Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data | Paper Citation Record

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This paper cites Prediction accuracy and variable selection for penalized cause- specific hazards models.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Prediction accuracy and variable selection for penalized cause- specific hazards models

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Structured fusion lasso penalized multi-state models

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Risk factor identification in heterogeneous disease progression with L1-regularized multi-state models

Reference 3

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Regularized continuous-time Markov model via elastic net

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Boosting multi-state models

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This paper cites A global test for competing risks survival analysis.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data A global test for competing risks survival analysis

Reference 6

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Reduced rank proportional hazards model for competing risks

Reference 7

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This paper cites Reduced-rankproportionalhazardsregressionandsimulation-basedprediction for multi-state models.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Reduced-rankproportionalhazardsregressionandsimulation-basedprediction for multi-state models

Reference 8

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This paper cites Two-sample multistate accelerated sojourn times model.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Two-sample multistate accelerated sojourn times model

Reference 9

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This paper cites Estimationforanacceleratedfailuretimemodelwithintermediatestates as auxiliary information.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Estimationforanacceleratedfailuretimemodelwithintermediatestates as auxiliary information

Reference 10

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This paper cites Regularized estimation in the accelerated failure time model with high-dimensional covariates.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Regularized estimation in the accelerated failure time model with high-dimensional covariates

Reference 11

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This paper cites Generalised linear models for correlated pseudo-observations, with applications to multi-state models.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Generalised linear models for correlated pseudo-observations, with applications to multi-state models

Reference 12

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Penalized generalized estimating equations for high-dimensional longitudinal data analysis

Reference 13

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Variable selection via penalized generalized estimating equations for a marginal survival model

Reference 14

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This paper cites Analysis of survival data with cure fraction and variable selection: A pseudo- observations approach.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Analysis of survival data with cure fraction and variable selection: A pseudo- observations approach

Reference 15

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This paper cites Statisticalmodelsbasedoncountingprocesses.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Statisticalmodelsbasedoncountingprocesses

Reference 16

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This paper cites Multi-state models for event history analysis.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Multi-state models for event history analysis

Reference 17

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This paper cites Tutorial in biostatistics: Competing risks and multi-state models.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Tutorial in biostatistics: Competing risks and multi-state models

Reference 18

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This paper cites The utility of multistate models: a flexible framework for time-to-event data.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data The utility of multistate models: a flexible framework for time-to-event data

Reference 19

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This paper cites Estimation and prediction in a multi-state model for breast cancer.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Estimation and prediction in a multi-state model for breast cancer

Reference 20

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This paper cites Computer methods and programs in biomedicine 2010; 99(3): 261–274.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Computer methods and programs in biomedicine 2010; 99(3): 261–274

Reference 21

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This paper cites L1 penalized estimation in the cox proportional hazards model.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data L1 penalized estimation in the cox proportional hazards model

Reference 22

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Cross-validatedCoxregressiononmicroarray gene expression data

Reference 23

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This paper cites High-Dimensional Cox Models: The Choice of Penalty as Part of the Model Building Process.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data High-Dimensional Cox Models: The Choice of Penalty as Part of the Model Building Process

Reference 24

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This paper cites Variable selection - A review and recommendations for the practicing statistician.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Variable selection - A review and recommendations for the practicing statistician

Reference 25

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This paper cites High-dimensional survival analysis: Methods and applications.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data High-dimensional survival analysis: Methods and applications

Reference 26

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Regression shrinkage and selection via the lasso

Reference 27

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Regularizationandvariableselectionviatheelasticnet

Reference 28

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Sparsity and smoothness via the fused lasso

Reference 29

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data A Sparse-Group Lasso

Reference 30

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Modeling disease progression via fused sparse group lasso

Reference 31

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Ridge regression: Biased estimation for nonorthogonal problems

Reference 32

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This paper cites Flexible methods for analyzing survival data using splines, with applications to breast cancer prognosis.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Flexible methods for analyzing survival data using splines, with applications to breast cancer prognosis

Reference 33

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This paper cites Penalized likelihood in Cox regression.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Penalized likelihood in Cox regression

Reference 34

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data The lasso method for variable selection in the cox model

Reference 35

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This paper cites Regularization paths for Cox’s proportional hazards model via coordinate descent.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Regularization paths for Cox’s proportional hazards model via coordinate descent

Reference 36

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This paper cites Fused lasso algorithm for cox proportional hazards and binomial logit models with application to copy number profiles.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Fused lasso algorithm for cox proportional hazards and binomial logit models with application to copy number profiles

Reference 37

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This paper cites Model selection and estimation in regression with grouped variables.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Model selection and estimation in regression with grouped variables

Reference 38

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Unresolved cited work

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This paper cites Biometrics 2019; 75(4): 1299–1309.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Biometrics 2019; 75(4): 1299–1309

