A study of subgroup identification and micro aggregation

A study of subgroup identification and micro aggregation

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To make treatment decisions that are better for individual patients it is necessary to find patient characteristics where treatments are safer and more effective. It is the case that most drugs do not work for all patients. Also, it is important to be able to make data sets available without those receiving the data set being able to identify individual patients, yet retain the information in the original data set. With greater access to data sets, more people can explore beneficial relationships. Both patient subgroup identification and micro aggregation should improve the overall medical discovery process.

One of the complications of medical research is that humans are very diverse; statistical methods have to work in the presence of human diversity. We have chosen to use a 3x3 factorial design for studying subgroup identifiably. We will study the loss of information as greater micro aggregation is used.

Any discoveries made will be presented orally at statistics conferences and written up in technical reports posted at the National Institute of Statistical Sciences and/or in scholarly journals.

[{ "PostingID": 392, "Title": "GSK-HZA113091", "Description": "A randomised, double-blind, double-dummy, parallel-group multicentre study to assess efficacy and safety of Fluticasone Furoate/GW642444 Inhalation Powder and Fluticasone Propionate/Salmeterol Inhalation Powder in the treatment of persistent asthma in adults and adolescents

Medicine: fluticasone furoate/vilanterol, Condition: Asthma, Phase: 3, Clinical Study ID: HZA113091, Sponsor: GSK" }]

The publication citation will be added after the research is published.