<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Carter KW</submitter><funding>Lundbeck Foundation</funding><pagination>408-416</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC4864874</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>45(2)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Research studies exploring the determinants of disease require sufficient statistical power to detect meaningful effects. Sample size is often increased through centralized pooling of disparately located datasets, though ethical, privacy and data ownership issues can often hamper this process. Methods that facilitate the sharing of research data that are sympathetic with these issues and which allow flexible and detailed statistical analyses are therefore in critical need. We have created a software platform for the Virtual Pooling and Analysis of Research data (ViPAR), which employs free and open source methods to provide researchers with a web-based platform to analyse datasets housed in disparate locations.&lt;h4>Methods&lt;/h4>Database federation permits controlled access </pubmed_abstract><journal>International journal of epidemiology</journal><pubmed_title>ViPAR: a software platform for the Virtual Pooling and Analysis of Research Data.</pubmed_title><pmcid>PMC4864874</pmcid><funding_grant_id>R155-2014-1724</funding_grant_id><pubmed_authors>Sourander A</pubmed_authors><pubmed_authors>Steadman C</pubmed_authors><pubmed_authors>Petersson G</pubmed_authors><pubmed_authors>Gissler M</pubmed_authors><pubmed_authors>Carter KW</pubmed_authors><pubmed_authors>Susser E</pubmed_authors><pubmed_authors>Suren P</pubmed_authors><pubmed_authors>Reichenberg A</pubmed_authors><pubmed_authors>Schendel DE</pubmed_authors><pubmed_authors>Sandin S</pubmed_authors><pubmed_authors>Hammond G</pubmed_authors><pubmed_authors>Hornig M</pubmed_authors><pubmed_authors>Langridge A</pubmed_authors><pubmed_authors>Newman S</pubmed_authors><pubmed_authors>Gross R</pubmed_authors><pubmed_authors>Sylvester Vethanayagam A</pubmed_authors><pubmed_authors>Schalkwyk L</pubmed_authors><pubmed_authors>Suominen A</pubmed_authors><pubmed_authors>Parner ET</pubmed_authors><pubmed_authors>Francis RW</pubmed_authors><pubmed_authors>Hultman CM</pubmed_authors><pubmed_authors>Yusof Z</pubmed_authors><pubmed_authors>International Collaboration for Autism Registry Epidemiology</pubmed_authors><pubmed_authors>Gunnes N</pubmed_authors><pubmed_authors>Huttunen J</pubmed_authors><pubmed_authors>Gronborg TK</pubmed_authors><pubmed_authors>Bresnahan M</pubmed_authors><pubmed_authors>Leonard H</pubmed_authors><pubmed_authors>Stoltenberg C</pubmed_authors></additional><is_claimable>false</is_claimable><name>ViPAR: a software platform for the Virtual Pooling and Analysis of Research Data.</name><description>&lt;h4>Background&lt;/h4>Research studies exploring the determinants of disease require sufficient statistical power to detect meaningful effects. Sample size is often increased through centralized pooling of disparately located datasets, though ethical, privacy and data ownership issues can often hamper this process. Methods that facilitate the sharing of research data that are sympathetic with these issues and which allow flexible and detailed statistical analyses are therefore in critical need. We have created a software platform for the Virtual Pooling and Analysis of Research data (ViPAR), which employs free and open source methods to provide researchers with a web-based platform to analyse datasets housed in disparate locations.&lt;h4>Methods&lt;/h4>Database federation permits controlled access </description><dates><release>2016-01-01T00:00:00Z</release><publication>2016 Apr</publication><modification>2025-04-19T14:46:15.661Z</modification><creation>2019-03-26T23:05:29Z</creation></dates><accession>S-EPMC4864874</accession><cross_references><pubmed>26452388</pubmed><doi>10.1093/ije/dyv193</doi></cross_references></HashMap>