Guanghan F Liu
Overview
Explore the profile of Guanghan F Liu including associated specialties, affiliations and a list of published articles.
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Articles
14
Citations
152
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0
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Recent Articles
1.
Tan X, Wang W, Zeng D, Liu G, Diao G, Jafari N, et al.
Stat Med
. 2024 Jan;
43(7):1397-1418.
PMID: 38297431
Postmarket drug safety database like vaccine adverse event reporting system (VAERS) collect thousands of spontaneous reports annually, with each report recording occurrences of any adverse events (AEs) and use of...
2.
Diao G, Liu G, Zeng D, Zhang Y, Golm G, Heyse J, et al.
Stat Biopharm Res
. 2022 May;
14(2):153-161.
PMID: 35601027
Missing data are commonly encountered in clinical trials due to dropout or nonadherence to study procedures. In trials in which recurrent events are of interest, the observed count can be...
3.
Jia B, Zeng D, Liao J, Liu G, Tan X, Diao G, et al.
Lifetime Data Anal
. 2022 Apr;
28(3):356-379.
PMID: 35486260
In oncology studies, it is important to understand and characterize disease heterogeneity among patients so that patients can be classified into different risk groups and one can identify high-risk patients...
4.
Jia B, Zeng D, Liao J, Liu G, Tan X, Diao G, et al.
Stat Med
. 2021 Apr;
40(13):3181-3195.
PMID: 33819928
In cancer studies, it is important to understand disease heterogeneity among patients so that precision medicine can particularly target high-risk patients at the right time. Many feature variables such as...
5.
Tan X, Liu G, Zeng D, Wang W, Diao G, Heyse J, et al.
Stat Med
. 2019 Jul;
38(22):4378-4389.
PMID: 31313376
Analyzing safety data from clinical trials to detect safety signals worth further examination involves testing multiple hypotheses, one for each observed adverse event (AE) type. There exists certain hierarchical structure...
6.
Diao G, Liu G, Zeng D, Wang W, Tan X, Heyse J, et al.
Biometrics
. 2019 Jan;
75(3):1000-1008.
PMID: 30690717
It is an important and yet challenging task to identify true signals from many adverse events that may be reported during the course of a clinical trial. One unique feature...
7.
Gao F, Liu G, Zeng D, Xu L, Lin B, Diao G, et al.
Pharm Stat
. 2017 Aug;
16(6):424-432.
PMID: 28834175
In clinical trials, missing data commonly arise through nonadherence to the randomized treatment or to study procedure. For trials in which recurrent event endpoints are of interests, conventional analyses using...
8.
Ibrahim J, Chen M, Lakshminarayanan M, Liu G, Heyse J
Stat Med
. 2014 Oct;
34(2):249-64.
PMID: 25339499
Developing sophisticated statistical methods for go/no-go decisions is crucial for clinical trials, as planning phase III or phase IV trials is costly and time consuming. In this paper, we develop...
9.
Liu G
Pharm Stat
. 2012 Feb;
11(2):163-9.
PMID: 22337507
Proportion differences are often used to estimate and test treatment effects in clinical trials with binary outcomes. In order to adjust for other covariates or intra-subject correlation among repeated measures,...
10.
Li X, Wang W, Liu G, Chan I
J Biopharm Stat
. 2011 Mar;
21(2):294-310.
PMID: 21391003
In clinical trials, study subjects are usually followed for a period of time after treatment, and the missing data issue is almost inevitable due to various reasons, including early dropout...