Reference 40

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This paper cites Variableselectionforcox’sproportionalhazardsmodelandfrailtymodel.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Variableselectionforcox’sproportionalhazardsmodelandfrailtymodel

Reference 41

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This paper cites Adualalgorithmforthesolutionofnonlinearvariationalproblemsviafiniteelementapproximation.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Adualalgorithmforthesolutionofnonlinearvariationalproblemsviafiniteelementapproximation

Reference 42

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This paper cites Sur l’approximation, par éléments finis d’ordre un, et la résolution, par pénalisation-dualité d’uneclassedeproblèmesdedirichletnonlinéaires.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Sur l’approximation, par éléments finis d’ordre un, et la résolution, par pénalisation-dualité d’uneclassedeproblèmesdedirichletnonlinéaires

Reference 43

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This paper cites Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

Reference 44

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Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Admm for least square problems with pairwise-difference penalties for coefficient grouping

Reference 45

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This paper cites Alternating direction method with self-adaptive penalty parameters for monotone variational inequalities.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Alternating direction method with self-adaptive penalty parameters for monotone variational inequalities

Reference 46

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This paper cites Regularizationpathsforgeneralizedlinearmodelsviacoordinatedescent.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Regularizationpathsforgeneralizedlinearmodelsviacoordinatedescent

Reference 47

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This paper cites Convexcovariateclusteringforclassification.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Convexcovariateclusteringforclassification

Reference 48

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This paper cites Smoothingnoisydatawithsplinefunctions:estimatingthecorrectdegreeofsmoothingbythemethod of generalized cross-validation.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Smoothingnoisydatawithsplinefunctions:estimatingthecorrectdegreeofsmoothingbythemethod of generalized cross-validation

Reference 49

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This paper cites Generalizedcrossvalidationinvariableselectionwithandwithoutshrinkage.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Generalizedcrossvalidationinvariableselectionwithandwithoutshrinkage

Reference 50

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Observation e8ec0aab-4ed4-473a-8f60-71fe7b3ee1ea · outbound

This paper cites Algorithms for minimization without derivatives.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Algorithms for minimization without derivatives

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.534819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 39b1660c-cba3-4490-9e6f-8606087699bb · outbound

This paper cites Phasesofmethodologicalresearchinbiostatistics—buildingtheevidencebase for new methods.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Phasesofmethodologicalresearchinbiostatistics—buildingtheevidencebase for new methods

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.525301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 419fad7c-597d-41c1-9061-182c10df8017 · outbound

This paper cites Simulationstudiesformethodologicalresearchinpsychology:Astandardizedtemplate for planning, preregistration, and reporting [preprint].

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Simulationstudiesformethodologicalresearchinpsychology:Astandardizedtemplate for planning, preregistration, and reporting [preprint]

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.516667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 90c4d7e3-7fd6-4b16-bf5b-a66bb3d004eb · outbound

This paper cites Using simulation studies to evaluate statistical methods.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Using simulation studies to evaluate statistical methods

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.508079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 253de903-a46d-47f0-b031-4f82a7551d67 · outbound

This paper cites Simulating competing risks data in survival analysis.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Simulating competing risks data in survival analysis

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.499213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7b2a69de-7ee6-4054-ac01-1b0a2a6e314c · outbound

This paper cites an unresolved cited work.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:14:23.489662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9ae1904e-382c-400a-a577-14b35541e47f · outbound

This paper cites Impactofmyelodysplasia-relatedandadditionalgenemutationsinintensivelytreated patients with NPM1-mutated acute myeloid leukemia.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data Impactofmyelodysplasia-relatedandadditionalgenemutationsinintensivelytreated patients with NPM1-mutated acute myeloid leukemia

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.479836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 445fea92-a5b7-4949-bd97-c355df32424c · outbound

This paper cites R: A Language and Environment for Statistical Computing.R Foundation for Statistical Computing;Vienna, Austria: 2024.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data R: A Language and Environment for Statistical Computing.R Foundation for Statistical Computing;Vienna, Austria: 2024

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.470458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3c333ff7-e748-47ee-8387-ed9d08cd34b3 · outbound

This paper cites mstate: An R Package for the Analysis of Competing Risks and Multi-State Models.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data mstate: An R Package for the Analysis of Competing Risks and Multi-State Models

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.460118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 771a6906-a46b-49c4-bc81-207491ba3a28 · outbound

This paper cites penMSM: Estimating Regularized Multi-state Models Using L1 Penalties.2015.

Variable selection via fused sparse-group lasso penalized multi-state models incorporating molecular data penMSM: Estimating Regularized Multi-state Models Using L1 Penalties.2015

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:14:23.448856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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