A tutorial on multilevel survival analysis: methods, models and applications
PC Austin - International Statistical Review, 2017 - Wiley Online Library
Data that have a multilevel structure occur frequently across a range of disciplines, including
epidemiology, health services research, public health, education and sociology. We …
epidemiology, health services research, public health, education and sociology. We …
Device closure of patent foramen ovale after stroke: pooled analysis of completed randomized trials
DM Kent, IJ Dahabreh, R Ruthazer, AJ Furlan… - Journal of the American …, 2016 - jacc.org
Background The comparative effectiveness of percutaneous closure of patent foramen ovale
(PFO) plus medical therapy versus medical therapy alone for cryptogenic stroke is uncertain …
(PFO) plus medical therapy versus medical therapy alone for cryptogenic stroke is uncertain …
[HTML][HTML] Different ways to estimate treatment effects in randomised controlled trials
J Twisk, L Bosman, T Hoekstra, J Rijnhart… - Contemporary clinical …, 2018 - Elsevier
Background Regarding the analysis of RCT data there is a debate going on whether an
adjustment for the baseline value of the outcome variable should be made. When an …
adjustment for the baseline value of the outcome variable should be made. When an …
[HTML][HTML] The number of subjects per variable required in linear regression analyses
PC Austin, EW Steyerberg - Journal of clinical epidemiology, 2015 - Elsevier
Objectives To determine the number of independent variables that can be included in a
linear regression model. Study Design and Setting We used a series of Monte Carlo …
linear regression model. Study Design and Setting We used a series of Monte Carlo …
Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis
PC Austin - Statistics in medicine, 2016 - Wiley Online Library
Propensity score methods are used to reduce the effects of observed confounding when
using observational data to estimate the effects of treatments or exposures. A popular …
using observational data to estimate the effects of treatments or exposures. A popular …
The use of propensity score methods with survival or time‐to‐event outcomes: reporting measures of effect similar to those used in randomized experiments
PC Austin - Statistics in medicine, 2014 - Wiley Online Library
Propensity score methods are increasingly being used to estimate causal treatment effects
in observational studies. In medical and epidemiological studies, outcomes are frequently …
in observational studies. In medical and epidemiological studies, outcomes are frequently …
[图书][B] Targeted learning in data science
MJ Van der Laan, S Rose - 2018 - Springer
This book builds on and is a sequel to our book Targeted Learning: Causal Inference for
Observational and Experimental Studies (2011). Since the publication of this first book on …
Observational and Experimental Studies (2011). Since the publication of this first book on …
The performance of different propensity score methods for estimating marginal hazard ratios
PC Austin - Statistics in medicine, 2013 - Wiley Online Library
Propensity score methods are increasingly being used to reduce or minimize the effects of
confounding when estimating the effects of treatments, exposures, or interventions when …
confounding when estimating the effects of treatments, exposures, or interventions when …
The risks and rewards of covariate adjustment in randomized trials: an assessment of 12 outcomes from 8 studies
Background Adjustment for prognostic covariates can lead to increased power in the
analysis of randomized trials. However, adjusted analyses are not often performed in …
analysis of randomized trials. However, adjusted analyses are not often performed in …
The performance of inverse probability of treatment weighting and full matching on the propensity score in the presence of model misspecification when estimating the …
There is increasing interest in estimating the causal effects of treatments using observational
data. Propensity-score matching methods are frequently used to adjust for differences in …
data. Propensity-score matching methods are frequently used to adjust for differences in …