activity
20122020
most citedHandling missing values in cost-effectiveness analyses that use data from cluster randomised trials

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP2020

Comparing the Performance of Statistical Adjustment Methods By Recovering the Experimental Benchmark from the REFLUX Trial

Luke Keele, Stephen O'Neill, Richard Grieve

Much evidence in comparative effectiveness research is based on observational studies. Researchers who conduct observational studies typically assume that there are no unobservable…

stat.AP2019

Non-compliance and missing data in health economic evaluation

Karla DiazOrdaz, Richard Grieve

Health economic evaluations face the issues of non-compliance and missing data. Here, non-compliance is defined as non-adherence to a specific treatment, and occurs within randomis…

stat.ME2016

Instrumental variable approaches for estimating complier average causal effects on bivariate outcomes in randomised trials with non-compliance

Karla DiazOrdaz, Angelo Franchini, Richard Grieve

In Randomised Controlled Trials (RCT) with treatment non-compliance, instrumental variable approaches are used to estimate complier average causal effects. We extend these approach…

stat.ME2014★ 1 cited

A comparison of multiple imputation methods for bivariate hierarchical outcomes

Karla Diaz-Ordaz, Michael G. Kenward, Manuel Gomes +1

Missing observations are common in cluster randomised trials. Approaches taken to handling such missing data include: complete case analysis, single-level multiple imputation that…

stat.ME2012★ 3 cited

Handling missing values in cost-effectiveness analyses that use data from cluster randomised trials

Karla Diaz-Ordaz, Michael G. Kenward, Richard Grieve

Public policy-makers use cost-effectiveness analyses (CEA) to decide which health and social care interventions to provide. Appropriate methods have not been developed for handling…