Sensitivity analysis for nonignorable missingness and outcome misclassification from proxy reports.

about

Statistical analysis with missing exposure data measured by proxy respondents: a misclassification problem within a missing-data problem.Total tooth loss and complete denture use in older adults with intellectual disabilities in Ireland.

P2860

Q30831598-01F8F8DA-D9F4-4DE0-B521-F835DD5581BD Q48260398-0F5FE6AC-5BED-430F-93D5-76CA0E6992FE

P2860

Sensitivity analysis for nonignorable missingness and outcome misclassification from proxy reports.

Item

http://www.wikidata.org/entity/Q36593926

description

2013 nî lūn-bûn

@nan

2013年の論文

@ja

2013年論文

@yue

2013年論文

@zh-hant

2013年論文

@zh-hk

2013年論文

@zh-mo

2013年論文

@zh-tw

2013年论文

@wuu

2013年论文

@zh

2013年论文

@zh-cn

name

Sensitivity analysis for nonig ...... sification from proxy reports.

@ast

Sensitivity analysis for nonig ...... sification from proxy reports.

@en

type

Item

label

Sensitivity analysis for nonig ...... sification from proxy reports.

@ast

Sensitivity analysis for nonig ...... sification from proxy reports.

@en

prefLabel

Sensitivity analysis for nonig ...... sification from proxy reports.

@ast

Sensitivity analysis for nonig ...... sification from proxy reports.

@en

P1476

Sensitivity analysis for nonig ...... sification from proxy reports.

@en

P2093

Barbara Resnick

http://www.w3.org/2001/XMLSchema#string

Gregory E Hicks

http://www.w3.org/2001/XMLSchema#string

Jay Magaziner

http://www.w3.org/2001/XMLSchema#string

Michelle Shardell

http://www.w3.org/2001/XMLSchema#string

P2860

Analysis of clustered and longitudinal binary data subject to response misclassification.

Semi-automated sensitivity analysis to assess systematic errors in observational data.

Are missing outcome data adequately handled? A review of published randomized controlled trials in major medical journals.

Sensitivity analysis using elicited expert information for inference with coarsened data: illustration of censored discrete event times in the AIDS Link to Intravenous Experience (ALIVE) Study.

Sensitivity analysis of informatively coarsened data using pattern mixture models.

Improving propensity score weighting using machine learning.

Pattern-mixture models for analyzing normal outcome data with proxy respondents

Reliability of proxy respondents for patients with stroke: a systematic review.

Using causal diagrams to guide analysis in missing data problems.

A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data with Application to the Breast Cancer Prevention Trial.

P304

215-223

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1097/EDE.0B013E31827F4FA9

http://www.w3.org/2001/XMLSchema#string

P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P50

Luigi Ferrucci

Eleanor M Simonsick

P577

2013-03-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P698

23348065

http://www.w3.org/2001/XMLSchema#string

P921

misclassification

P932

3566762

http://www.w3.org/2001/XMLSchema#string

Sensitivity analysis for nonignorable missingness and outcome misclassification from proxy reports.

about

P2860

P2860

Sensitivity analysis for nonignorable missingness and outcome misclassification from proxy reports.

description

name

type

label

prefLabel

P1433

P1476

P2093

P2860

P304

P31

P356

P433

P478

P50

P577

P698

P921

P932

P356

P1433

P1476

P2093

P2860

P304

P31

P356

P433

P478

P50

P577

P698

P921

P932