Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment | Paper Citation Record

Observation c47b3d5d-1a84-4729-9d5a-2c897d26dacc · outbound

This paper cites Alternative analysis methods for time to event endpoi nts under nonproportional haz- ards: A comparative analysis,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Alternative analysis methods for time to event endpoi nts under nonproportional haz- ards: A comparative analysis,

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This paper cites The optimization was stopped, if the ℓ2-norm of the gradient gets smaller than ǫstop = 1.0 × 10−2.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The optimization was stopped, if the ℓ2-norm of the gradient gets smaller than ǫstop = 1.0 × 10−2

Reference 2

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

Reference 3

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This paper cites Does cox analysis of a randomized survival study yield a causal treatment eﬀect?.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Does cox analysis of a randomized survival study yield a causal treatment eﬀect?

Reference 4

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This paper cites The hazards of per iod speciﬁc and weighted hazard ratios,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The hazards of per iod speciﬁc and weighted hazard ratios,

Reference 5

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This paper cites The hazards of hazard ratios,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The hazards of hazard ratios,

Reference 6

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This paper cites Intention-to-trea t comparisons in randomized trials,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Intention-to-trea t comparisons in randomized trials,

Reference 7

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This paper cites Subtleties in the inter- pretation of hazard contrasts,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Subtleties in the inter- pretation of hazard contrasts,

Reference 8

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This paper cites Causality and the cox regression m odel,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Causality and the cox regression m odel,

Reference 9

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Observation ea9a9134-dac6-4b3c-a993-813713ee69a4 · outbound

This paper cites Treatment eﬀect quantiﬁcation for tim e-to-event endpoints–estimands, analysis strategies, and beyond,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Treatment eﬀect quantiﬁcation for tim e-to-event endpoints–estimands, analysis strategies, and beyond,

Reference 10

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This paper cites On Defense of the Hazard Ratio.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On Defense of the Hazard Ratio

Reference 11

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This paper cites Causal interpretation of the ha zard ratio in ran- domized clinical trials,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Causal interpretation of the ha zard ratio in ran- domized clinical trials,

Reference 12

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This paper cites Estimating heterogeneous treatment eﬀects with right-censored data vi a causal survival forests,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Estimating heterogeneous treatment eﬀects with right-censored data vi a causal survival forests,

Reference 13

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Observation 80c0ab57-ec51-4dbb-b812-0c299fc4f559 · outbound

This paper cites Uses and limitations of the restricted mean survival time: Illustra tive examples from cardiovascular outcomes and mortality trials in type 2 diabetes,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Uses and limitations of the restricted mean survival time: Illustra tive examples from cardiovascular outcomes and mortality trials in type 2 diabetes,

Reference 14

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Observation 70854644-5ac5-4f59-9bf1-7a6fe52058c9 · outbound

This paper cites Treatment eﬀe ct measures un- der nonproportional hazards,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Treatment eﬀe ct measures un- der nonproportional hazards,

Reference 15

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This paper cites Design, implem entation, and inferential issues asso- ciated with clinical trials that rely on data in electronic m edical records: a narrative review,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Design, implem entation, and inferential issues asso- ciated with clinical trials that rely on data in electronic m edical records: a narrative review,

Reference 16

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Observation 9d206ccc-c65f-4d8f-b1ba-56b4e9bcfdea · outbound

This paper cites Estimating heterogeneous treatment eﬀects on survi val outcomes using counterfactual censoring unbiased transformations,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Estimating heterogeneous treatment eﬀects on survi val outcomes using counterfactual censoring unbiased transformations,

Reference 17

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This paper cites Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data

Reference 18

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This paper cites Double/debiased machine learning for treat- ment and structural parameters,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Double/debiased machine learning for treat- ment and structural parameters,

Reference 19

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This paper cites Marginal structural models to estimate the joint causal eﬀect of nonrandomized treatmen ts,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Marginal structural models to estimate the joint causal eﬀect of nonrandomized treatmen ts,

Reference 20

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

Reference 21

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

Reference 22

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Observation 6f8582fb-dd7a-4081-9177-0d941670fad8 · outbound

