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Imputation of missing variance data using non-linear mixed effects modelling to enable an inverse variance weighted meta-analysis of summary-level longitudinal data: a case study
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Imputation of missing variance data using non-linear mixed effects modelling to enable an inverse variance weighted meta-analysis of summary-level longitudinal data: a case study

Pharmaceutical Statistics, 2012 Jul-Aug, Vol.11(4), pp.318-324 [Peer Reviewed Journal]

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Imputation of missing variance data using non-linear mixed effects modelling to enable an inverse variance weighted meta-analysis of summary-level longitudinal data: a case study.

Pharmaceutical statistics, 2012 Jul-Aug, Vol.11(4), pp.318-324 [Peer Reviewed Journal]

© ProQuest LLC All rights reserved

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Imputation of missing variance data using non-linear mixed effects modelling to enable an inverse variance weighted meta-analysis of summary-level longitudinal data: a case study

Pharmaceutical statistics, 2012, Vol.11(4), pp.318-24 [Peer Reviewed Journal]

MEDLINE/PubMed (U.S. National Library of Medicine)

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Imputation of missing variance data using non-linear mixed effects modelling to enable an inverse variance weighted meta-analysis of summary-level longitudinal data: A case study

Pharmaceutical Statistics, July 2012, Vol.11(4), pp.318-324 [Peer Reviewed Journal]

Scopus (Elsevier B.V)

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