ArticlePrevention science : the official journal of the Society for Prevention Research2022
Design-Based Approaches to Causal Replication Studies.
Article in Prevention science : the official journal of the Society for Prevention Research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A scoping review on metrics to quantify reproducibility: a multitude of questions leads to a multitude of metrics.Royal Society open science · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent interest in promoting replication efforts assumes that there is well-established methodological guidance for designing and implementing these studies. However, no such consensus exists in the methodology literature. This article addresses these challenges by describing design-based approaches for planning systematic replication studies. Our general approach is derived from the Causal Replication Framework (CRF), which formalizes the assumptions under which replication success can be expected. The assumptions may be understood broadly as replication design requirements and individual study design requirements. Replication failure occurs when one or more CRF assumptions are violated. In design-based approaches to replication, CRF assumptions are systematically tested to evaluate the replicability of effects, as well as to identify sources of effect variation when replication failure is observed. The paper describes research designs for replication and demonstrates how multiple designs may be combined in systematic replication efforts, as well as how diagnostic measures may be used to assess the extent to which CRF assumptions are met in field settings.
Indexed as
Identifiers
34212299What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.