This paper cites An introduction to double/debiased ma chine learning,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment An introduction to double/debiased ma chine learning,

Reference 23

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This paper cites Full likelihood inference s in the cox model: an empirical likelihood approach,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Full likelihood inference s in the cox model: an empirical likelihood approach,

Reference 24

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This paper cites Marginal structuralmodels and causal inference in epidemiology,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Marginal structuralmodels and causal inference in epidemiology,

Reference 25

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This paper cites Kernel ba yes’ rule: Bayesian inference with positive deﬁnite kernels,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Kernel ba yes’ rule: Bayesian inference with positive deﬁnite kernels,

Reference 26

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This paper cites Applica- tion of marginal structural models in pharmacoepidemiolog ic studies: a sys- tematic review,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Applica- tion of marginal structural models in pharmacoepidemiolog ic studies: a sys- tematic review,

Reference 27

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This paper cites Functional analysis and semi-groups, 3rd printing of rev. ed. of 1957,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Functional analysis and semi-groups, 3rd printing of rev. ed. of 1957,

Reference 28

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This paper cites 4 (Springer, 2006).

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment 4 (Springer, 2006)

Reference 29

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This paper cites History-adjusted marginal structural models and statically-optimal dynamic treatme nt regimens,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment History-adjusted marginal structural models and statically-optimal dynamic treatme nt regimens,

Reference 30

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This paper cites Theory of reproducing kernels,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Theory of reproducing kernels,

Reference 31

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This paper cites Learning the kernel matrix with semideﬁnite progr amming,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Learning the kernel matrix with semideﬁnite progr amming,

Reference 32

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Fast learning rate of multiple kernel learning: Trade-oﬀ between sparsity and smoothness,

Reference 33

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This paper cites Sparsity in mult iple kernel learning,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Sparsity in mult iple kernel learning,

Reference 34

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This paper cites Consistency of the group lasso and mult iple kernel learning.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Consistency of the group lasso and mult iple kernel learning

Reference 35

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This paper cites Hig h-dimensional additive modeling,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Hig h-dimensional additive modeling,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.320647Z

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This paper cites The asymptotic information in censored s urvival data,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The asymptotic information in censored s urvival data,

Reference 37

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This paper cites Regression models and life-tables,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Regression models and life-tables,

Reference 38

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This paper cites The eﬃciency of cox’s likelihood funct ion for censored data,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The eﬃciency of cox’s likelihood funct ion for censored data,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.264004Z

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Observation 8a26798f-0890-46f4-8122-8dda03b0ba41 · outbound

This paper cites Bayesian inference for cox proportional hazard models with partial likelihoods, nonl inear covariate eﬀects and correlated observations,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Bayesian inference for cox proportional hazard models with partial likelihoods, nonl inear covariate eﬀects and correlated observations,

Reference 40

Resolution: verified exact; doi, observed 2026-08-15T18:25:06.070241Z

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Observation 7f285980-bd59-4176-914b-7256a6ff8180 · outbound

This paper cites On maximum likelihood estima tion of the semi-parametric cox model with time-varying covariates,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On maximum likelihood estima tion of the semi-parametric cox model with time-varying covariates,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.202323Z

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Observation e44bfdfa-5abb-4241-89e0-21a8a14e826a · outbound

This paper cites D oubly robust estimation un- der a possibly misspeciﬁed marginal structural cox model,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment D oubly robust estimation un- der a possibly misspeciﬁed marginal structural cox model,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.180274Z

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Observation bc35961f-d971-4f05-9149-ba5aa8a612b7 · outbound

This paper cites Identiﬁability of parameters in latent structure models with many observed variables,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Identiﬁability of parameters in latent structure models with many observed variables,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.121488Z

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Observation 430006a7-e4e2-4f39-9c74-2d4898143338 · outbound

This paper cites Machine learn- ing approaches to evaluate heterogeneous treatment eﬀects i n randomized controlled trials: a 42 scoping review,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Machine learn- ing approaches to evaluate heterogeneous treatment eﬀects i n randomized controlled trials: a 42 scoping review,

