42 citations · 68 across the 19 of their papers we have counts for
20 papers
Normalised Local Hazard Plots
Nils Lid Hjort, Thomas Lumley
The purpose of this paper is to develop and illustrate certain classes of graphical plots that can be used for model verification in quite general survival data and life history da…
Linear mixed models for complex survey data: implementing and evaluating pairwise likelihood
Thomas Lumley, Xudong Huang
As complex-survey data becomes more widely used in health and social-science research, there is increasing interest in fitting a wider range of regression models. We describe an im…
Practical considerations for sandwich variance estimation in two-stage regression settings
Lillian A. Boe, Thomas Lumley, Pamela A. Shaw
We present a practical approach for computing the sandwich variance estimator in two-stage regression model settings. As a motivating example for two-stage regression, we consider…
Privacy with Good Taste: A Case Study in Quantifying Privacy Risks in Genetic Scores
Raúl Pardo, Willard Rafnsson, Gregor Steinhorn +5
Analysis of genetic data opens up many opportunities for medical and scientific advances. The use of phenotypic information and polygenic risk scores to analyze genetic data is wid…
Three-phase generalized raking and multiple imputation estimators to address error-prone data
Gustavo Amorim, Ran Tao, Sarah Lotspeich +4
Validation studies are often used to obtain more reliable information in settings with error-prone data. Validated data on a subsample of subjects can be used together with error-p…
Choosing good subsamples for regression modelling
Thomas Lumley, Tong Chen
A common problem in health research is that we have a large database with many variables measured on a large number of individuals. We are interested in measuring additional variab…
Analysis of Error-prone Electronic Health Records with Multi-wave Validation Sampling: Association of Maternal Weight Gain during Pregnancy with Childhood Outcomes
Bryan E. Shepherd, Kyunghee Han, Tong Chen +6
Electronic health record (EHR) data are increasingly used for biomedical research, but these data have recognized data quality challenges. Data validation is necessary to use EHR d…
Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall
Jasper B. Yang, Bryan E. Shepherd, Thomas Lumley +1
The R package optimall offers a collection of functions that efficiently streamline the design process of sampling in surveys ranging from simple to complex. The package's main fun…
Optimal sampling for design-based estimators of regression models
Tong Chen, Thomas Lumley
Two-phase designs measure variables of interest on a subcohort where the outcome and covariates are readily available or cheap to collect on all individuals in the cohort. Given li…
Multiple Imputation Through XGBoost
Yongshi Deng, Thomas Lumley
The use of multiple imputation (MI) is becoming increasingly popular for addressing missing data. Although some conventional MI approaches have been well studied and have shown emp…
Improved Generalized Raking Estimators to Address Dependent Covariate and Failure-Time Outcome Error
Eric J. Oh, Bryan E. Shepherd, Thomas Lumley +1
Biomedical studies that use electronic health records (EHR) data for inference are often subject to bias due to measurement error. The measurement error present in EHR data is typi…
Two-phase analysis and study design for survival models with error-prone exposures
Kyunghee Han, Thomas Lumley, Bryan E. Shepherd +1
Increasingly, medical research is dependent on data collected for non-research purposes, such as electronic health records data (EHR). EHR data and other large databases can be pro…
Stylised Choropleth Maps for New Zealand Regions and District Health Boards
Thomas Lumley
New Zealand has two top-level sets of administrative divisions: the District Health Boards and the Regions. In this note I describe a hexagonal layout for creating stylised maps of…
Combining multiple imputation with raking of weights: An efficient and robust approach in the setting of nearly-true models
Kyunghee Han, Pamela A. Shaw, Thomas Lumley
Multiple imputation provides us with efficient estimators in model-based methods for handling missing data under the true model. It is also well-understood that design-based estima…
Raking and Regression Calibration: Methods to Address Bias from Correlated Covariate and Time-to-Event Error
Eric J. Oh, Bryan E. Shepherd, Thomas Lumley +1
Medical studies that depend on electronic health records (EHR) data are often subject to measurement error, as the data are not collected to support research questions under study.…
Fast generalised linear models by database sampling and one-step polishing
Thomas Lumley
In this note, I show how to fit a generalised linear model to observations on variables stored in a relational database, using one sampling query and one aggregation querie…
Estimating prediction error for complex samples
Andrew Holbrook, Thomas Lumley, Daniel Gillen
With a growing interest in using non-representative samples to train prediction models for numerous outcomes it is necessary to account for the sampling design that gives rise to t…
Robustness of semiparametric efficiency in nearly-true models for two-phase samples
Thomas Lumley
We examine the performance of efficient and AIPW estimators under two-phase sampling when the complete-data model is nearly correctly specified, in the sense that the misspecificat…
Pseudo- statistics under complex sampling
Thomas Lumley
Model summaries based on the ratio of fitted and null likelihoods have been proposed for generalised linear models, reducing to the familiar coefficient of determination in t…
Model-robust regression and a Bayesian ``sandwich'' estimator
Adam A. Szpiro, Kenneth M. Rice, Thomas Lumley
We present a new Bayesian approach to model-robust linear regression that leads to uncertainty estimates with the same robustness properties as the Huber--White sandwich estimator.…