Lan Liu


Accepting PhD Students

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Personal profile

Research interests

Causal Inference, Big Data, Missing Data, Bayesian Inference, Statistical Consulting


Stat 5021 2016 Spring

Stat 4051 2016 Fall

Stat 4052 2017 Spring

Education/Academic qualification

PhD, University of North Carolina

MS, University of Science and Technology of China

Research interests

  • Causal Inference
  • Statistical Consulting
  • statistics
  • Big Data

Fingerprint The Fingerprint is created by mining the titles and abstracts of the person's research outputs and projects/funding awards to create an index of weighted terms from discipline-specific thesauri.

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Treatment Effects Mathematics
Semiparametric Estimation Mathematics
Missing at Random Mathematics
Observational Study Mathematics
Instrumental Variables Mathematics
Robust Estimation Mathematics
Latent Variables Mathematics
Paradox Mathematics

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2017 2022

Functional magnetic resonance imaging

Research Output 2013 2019

Doubly robust estimation in observational studies with partial interference

Liu, L., Hudgens, M. G., Saul, B., Clemens, J. D., Ali, M. & Emch, M. E., Jan 1 2019, In : Stat. 8, 1, e214.

Research output: Contribution to journalArticle

Observational Study
Robust Estimation

Novel criteria to exclude the surrogate paradox and their optimalities

Yin, Y., Liu, L., Geng, Z. & Luo, P., Jan 1 2019, In : Scandinavian Journal of Statistics.

Research output: Contribution to journalArticle

Causal Effect
Surrogate Endpoint
Observed Information
3 Citations (Scopus)

Semiparametric estimation with data missing not at random using an instrumental variable

Sun, B. L., Liu, L., Miao, W., Wirth, K., Robins, J. & Tchetgen, E. J., Oct 1 2018, In : Statistica Sinica. 28, 4, p. 1965-1983 19 p.

Research output: Contribution to journalArticle

Semiparametric Estimation
Missing at Random
Instrumental Variables
Nonparametric Identification
Missing Data Mechanism

On the Individual Surrogate Paradox

Ma, L., Yin, Y., Liu, L. & Geng, Z., 2017, In : arXiv.

Research output: Contribution to journalArticle

Causal effect
Treatment effects

Assessing the Treatment Effect Heterogeneity with a Latent Variable

Yin, Y., Liu, L. & Geng, Z., 2016, In : Statistica Sinica. 28, 1, p. 115-135 21 p.

Research output: Contribution to journalArticle

Latent Variables
Treatment Effects
Average Treatment Effect
Potential Outcomes