Current advances in sampling theory: implications for human observational studies

Randomization: Beyond the closurization principle

Many cluster randomized trials have relatively few numbers of clusters to be randomized. When baseline cluster-level covariates are available prior to randomization, the set of potential allocations can be restricted so as to ensure balance across study arms. This article discusses why and how restrictions can be made, and the ramifications of so doing. The Fisher-Bailey validity is explained, and examples are given regarding the tradeoff between balance and validity.

How can the scientific community support the generation of the evidence needed to improve the quality of guidelines for micronutrient interventions?

The process used by the WHO to generate nutrition recommendations relies on high-quality research evidence, and this makes new demands on the research questions that nutrition scientists address. As a researcher involved in WHO nutrition guidelines development, my objective is to suggest ways in which our research can adapt to meet these demands. Randomized controlled trials and systematic reviews generate the highest quality of evidence to support strong recommendations, yet even these methods leave controversies in which judgments must be made. Using examples from recent research and guidelines, 4 issues are highlighted that illustrate ways in which nutrition research can adapt to become more useful and informative to global nutrition guidelines. These issues include embedding mechanistic research within trials, explicit choice of design along the efficacy or effectiveness spectrum, anticipation of heterogeneity of effects, and the need for research on consumer or community values and preferences.

Covariate-based constrained randomization of group-randomized trials

Group-randomized study designs are useful when individually randomized designs are either not possible, or will not be able to estimate the parameters of interest. Blocked and/or stratified (for example, pair-matched) designs have been used, and their properties statistically evaluated by many researchers. Group-randomized trials often have small numbers of experimental units, and strong, geographically induced between-unit correlation, which increase the chance of obtaining a "bad" randomization outcome. This article describes a procedure--random selection from a list of acceptable allocations--to allocate treatment conditions in a way that ensures balance on relevant covariates. Numerous individual- and group-level covariates can be balanced using exact or caliper criteria. Simulation results indicate that this method has good frequency properties, but some care may be needed not to overly constrain the randomization. There is a trade-off between achieving good balance through a highly constrained design, and jeopardizing the appearance of impartiality of the investigator and potentially departing from the nominal Type I error.

Randomization in Controlled Clinical Trials: Why the Flip of a Coin Is So Important

The randomized controlled trial (RCT) is considered the highest level of medical evidence. In this brief overview, we discuss several key principles of the RCT. First, balance is paramount. Comparison groups must have similar proportions of participants with "important" prognostic and confounding factors. Randomization may or may not achieve this balance; if it does not, statistical adjustments should be used. Second, a statistical analysis should emphasize comparability and not mask dissimilarity. If the trial was indeed randomized, certain analysis techniques, such as an intention to treat analysis, should always be presented. Third, additional bias-reducing techniques, such as concealing treatment assignments from treating physicians and participants (i.e., masking) and using clearly defined exclusion and inclusion criteria, should be used wherever possible.