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dc.contributor.authorŘíha, David
dc.contributor.authorStros, Michael
dc.date.accessioned2019-02-22T09:13:32Z
dc.date.available2019-02-22T09:13:32Z
dc.date.issued2018
dc.identifier.citationTrendy v podnikání = Business trends : vědecký časopis Fakulty ekonomické ZČU v Plzni. 2018, č. 1, roč. 8, s. 45-55.cs
dc.identifier.issn1805-0603
dc.identifier.urihttp://hdl.handle.net/11025/31019
dc.identifier.urihttps://drive.google.com/drive/folders/1LxJN4JSfOhOxX_FK0xL7D4baGf4iQOAn
dc.format11 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherZápadočeská univerzita v Plznics
dc.relation.ispartofseriesTrendy v podnikánícs
dc.rights© Západočeská univerzita v Plznics
dc.subjectanalýza podnikových datcs
dc.subjectheterogenní datový setcs
dc.subjecthierarchický lineární modelcs
dc.subjectvícenásobná regresecs
dc.titleLinear models based on business data from the pharmaceutical industryen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThis article describes the analysis of heterogeneous market data. For this purpose, the most relevant methodological aspects are discussed and analyses using a hierarchical linear model and multiple regression are presented. In the first step, the applied data set is presented, and the assumed hierarchical two-level structure is shown. The data are then prepared for the analysis. The data are checked for outliers, a multicollinearity check is conducted, a new variable introduced, missing values are replaced by estimated values, a transformation procedure is conducted in order to obtain normality, the data are aggregated for each hierarchical level and a sample size test is performed. The results of both methods are discussed. Finally, it is concluded that whereas the application of a hierarchical linear model appears to be one option, a multiple regression analysis can be employed instead if the quality of the data, especially the sample size, is not sufficient.en
dc.subject.translatedbusiness data analysisen
dc.subject.translatedheterogeneous data seten
dc.subject.translatedhierarchical linear modelen
dc.subject.translatedmultiple regressionen
dc.identifier.doihttps://doi.org/10.24132/jbt.2018.8.1.45_55
dc.type.statusPeer-revieweden
Appears in Collections:Číslo 1 (2018)
Číslo 1 (2018)

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