An application of maximum likelihood and generalized estimating equations to the analysis of ordinal data from a longitudinal study with cases missing at random.
about
Modelling ordered categorical data: recent advances and future challenges.Marginal modelling of multivariate categorical data.Missing data perspectives of the fluvoxamine data set: a review.Impact of missing data due to drop-outs on estimators for rates of change in longitudinal studies: a simulation study.Sensitivity analysis of longitudinal binary quality of life data with drop-out: an example using the EORTC QLQ-C30.Complete imputation of missing repeated categorical data: one-sample applications.A local influence approach applied to binary data from a psychiatric study.A transition model for ordinal response data with random dropout: an application to the fluvoxamine data.Semiparametric regression models and sensitivity analysis of longitudinal data with nonrandom dropouts.Interpretation of mixed models and marginal models with cohort attrition due to death and drop-out.Mixed models approaches for joint modeling of different types of responses.Analysis of the progression of systolic blood pressure using imputation of missing phenotype values.A global sensitivity test for evaluating statistical hypotheses with nonidentifiable models.Proportional-odds models for repeated composite and long ordinal outcome scales.A joint marginal-conditional model for multivariate longitudinal data.Dropouts in longitudinal studies: definitions and models.Effect of a Health Care Professional Communication Training Intervention on Adolescent Human Papillomavirus Vaccination: A Cluster Randomized Clinical Trial.Comparison of statistical approaches for analyzing incomplete longitudinal patient-reported outcome data in randomized controlled trials.A comparison of psychological well-being and quality of life between spouse and non-spouse caregivers in patients with head and neck cancer: a 6-month follow-up study.ICT Activity, Innovation and Productivity: An Analysis of Data From Australian BusinessesAssessing uncertainty about parameter estimates with incomplete repeated ordinal data
P2860
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P2860
An application of maximum likelihood and generalized estimating equations to the analysis of ordinal data from a longitudinal study with cases missing at random.
description
1994 nî lūn-bûn
@nan
1994年の論文
@ja
1994年論文
@yue
1994年論文
@zh-hant
1994年論文
@zh-hk
1994年論文
@zh-mo
1994年論文
@zh-tw
1994年论文
@wuu
1994年论文
@zh
1994年论文
@zh-cn
name
An application of maximum like ...... with cases missing at random.
@ast
An application of maximum like ...... with cases missing at random.
@en
type
label
An application of maximum like ...... with cases missing at random.
@ast
An application of maximum like ...... with cases missing at random.
@en
prefLabel
An application of maximum like ...... with cases missing at random.
@ast
An application of maximum like ...... with cases missing at random.
@en
P2093
P356
P1433
P1476
An application of maximum like ...... with cases missing at random.
@en
P2093
Kenward MG
Lesaffre E
Molenberghs G
P304
P356
10.2307/2533434
P407
P577
1994-12-01T00:00:00Z