Missing data in clinical trials
dc.contributor.advisor | Valge, Marju, juhendaja | |
dc.contributor.advisor | Korhonen, Pasi Antero, juhendaja | |
dc.contributor.author | Kadastik, Birgit | |
dc.contributor.other | Tartu Ülikool. Matemaatika ja statistika instituut | et |
dc.contributor.other | Tartu Ülikool. Loodus- ja täppisteaduste valdkond | et |
dc.date.accessioned | 2016-07-07T09:02:54Z | |
dc.date.available | 2016-07-07T09:02:54Z | |
dc.date.issued | 2016 | |
dc.description.abstract | The aim of this Bachelor’s Thesis is to explain what missing data means and give some ways to deal with it in clinical trials. Firstly, an overview of different types of missing data is given and the reasons for their occurrence. Second part of the thesis explains which analytical approaches can be used to conduct an unbiased analysis. Further, missing data are simulated for a data set to show how the approaches described are used in practice with SAS software. | en |
dc.identifier.uri | http://hdl.handle.net/10062/52398 | |
dc.language.iso | en | en |
dc.subject | clinical trials | en |
dc.subject | complete case analysis | en |
dc.subject | missing at random | en |
dc.subject | missing completely at random | en |
dc.subject | missing data | en |
dc.subject | multiple imputation | en |
dc.subject | SAS | en |
dc.subject | kliinilised uuringud | et |
dc.subject | täielike andmetega analüüs | et |
dc.subject | juhuslik puudumine | et |
dc.subject | täiesti juhuslik puudumine | et |
dc.subject | puuduvad andmed | et |
dc.subject | mitmene asendamine | et |
dc.subject.other | bakalaureusetööd | et |
dc.title | Missing data in clinical trials | en |
dc.type | Thesis | en |