Q Lian, H Zou, H Chu
Journal of general internal medicine 34 (6), 960-968, 2019
52019
The magnitude of small-study effects in the Cochrane Database of Systematic Reviews: an empirical study of nearly 30 000 meta-analyses
L Lin, L Shi, H Chu, MH Murad
BMJ evidence-based medicine 25 (1), 27-32, 2020
42020
Comparison between PD-1/PD-L1 inhibitors (nivolumab, pembrolizumab, and atezolizumab) in pre-treated NSCLC patients: evidence from a Bayesian network model
Y Wu, L Lin, Y Shen, H Wu
Int J Cancer 143 (11), 3038-3040, 2018
42018
Bayesian multivariate meta‐analysis of multiple factors
L Lin, H Chu
Research synthesis methods 9 (2), 261-272, 2018
42018
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Articles 1–20