MMRM versus MI in dealing with missing data--a comparison based on 25 NDA data sets (Q33856930)

29 July 2017

title

MMRM versus MI in dealing with missing data--a comparison based on 25 NDA data sets (English)

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29 July 2017

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Ohidul Siddiqui

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29 July 2017

publication date

1 May 2011

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Journal of Biopharmaceutical Statistics

29 July 2017

published in

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volume

21

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issue

3

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page(s)

423-436

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The impact of missing data and how it is handled on the rate of false-positive results in drug development

29 July 2017

cites work

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Type I Error Rates from Mixed Effects Model Repeated Measures versus Fixed Effects Anova with Missing Values Imputed via Last Observation Carried Forward

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Sample Selection Bias as a Specification Error

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Missing data in longitudinal studies

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Random-effects models for longitudinal data

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Handling drop-out in longitudinal clinical trials: a comparison of the LOCF and MMRM approaches.

21 January 2018

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A multiple imputation strategy for clinical trials with truncation of patient data

21 January 2018

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21 January 2018

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The effect of correlation structure on treatment contrasts estimated from incomplete clinical trial data with likelihood-based repeated measures compared with last observation carried forward ANOVA.

21 January 2018

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Accounting for dropout bias using mixed-effects models.

21 January 2018

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A comparison of the random-effects pattern mixture model with last-observation-carried-forward (LOCF) analysis in longitudinal clinical trials with dropouts.

21 January 2018

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Inference and missing data

21 January 2018

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MMRM vs. LOCF: a comprehensive comparison based on simulation study and 25 NDA datasets

21 January 2018

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Estimation and comparison of changes in the presence of informative right censoring: conditional linear model

21 January 2018

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10.1080/10543401003777995

21 January 2018

Identifiers

DOI

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29 July 2017

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