Sharp Bounds on the Variance of General Regression Adjustment in Randomized Experiments Article Swipe
Jonas M. Mikhaeil
,
Donald P. Green
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.00191
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.00191
A growing statistical literature focuses on causal inference in the context of experiments where the target of inference is the average treatment effect in a finite population and random assignment determines which subjects are allocated to one of the experimental conditions. In this framework, variances of average treatment effect estimators remain unidentified because they depend on the covariance between treated and untreated potential outcomes, which are never jointly observed. Conventional variance estimators are upwardly biased. Aronow, Green and Lee [Ann. Statist. 42(3): 850-871 (June 2014)] provide an estimator for the variance of the difference-in-means estimator that is asymptotically sharp. In practice, researchers often use some form of covariate adjustment, such as linear regression, when estimating the average treatment effect. Adapting propositions from empirical process theory, we extend the result in (Aronow et al., 2014), providing asymptotically sharp variance bounds for general regression adjustment. We apply these results to linear regression adjustment and show benefits both in a simulation and in three empirical applications drawn from different disciplines.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2411.00191
- https://arxiv.org/pdf/2411.00191
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404344740
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4404344740Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2411.00191Digital Object Identifier
- Title
-
Sharp Bounds on the Variance of General Regression Adjustment in Randomized ExperimentsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-10-31Full publication date if available
- Authors
-
Jonas M. Mikhaeil, Donald P. GreenList of authors in order
- Landing page
-
https://arxiv.org/abs/2411.00191Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2411.00191Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2411.00191Direct OA link when available
- Concepts
-
Randomized experiment, Variance (accounting), Randomized controlled trial, Regression, Statistics, Mathematics, Analysis of variance, Econometrics, Economics, Medicine, Internal medicine, AccountingTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4404344740 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2411.00191 |
| ids.doi | https://doi.org/10.48550/arxiv.2411.00191 |
| ids.openalex | https://openalex.org/W4404344740 |
| fwci | |
| type | preprint |
| title | Sharp Bounds on the Variance of General Regression Adjustment in Randomized Experiments |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11871 |
| topics[0].field.id | https://openalex.org/fields/26 |
| topics[0].field.display_name | Mathematics |
| topics[0].score | 0.927299976348877 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2613 |
| topics[0].subfield.display_name | Statistics and Probability |
| topics[0].display_name | Advanced Statistical Methods and Models |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C155108698 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6266686916351318 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1231081 |
| concepts[0].display_name | Randomized experiment |
| concepts[1].id | https://openalex.org/C196083921 |
| concepts[1].level | 2 |
| concepts[1].score | 0.600098192691803 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q7915758 |
| concepts[1].display_name | Variance (accounting) |
| concepts[2].id | https://openalex.org/C168563851 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5269920229911804 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1436668 |
| concepts[2].display_name | Randomized controlled trial |
| concepts[3].id | https://openalex.org/C83546350 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5243197679519653 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1139051 |
| concepts[3].display_name | Regression |
| concepts[4].id | https://openalex.org/C105795698 |
| concepts[4].level | 1 |
| concepts[4].score | 0.5130192637443542 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[4].display_name | Statistics |
| concepts[5].id | https://openalex.org/C33923547 |
| concepts[5].level | 0 |
| concepts[5].score | 0.4406394362449646 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[5].display_name | Mathematics |
| concepts[6].id | https://openalex.org/C99476002 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4264284372329712 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q42297 |
| concepts[6].display_name | Analysis of variance |
| concepts[7].id | https://openalex.org/C149782125 |
| concepts[7].level | 1 |
| concepts[7].score | 0.4216388165950775 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q160039 |
| concepts[7].display_name | Econometrics |
