Maya B. Mathur
Stanford University
StatisticsCovariateReplication (statistics)Internal medicineEconometricsPsychologyCausal inferenceCognitive psychologySensitivity (control systems)Observational studyMEDLINEPublication biasPopulationUnmeasured confoundingSensitivity analysesMathematicsComputer sciencePoint estimationConfidence intervalMedicineConfoundingRelative riskMeta-analysis
95Publications
18H-index
4,728Citations
Publications 91
Newest
#1Maya B. Mathur (Stanford University)H-Index: 18
#2Tyler J. VanderWeele (Harvard University)H-Index: 82
Meta-analyses contribute critically to cumulative science, but they can produce misleading conclusions if their constituent primary studies are biased, for example by unmeasured confounding in nonrandomized studies. We provide practical guidance on how meta-analysts can address confounding and other biases that affect studies' internal validity, focusing primarily on sensitivity analyses that help quantify how biased the meta-analysis estimates might be. We review a number of sensitivity analysi...
Source
#1Guo-Qiang Zhang (University of Gothenburg)
#2Jin-Liang Chen (CQMU: Chongqing Medical University)
Last. Mary Ann Lumsden (Glasgow Royal Infirmary)H-Index: 33
view all 17 authors...
Background: There remains uncertainty about the impact of menopausal hormone therapy (MHT) on women’s health. A systematic, comprehensive assessment of the effects on multiple outcomes is lacking. We conducted an umbrella review to comprehensively summarize evidence on the benefits and harms of MHT across diverse health outcomes. Methods and findings: We searched MEDLINE, EMBASE, and 10 other databases from inception to November 26, 2017, updated on December 17, 2020, to identify systematic revi...
Source
#1Maya B. Mathur (Stanford University)H-Index: 18
#2Tyler J. VanderWeele (Harvard University)H-Index: 82
Meta-regression analyses usually focus on estimating and testing differences in average effect sizes between individual levels of each meta-regression covariate in turn. These metrics are useful but have limitations: they consider each covariate individually, rather than in combination, and they characterize only the mean of a potentially heterogeneous distribution of effects. We propose additional metrics that address both limitations. Given a chosen threshold representing a meaningfully strong...
Source
#1Louisa H. Smith (Harvard University)H-Index: 5
#2Maya B. Mathur (Stanford University)H-Index: 18
Last. Tyler J. VanderWeele (Harvard University)H-Index: 82
view all 3 authors...
Confounding, selection bias, and measurement error are well-known sources of bias in epidemiologic research. Methods for assessing these biases have their own limitations. Many quantitative sensitivity analysis approaches consider each type of bias individually, although more complex approaches are harder to implement or require numerous assumptions. By failing to consider multiple biases at once, researchers can underestimate-or overestimate-their joint impact. We show that it is possible to bo...
1 CitationsSource
Last. Bright I. NwaruH-Index: 26
view all 17 authors...
Source
#1Maya B. Mathur (Stanford University)H-Index: 18
#2Jacob PeacockH-Index: 2
Last. Thomas N. Robinson (Stanford University)H-Index: 87
view all 7 authors...
Abstract Reducing meat consumption may improve human health, curb environmental damage, and limit the large-scale suffering of animals raised in factory farms. Most attention to reducing consumption has focused on restructuring environments where foods are chosen or on making health or environmental appeals. However, psychological theory suggests that interventions appealing to animal welfare concerns might operate on distinct, potent pathways. We conducted a systematic review and meta-analysis ...
3 CitationsSource
#1Maya B. MathurH-Index: 18
#2Louisa H. SmithH-Index: 5
Last. Tyler J. VanderWeeleH-Index: 82
view all 4 authors...
#1Maya B. Mathur (Stanford University)H-Index: 18
#2Tyler J. VanderWeele (Harvard University)H-Index: 82
Selective publication and reporting in individual papers compromise the scientific record, but are meta-analyses as compromised as their constituent studies? We systematically sampled 63 meta-analyses (each comprising at least 40 studies) in PLoS One, top medical journals, top psychology journals, and Metalab, an online, open-data database of developmental psychology meta-analyses. We empirically estimated publication bias in each, including only the peer-reviewed studies. Across all meta-analys...
1 CitationsSource
#1Maya B. MathurH-Index: 18
#2Louisa H. SmithH-Index: 5
Last. Tyler J. VanderWeeleH-Index: 82
view all 4 authors...
3 Citations
#1Maya B. MathurH-Index: 18
#2Louisa H. SmithH-Index: 5
Last. Tyler J. VanderWeeleH-Index: 82
view all 5 authors...
We provide sensitivity analyses for unmeasured confounding in estimates of effect heterogeneity and causal interaction.