Generalizability of Subgroup Effects.

Journal Article (Journal Article)

Generalizability methods are increasingly used to make inferences about the effect of interventions in target populations using a study sample. Most existing methods to generalize effects from sample to population rely on the assumption that subgroup-specific effects generalize directly. However, researchers may be concerned that in fact subgroup-specific effects differ between sample and population. In this brief report, we explore the generalizability of subgroup effects. First, we derive the bias in the sample average treatment effect estimator as an estimate of the population average treatment effect when subgroup effects in the sample do not directly generalize. Next, we present a Monte Carlo simulation to explore bias due to unmeasured heterogeneity of subgroup effects across sample and population. Finally, we examine the potential for bias in an illustrative data example. Understanding the generalizability of subgroup effects may lead to increased use of these methods for making externally valid inferences of treatment effects using a study sample.

Full Text

Duke Authors

Cited Authors

  • Seamans, MJ; Hong, H; Ackerman, B; Schmid, I; Stuart, EA

Published Date

  • May 1, 2021

Published In

Volume / Issue

  • 32 / 3

Start / End Page

  • 389 - 392

PubMed ID

  • 33591050

Pubmed Central ID

  • PMC8012217

Electronic International Standard Serial Number (EISSN)

  • 1531-5487

Digital Object Identifier (DOI)

  • 10.1097/EDE.0000000000001329

Language

  • eng

Conference Location

  • United States