| concepts[8].id | https://openalex.org/C162324750 |
| concepts[8].level | 0 |
| concepts[8].score | 0.30724412202835083 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[8].display_name | Economics |
| concepts[9].id | https://openalex.org/C71924100 |
| concepts[9].level | 0 |
| concepts[9].score | 0.14976921677589417 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[9].display_name | Medicine |
| concepts[10].id | https://openalex.org/C126322002 |
| concepts[10].level | 1 |
| concepts[10].score | 0.059600770473480225 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11180 |
| concepts[10].display_name | Internal medicine |
| concepts[11].id | https://openalex.org/C121955636 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q4116214 |
| concepts[11].display_name | Accounting |
| keywords[0].id | https://openalex.org/keywords/randomized-experiment |
| keywords[0].score | 0.6266686916351318 |
| keywords[0].display_name | Randomized experiment |
| keywords[1].id | https://openalex.org/keywords/variance |
| keywords[1].score | 0.600098192691803 |
| keywords[1].display_name | Variance (accounting) |
| keywords[2].id | https://openalex.org/keywords/randomized-controlled-trial |
| keywords[2].score | 0.5269920229911804 |
| keywords[2].display_name | Randomized controlled trial |
| keywords[3].id | https://openalex.org/keywords/regression |
| keywords[3].score | 0.5243197679519653 |
| keywords[3].display_name | Regression |
| keywords[4].id | https://openalex.org/keywords/statistics |
| keywords[4].score | 0.5130192637443542 |
| keywords[4].display_name | Statistics |
| keywords[5].id | https://openalex.org/keywords/mathematics |
| keywords[5].score | 0.4406394362449646 |
| keywords[5].display_name | Mathematics |
| keywords[6].id | https://openalex.org/keywords/analysis-of-variance |
| keywords[6].score | 0.4264284372329712 |
| keywords[6].display_name | Analysis of variance |
| keywords[7].id | https://openalex.org/keywords/econometrics |
| keywords[7].score | 0.4216388165950775 |
| keywords[7].display_name | Econometrics |
| keywords[8].id | https://openalex.org/keywords/economics |
| keywords[8].score | 0.30724412202835083 |
| keywords[8].display_name | Economics |
| keywords[9].id | https://openalex.org/keywords/medicine |
| keywords[9].score | 0.14976921677589417 |
| keywords[9].display_name | Medicine |
| keywords[10].id | https://openalex.org/keywords/internal-medicine |
| keywords[10].score | 0.059600770473480225 |
| keywords[10].display_name | Internal medicine |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2411.00191 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2411.00191 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2411.00191 |
| locations[1].id | doi:10.48550/arxiv.2411.00191 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | cc-by |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2411.00191 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5094063561 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Jonas M. Mikhaeil |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Mikhaeil, Jonas M. |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5057733936 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-8850-438X |
| authorships[1].author.display_name | Donald P. Green |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Green, Donald P. |
| authorships[1].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2411.00191 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Sharp Bounds on the Variance of General Regression Adjustment in Randomized Experiments |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T11871 |
| primary_topic.field.id | https://openalex.org/fields/26 |
| primary_topic.field.display_name | Mathematics |
| primary_topic.score | 0.927299976348877 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2613 |
| primary_topic.subfield.display_name | Statistics and Probability |
| primary_topic.display_name | Advanced Statistical Methods and Models |
| related_works | https://openalex.org/W2355769538, https://openalex.org/W2081816252, https://openalex.org/W2015216653, https://openalex.org/W2373885168, https://openalex.org/W2112436308, https://openalex.org/W2362391294, https://openalex.org/W3004061946, https://openalex.org/W3195883860, https://openalex.org/W2026473779, https://openalex.org/W2093998792 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2411.00191 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2411.00191 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2411.00191 |
| primary_location.id | pmh:oai:arXiv.org:2411.00191 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2411.00191 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2411.00191 |
| publication_date | 2024-10-31 |
| publication_year | 2024 |
| referenced_works_count | 0 |
| abstract_inverted_index.A | 0 |
| abstract_inverted_index.a | 24, 156 |
| abstract_inverted_index.In | 41, 99 |
| abstract_inverted_index.We | 143 |
| abstract_inverted_index.an | 86 |
| abstract_inverted_index.as | 110 |
