Developing a prognostic model in the presence of missing data: an ovarian cancer case study.
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Predicting stillbirth in a low resource setting.ASCORE: an up-to-date cardiovascular risk score for hypertensive patients reflecting contemporary clinical practice developed using the (ASCOT-BPLA) trial data.Survival analysis Part III: multivariate data analysis -- choosing a model and assessing its adequacy and fit.On the performance of multiple imputation based on chained equations in tackling missing data of the African α3.7 -globin deletion in a malaria association studyVariable selection under multiple imputation using the bootstrap in a prognostic studyThe estimation and use of predictions for the assessment of model performance using large samples with multiply imputed data.Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines.Modelling relative survival in the presence of incomplete data: a tutorial.Could baseline health-related quality of life (QoL) predict overall survival in metastatic colorectal cancer? The results of the GERCOR OPTIMOX 1 study.The search for stable prognostic models in multiple imputed data sets.Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study.Modeling prognostic factors in resectable pancreatic adenocarcinomas.An independent and external validation of QRISK2 cardiovascular disease risk score: a prospective open cohort studyDeveloping a multivariable prognostic model for pancreatic endocrine tumors using the clinical data warehouse resources of a single institution.Prediction of persistent shoulder pain in general practice: comparing clinical consensus from a Delphi procedure with a statistical scoring system.Developing a predictive tool for psychological well-being among Chinese adolescents in the presence of missing data.Validation, revision and extension of the Mantle Cell Lymphoma International Prognostic Index in a population-based setting.Predicting early mortality in adult trauma patients admitted to three public university hospitals in urban India: a prospective multicentre cohort study.Estimation and external validation of a new prognostic model for predicting recurrence-free survival for early breast cancer patients in the UK.Multiple imputation in survival models: applied on breast cancer dataDo children with central venous line (CVL) dysfunction have increased risk of symptomatic thromboembolism compared to those without CVL-dysfunction, while on cancer therapy?Prophylaxis against de novo hepatitis B for liver transplantation utilizing hep B core (+) donors: does hepatitis B immunoglobulin provide a survival advantage?Predictors of survival after resection of retroperitoneal sarcoma: a population-based analysis and critical appraisal of the AJCC staging system.Application of hazard models for patients with breast cancer in Cuba.Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes.Tuning multiple imputation by predictive mean matching and local residual draws.Survival analysis part IV: further concepts and methods in survival analysisAdherence to extended postpartum antiretrovirals is associated with decreased breast milk HIV-1 transmission.Survival of patients with nonseminomatous germ cell cancer: a review of the IGCC classification by Cox regression and recursive partitioning.Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study.Identifying patients with undetected colorectal cancer: an independent validation of QCancer (Colorectal).Extended prediction rule to optimise early detection of heart failure in older persons with non-acute shortness of breath: a cross-sectional study.Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2.Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore.An introduction to statistical methods used in binary outcome modeling.Proportional hazards regression in the presence of missing study eligibility informationPrognostic models: a methodological framework and review of models for breast cancer.Predicting risk of osteoporotic fracture in men and women in England and Wales: prospective derivation and validation of QFractureScores.The science of risk models.A comparison of imputation techniques for handling missing predictor values in a risk model with a binary outcome.
P2860
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P2860
Developing a prognostic model in the presence of missing data: an ovarian cancer case study.
description
2003 nî lūn-bûn
@nan
2003 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2003 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2003年の論文
@ja
2003年学术文章
@wuu
2003年学术文章
@zh-cn
2003年学术文章
@zh-hans
2003年学术文章
@zh-my
2003年学术文章
@zh-sg
2003年學術文章
@yue
name
Developing a prognostic model ...... an ovarian cancer case study.
@ast
Developing a prognostic model ...... an ovarian cancer case study.
@en
type
label
Developing a prognostic model ...... an ovarian cancer case study.
@ast
Developing a prognostic model ...... an ovarian cancer case study.
@en
prefLabel
Developing a prognostic model ...... an ovarian cancer case study.
@ast
Developing a prognostic model ...... an ovarian cancer case study.
@en
P1476
Developing a prognostic model ...... an ovarian cancer case study.
@en
P2093
Taane G Clark
P356
10.1016/S0895-4356(02)00539-5
P577
2003-01-01T00:00:00Z