Reference 44

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Observation 56b6e9d3-9120-4f20-838f-bd38be3f716a · outbound

This paper cites On the ma ximum penalized likelihood ap- proach for proportional hazard models with right censored s urvival data,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On the ma ximum penalized likelihood ap- proach for proportional hazard models with right censored s urvival data,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.157582Z

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Observation e7dbad0b-3858-4ca8-b1b9-43462cc3dd79 · outbound

This paper cites Nonparametri c ﬁnite translation hidden markov models and extensions,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Nonparametri c ﬁnite translation hidden markov models and extensions,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.045100Z

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Observation 80ef1132-7f5e-400e-aeab-ca77c16a7b43 · outbound

This paper cites Parameter identiﬁability of discrete bayesian networks with hidden v ariables,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Parameter identiﬁability of discrete bayesian networks with hidden v ariables,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.094085Z

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Observation 50f0e538-6e5c-4f08-a1e6-98cf5fbd55a1 · outbound

This paper cites Inference in ﬁnit e state space non parametric hidden markov models and applications,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Inference in ﬁnit e state space non parametric hidden markov models and applications,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:07.068220Z

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Observation 0a215ba4-3fff-4751-a990-4b3194357486 · outbound

This paper cites Estimating bayes fa ctors via thermodynamic integration and population mcmc,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Estimating bayes fa ctors via thermodynamic integration and population mcmc,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.970172Z

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Observation 223c9e4a-3964-4dea-b07f-1a4c8f1319b7 · outbound

This paper cites On structural and practical identiﬁability,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On structural and practical identiﬁability,

Reference 50

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Observation 9921f44c-99ff-42a2-918f-d78a05d136df · outbound

This paper cites 25 (Cambridge uni- versity press, 2009).

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment 25 (Cambridge uni- versity press, 2009)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.995972Z

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Observation 4e48feab-bb01-4cf0-b32a-89e69128d3e6 · outbound

This paper cites an unresolved cited work.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

Reference 52

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Observation 17533aaa-4f80-4f67-a633-88efb3d0ecf5 · outbound

This paper cites A widely applicable bayesian informa tion criterion,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment A widely applicable bayesian informa tion criterion,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.944980Z

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Observation 504730ca-e023-4e02-86bb-3d75162d13f4 · outbound

This paper cites A bayesian informat ion criterion for singular models,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment A bayesian informat ion criterion for singular models,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.921324Z

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Observation 9500e47b-29b1-4727-82ab-b23f7b22f3b5 · outbound

This paper cites Kernel independent compone nt analysis,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Kernel independent compone nt analysis,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.846724Z

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Observation 063d1fc9-2406-46d3-b5e4-ce59c7b5452a · outbound

This paper cites , An introduction to sequential Monte Carlo , Vol.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment , An introduction to sequential Monte Carlo , Vol

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.871218Z

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Observation 1a311843-46c3-4ba2-a470-62abc10c8fb6 · outbound

This paper cites Probability asymptotics: notes on notation.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Probability asymptotics: notes on notation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T18:25:05.946906Z

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Observation 9e2cef12-c88a-4c02-b7dc-d56705f03c67 · outbound

This paper cites S tatistical consistency of kernel canonical correlation analysis,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment S tatistical consistency of kernel canonical correlation analysis,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.785402Z

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Observation 4170d6b2-5083-409e-bb8c-71e0b8345a82 · outbound

This paper cites an unresolved cited work.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:25:07.817532Z

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Observation 0924b9bf-8b65-464f-8e87-3bbaac4d4e1c · outbound

This paper cites On the limited memory bfgs method for large scale opti- mization,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On the limited memory bfgs method for large scale opti- mization,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.825793Z

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Observation 5c693531-4b4f-4180-9dc3-dcb6891aaf3a · outbound

This paper cites 2 (MIT press Cambridge, MA, 2006).

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment 2 (MIT press Cambridge, MA, 2006)

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.806157Z

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Observation 722e46da-2210-404d-92a9-4dd4d691ee39 · outbound

This paper cites Theoretical analysis of density ratio estimation,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Theoretical analysis of density ratio estimation,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:25:06.760757Z

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