Full metadata record
DC FieldValueLanguage
dc.contributor.authorŘíha, David
dc.contributor.authorStros, Michael
dc.identifier.citationTrendy v podnikání = Business trends : vědecký časopis Fakulty ekonomické ZČU v Plzni. 2018, č. 1, roč. 8, s. 45-55.cs
dc.format11 s.cs
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.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
Appears in Collections:Číslo 1 (2018)
Číslo 1 (2018)

Files in This Item:
File Description SizeFormat 
6_Riha_Stros.pdfPlný text249,29 kBAdobe PDFView/Open

Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/31019

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.