CoChat
Sign Up
Cited by 70Advanced Causal Inference TechniquesOptimal Experimental Design MethodsEvaluation and Performance Assessment

Group Comparability: A Multiattribute Utility Measurement Approach to the Use of Random Assignment with Small Numbers of Aggregated Units

Graham, John W., Flay, Brian R., Anderson Johnson, C., Hansen, William B., Collins, Linda M.·1984·Evaluation Review
DOI 10.1177/0193841x8400800206
Open this paper in CoChat — free account

Abstract

It is not always possible, especially in large-scale evaluation research, to ensure that random assignment will produce groups that are comparable on any number of potentially important factors. Typically, gaining comparability has been achieved only at the expense of random assignment. A method is presented that allows multivariate comparability while making only minimal restrictions on randomization. The procedure is demonstrated in the context of assigning 63 aggregated units (schools) to 28 experimental and control conditions. Good comparability of groups for all primary main effects and interactions was venfied for 15 individual variables.

Integrity signals

Registry

Crossref · 10.1177/0193841x8400800206

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Graham, J. W., Flay, B. R., Anderson Johnson, C., Hansen, W. B., & Collins, L. M.
Affiliations
  • Health Behavior Research Institute University of Southern California
  • University of Southern California (US)
ORCID
Venue
Evaluation Review
Publisher
SAGE Publications
Published
1984-04
Volume
8
Issue
2
Pages
247-260
ISSN
  • 0145-4692 (ISSN-L)
  • 0193-841X
  • 1552-3926
DOI
10.1177/0193841x8400800206
OpenAlex
W2074613824
Cited by
70
References
15
Citations by year
2025: 1 · 2024: 1 · 2022: 2 · 2020: 1 · 2019: 3 · 2017: 3 · 2016: 2 · 2015: 1 · 2014: 4 · 2013: 4 · 2012: 5
FWCI
1.35
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
  • Evaluation Review (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
Keywords
random assignment, school assignment, experimental and control groups, main effects and interactions

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review