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...

Hierarchical datasets are commonly a product of the popular CSPro system developed by the U.S. Census Bureau. CSPro became widely popular and a de facto standard for data collection in many countries; some agencies supply data exclusively in CSPro format. While CSPro can export the data into...

Multiple imputation (MI) is a popular approach to handling missing data, and an extensive range of MI commands is now available in official Stata. A common problem is that of missing values in covariates of regression models. When the substantive model for the outcome contains nonlinear...

Within drug development, it is crucial to find the right dose that is going to be safe and efficacious; this is often done within early phase II clinical trials. The aim of the dose-finding trial is to understand the relationship between the dose of drug and the potential effect of the drug....

Electronic health records are increasingly used for epidemiological and health service research. However, missing data are often an issue when dealing with electronic records. Up to now, various approaches have been used to overcome these issues, including complete case analysis, last...

Stata has a wide range of tools for performing meta-analysis, but presently not individual participant data (IPD) meta-analysis, in which the analysis units are within-study observations (for example, patients) rather than aggregate study results. I present ipdmetan, a command that facilitates...

This presentation illustrates Stata’s implementation of the repeated half-sample bootstrap proposed by Saigo et al. (2001, Survey Methodology). This resampling scheme is easy to implement and is appropriate for complex survey designs, even with small stratum sizes. The user-written...

Reweighting is a popular statistical technique to deal with inference in presence of a nonrandom sample. In the literature, various reweighting estimators have been proposed. This paper presents the author-written Stata routine treatrew, which implements the reweighting on the propensity-score...

This presentation explains how to exploit Stata to run multilevel multiprocess regressions with aML (software downloadable for free from applied-ml.com). I show how a single do-file can prepare the dataset, write the control files, input the starting values, and run the regressions without the...

Econometricians have begun to devote more attention to spatial interactions when carrying out applied econometric studies. In part, this is motivated by an explicit focus on spatial interactions in policy formulation or market behavior, but it may also reflect concern about the role of omitted...