Multiple imputation is increasingly regarded as the standard method to account for partially observed data, but most methods have been based on cross-sectional imputation algorithms. Recently, a new multiple-imputation method, the two fold fully conditional specification (FCS) method, was...

Any analysis with incomplete data makes untestable assumptions about the missing data, and analysts are therefore urged to conduct sensitivity analyses. Ideally, a model is constructed containing a nonidentifiable parameter d, where d = 0 corresponds to the assumption made in the standard...

Network meta-analysis involves synthesising the scientific literature comparing several treatments. Typically, two-arm and three-arm randomized trials are synthesized, and the aim is to compare treatments that have not been directly compared and often to rank the treatments. A difficulty is that...

Treatment changes in randomized trials are common: for example, in a trial evaluating psychotherapy, individuals allocated to psychotherapy may attend only partially or not at all; or in a trial evaluating a drug treatment, individuals allocated to no drug treatment may nevertheless receive the...

A comprehensive range of user-written commands for meta-analysis is available in Stata and documented in detail in the recent book Meta-Analysis in Stata (Sterne, ed., 2009, [Stata Press]).The purpose of this session is to describe these commands, with a focus on recent developments and areas in...

Simulation studies are a powerful tool, but their analysis is not always done well; in particular, Monte Carlo standard errors are often not reported. I present a Stata program, - simsum-, which can output a range of summaries, including bias, precision of one method relative to another,...

In epidemiology, measurement error or within-individual variation in exposures and confounders leads to attenuated effect estimates and inadequate control of confounding. Adjustment for measurement error is possible if its magnitude may be estimated from supplementary information, typically...

A new command metamiss performs meta-analysis when some or all studies have missing data. A variety of assumptions are available, including missing-at-random, missing=failure, worst and best cases, and incorporating a user-specified prior distribution for the degree of informative missingness....

We consider a two-group clinical trial with a survival outcome, in which some subjects may 'cross over' to receive the treatment of the other arm. Our command strbee adjusts for treatment cross-over in one or both arms. This is done by a randomization-respecting method which preserves the...

In teaching logistic regression for case–control studies, I ask master’s students in epidemiology to assess an interaction between a 2-level exposure and a 4-level exposure using a likelihood-ratio test. Theory suggests that the test statistic has 3 degrees of freedom, but Stata uses 2...