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@inproceedings{1187941, author = {Žáková Talpová, Sylva}, address = {Reading, UK}, booktitle = {Proceedings of the 13th European Conference on Research Methodology for Business and Management Studies ECRM 2014}, editor = {Ann Brown and Martin Rich}, keywords = {logistic regression; management; binary dependent variable}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Reading, UK}, isbn = {978-1-909507-61-6}, pages = {348-356}, publisher = {Academic Conferences and Publishing International Limited}, title = {Logistic Regression: An Option for a Management Research?}, url = {http://academic-conferences.org/pdfs/ECRM_2014_Abstract-booklet.pdf}, year = {2014} }
TY - JOUR ID - 1187941 AU - Žáková Talpová, Sylva PY - 2014 TI - Logistic Regression: An Option for a Management Research? PB - Academic Conferences and Publishing International Limited CY - Reading, UK SN - 9781909507616 KW - logistic regression KW - management KW - binary dependent variable UR - http://academic-conferences.org/pdfs/ECRM_2014_Abstract-booklet.pdf L2 - http://academic-conferences.org/pdfs/ECRM_2014_Abstract-booklet.pdf N2 - Many research problems in management science call for the analysis and prediction of a dichotomous outcome. Logistic regression is a technique developed for analyzing data with categorical dependent variables. It is widely used in biomedical research and has recently, been employed in other fields such as ecology, meteorology, business and finance, and educational research. However, the application of this technique in management science remains rare, perhaps in consequence of a dearth of literature addressing the specifics of logistic regression and its consequences that might set possible users on the right path. Moreover, consensus on how the results of logistic regression should be reported is often lacking. This article introduces what logistic regression may be able to do for management science. Issues specific to the application of logistic regression are discussed, as are possible problems with interpretation, and guidelines and recommendations for the employment of logistic regression in the management sciences are provided. The theoretical overview is supported by a practical example of the application of logistic regression in the management sciences. ER -
ŽÁKOVÁ TALPOVÁ, Sylva. Logistic Regression: An Option for a Management Research?. Online. In Ann Brown and Martin Rich. \textit{Proceedings of the 13th European Conference on Research Methodology for Business and Management Studies ECRM 2014}. Reading, UK: Academic Conferences and Publishing International Limited, 2014, p.~348-356. ISBN~978-1-909507-61-6.
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