Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data
about
Statistical approaches for evaluating body composition markers in clinical cancer research.The versatility of multi-state models for the analysis of longitudinal data with unobservable features.Dynamic prediction of recurrent events data by landmarking with application to a follow-up study of patients after kidney transplant.Conditional survival and the choice of conditioning set for patients with colon cancer: an analysis of NSABP trials C-03 through C-07.Matching methods for obtaining survival functions to estimate the effect of a time-dependent treatment.Years of life lost due to lower extremity injury in association with dementia, and care need: a 6-year follow-up population-based study using a multi-state approach among German elderlyIncorporating short-term outcome information to predict long-term survival with discrete markers.Time-dependent prognostic score matching for recurrent event analysis to evaluate a treatment assigned during follow-up.Landmark Prediction of Long Term Survival Incorporating Short Term Event Time InformationA two-stage approach for dynamic prediction of time-to-event distributions.Landmark risk prediction of residual life for breast cancer survival.Landmark Estimation of Survival and Treatment Effect in a Randomized Clinical Trial.Application of multistate models in hospital epidemiology: advances and challenges.Review of multistate models in hematopoietic cell transplantation studies.Suggestions on the use of statistical methodologies in studies of the European Group for Blood and Marrow Transplantation.Landmark cure rate models with time-dependent covariates.Dynamic prediction by landmarking in competing risks.Joint multiple imputation for longitudinal outcomes and clinical events that truncate longitudinal follow-up.Disparate rates of acute rejection and donor-specific antibodies among high-immunologic risk renal transplant subgroups receiving antithymocyte globulin induction.Prognostic Significance of Early Tumor Shrinkage Under Second-Line Targeted Therapy for Metastatic Renal Cell Carcinoma: A Retrospective Multi-Institutional Study in Japan.Dynamic pseudo-observations: a robust approach to dynamic prediction in competing risks.Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.Dynamic Prediction of Renal Failure Using Longitudinal Biomarkers in a Cohort Study of Chronic Kidney Disease.Defining therapy goals for major molecular remission in chronic myeloid leukemia: results of the randomized CML Study IV.Reduced rank hazard regression with fixed and time-varying effects of the covariates.
P2860
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P2860
Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data
description
2008 nî lūn-bûn
@nan
2008 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Dynamic predicting by landmark ...... o acute lymphoid leukemia data
@ast
Dynamic predicting by landmark ...... o acute lymphoid leukemia data
@en
type
label
Dynamic predicting by landmark ...... o acute lymphoid leukemia data
@ast
Dynamic predicting by landmark ...... o acute lymphoid leukemia data
@en
prefLabel
Dynamic predicting by landmark ...... o acute lymphoid leukemia data
@ast
Dynamic predicting by landmark ...... o acute lymphoid leukemia data
@en
P2860
P1476
Dynamic predicting by landmark ...... o acute lymphoid leukemia data
@en
P2093
Hans C van Houwelingen
Hein Putter
P2860
P2888
P304
P356
10.1007/S10985-008-9099-8
P577
2008-10-03T00:00:00Z