Methods for categorical data analysis: Illustrating consumer behaviour with relation to organic produce

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F71226401%3A_____%2F20%3AN0100411" target="_blank" >RIV/71226401:_____/20:N0100411 - isvavai.cz</a>
Alternative codes found
RIV/60460709:41110/20:84687 RIV/62156489:43110/20:43918502
Result on the web
<a href="https://ap.pef.czu.cz/en/r-12193-conference-proceedings" target="_blank" >https://ap.pef.czu.cz/en/r-12193-conference-proceedings</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Methods for categorical data analysis: Illustrating consumer behaviour with relation to organic produce
Original language description
A description of consumers’ shopping habits based on categorical data interpretation and modelling (source of data: an extensive survey), with special focus on different groups of consumers (age, gender, income, and education etc. specific) purchasing organic products. The survey outcomes were analysed using the contingency tables analysis, including the Pearson’s chi-square test. Correspondence analysis enabled graphic representations of the resulting dependencies. Correspondence analysis represents a popular method often employed in order to analyse the associations between individual categories of variable(s) in contingency tables. The correspondence analysis mechanisms allow for the description of the associations between nominal or ordinal variables and their graphical presentation in multidimensional space. The influence of several predictors on one predicted variable was tested through logistic regression; the model parameters were estimated by the Maximum Likelihood Estimation. Relevant methods for categorical data processing indicated the dependency of organic produce purchase frequency on age, income, gender, household size and municipality of respondent.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
AGRARIAN PERSPECTIVES XXIX. TRENDS AND CHALLENGES OF AGRARIAN SECTOR
ISBN
978-80-213-3041-2
ISSN
2464-4781
e-ISSN
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Number of pages
441
Pages from-to
426-433
Publisher name
Czech University of Life Sciences Prague
Place of publication
Praha
Event location
Prague, Czech Republic
Event date
Sep 16, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000651198600051

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