| abstract_inverted_index.et | 131 |
| abstract_inverted_index.in | 8, 23, 129, 155, 159 |
| abstract_inverted_index.is | 18, 96 |
| abstract_inverted_index.of | 11, 16, 37, 45, 91, 106 |
| abstract_inverted_index.on | 5, 55 |
| abstract_inverted_index.to | 35, 147 |
| abstract_inverted_index.we | 125 |
| abstract_inverted_index.Lee | 78 |
| abstract_inverted_index.and | 27, 60, 77, 151, 158 |
| abstract_inverted_index.are | 33, 65, 72 |
| abstract_inverted_index.for | 88, 139 |
| abstract_inverted_index.one | 36 |
| abstract_inverted_index.the | 9, 14, 19, 38, 56, 89, 92, 115, 127 |
| abstract_inverted_index.use | 103 |
| abstract_inverted_index.al., | 132 |
| abstract_inverted_index.both | 154 |
| abstract_inverted_index.form | 105 |
| abstract_inverted_index.from | 121, 164 |
| abstract_inverted_index.show | 152 |
| abstract_inverted_index.some | 104 |
| abstract_inverted_index.such | 109 |
| abstract_inverted_index.that | 95 |
| abstract_inverted_index.they | 53 |
| abstract_inverted_index.this | 42 |
| abstract_inverted_index.when | 113 |
| abstract_inverted_index.(June | 83 |
| abstract_inverted_index.Green | 76 |
| abstract_inverted_index.[Ann. | 79 |
| abstract_inverted_index.apply | 144 |
| abstract_inverted_index.drawn | 163 |
| abstract_inverted_index.never | 66 |
| abstract_inverted_index.often | 102 |
| abstract_inverted_index.sharp | 136 |
| abstract_inverted_index.these | 145 |
| abstract_inverted_index.three | 160 |
| abstract_inverted_index.where | 13 |
| abstract_inverted_index.which | 31, 64 |
| abstract_inverted_index.2014), | 133 |
| abstract_inverted_index.2014)] | 84 |
| abstract_inverted_index.42(3): | 81 |
| abstract_inverted_index.bounds | 138 |
| abstract_inverted_index.causal | 6 |
| abstract_inverted_index.depend | 54 |
| abstract_inverted_index.effect | 22, 48 |
| abstract_inverted_index.extend | 126 |
| abstract_inverted_index.finite | 25 |
| abstract_inverted_index.linear | 111, 148 |
| abstract_inverted_index.random | 28 |
| abstract_inverted_index.remain | 50 |
| abstract_inverted_index.result | 128 |
| abstract_inverted_index.sharp. | 98 |
| abstract_inverted_index.target | 15 |
| abstract_inverted_index.(Aronow | 130 |
| abstract_inverted_index.850-871 | 82 |
| abstract_inverted_index.Aronow, | 75 |
| abstract_inverted_index.average | 20, 46, 116 |
| abstract_inverted_index.because | 52 |
| abstract_inverted_index.between | 58 |
| abstract_inverted_index.biased. | 74 |
| abstract_inverted_index.context | 10 |
| abstract_inverted_index.effect. | 118 |
| abstract_inverted_index.focuses | 4 |
| abstract_inverted_index.general | 140 |
| abstract_inverted_index.growing | 1 |
| abstract_inverted_index.jointly | 67 |
| abstract_inverted_index.process | 123 |
| abstract_inverted_index.provide | 85 |
| abstract_inverted_index.results | 146 |
| abstract_inverted_index.theory, | 124 |
| abstract_inverted_index.treated | 59 |
| abstract_inverted_index.Adapting | 119 |
| abstract_inverted_index.Statist. | 80 |
| abstract_inverted_index.benefits | 153 |
| abstract_inverted_index.subjects | 32 |
| abstract_inverted_index.upwardly | 73 |
| abstract_inverted_index.variance | 70, 90, 137 |
| abstract_inverted_index.allocated | 34 |
| abstract_inverted_index.covariate | 107 |
| abstract_inverted_index.different | 165 |
| abstract_inverted_index.empirical | 122, 161 |
| abstract_inverted_index.estimator | 87, 94 |
| abstract_inverted_index.inference | 7, 17 |
| abstract_inverted_index.observed. | 68 |
| abstract_inverted_index.outcomes, | 63 |
| abstract_inverted_index.potential | 62 |
| abstract_inverted_index.practice, | 100 |
| abstract_inverted_index.providing | 134 |
| abstract_inverted_index.treatment | 21, 47, 117 |
| abstract_inverted_index.untreated | 61 |
| abstract_inverted_index.variances | 44 |
| abstract_inverted_index.adjustment | 150 |
| abstract_inverted_index.assignment | 29 |
| abstract_inverted_index.covariance | 57 |
| abstract_inverted_index.determines | 30 |
| abstract_inverted_index.estimating | 114 |
| abstract_inverted_index.estimators | 49, 71 |
| abstract_inverted_index.framework, | 43 |
| abstract_inverted_index.literature | 3 |
| abstract_inverted_index.population | 26 |
| abstract_inverted_index.regression | 141, 149 |
| abstract_inverted_index.simulation | 157 |
| abstract_inverted_index.adjustment, | 108 |
| abstract_inverted_index.adjustment. | 142 |
| abstract_inverted_index.conditions. | 40 |
| abstract_inverted_index.experiments | 12 |
| abstract_inverted_index.regression, | 112 |
| abstract_inverted_index.researchers | 101 |
| abstract_inverted_index.statistical | 2 |
| abstract_inverted_index.Conventional | 69 |
| abstract_inverted_index.applications | 162 |
| abstract_inverted_index.disciplines. | 166 |
| abstract_inverted_index.experimental | 39 |
| abstract_inverted_index.propositions | 120 |
| abstract_inverted_index.unidentified | 51 |
| abstract_inverted_index.asymptotically | 97, 135 |
| abstract_inverted_index.difference-in-means | 93 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile |