Models for Ordered Categorical Variables: An Application
Ordered logit and ordered probit models, commonly used ordered categorical variable models, are used when the dependent variable is categorical and ordered. The validity of the predictions of these models depends on the assumption of parallel slopes. These models can be used if the assumption of...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
ORDT: Organization for Research Development and Training
2024-11-01
|
| Series: | Journal of Interdisciplinary Sciences |
| Subjects: | |
| Online Access: | https://journalofinterdisciplinarysciences.com/wp-content/uploads/2024/11/2-Models-for-Ordered-Categorical-Variables-An-Application.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850236015485124608 |
|---|---|
| author | Öznur İşçi Güneri Burcu Durmuş Aynur İncekırık |
| author_facet | Öznur İşçi Güneri Burcu Durmuş Aynur İncekırık |
| author_sort | Öznur İşçi Güneri |
| collection | DOAJ |
| description | Ordered logit and ordered probit models, commonly used ordered categorical variable
models, are used when the dependent variable is categorical and ordered. The validity of the
predictions of these models depends on the assumption of parallel slopes. These models can be used if
the assumption of parallel slopes is met. When this assumption is not met, the generalized ordered
logit/probit model, which is more flexible in terms of assumption, or the multinomial logit model can
be used by ignoring the assumption. In this connection, an exemplary data set was taken, and first of
all, the assumption of parallel slopes was investigated. These models were compared using loglikelihood, Akaike Information Criteria (AIC), and Bayes Information Criteria (BIC) statistics for the
validity of the models. In this way, the lowest log-likelihood, AIC, and BIC values were found for the
generalized logit model. |
| format | Article |
| id | doaj-art-5de3ff53bc4b4ea3909c441df76414b5 |
| institution | OA Journals |
| issn | 2594-3405 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | ORDT: Organization for Research Development and Training |
| record_format | Article |
| series | Journal of Interdisciplinary Sciences |
| spelling | doaj-art-5de3ff53bc4b4ea3909c441df76414b52025-08-20T02:02:05ZengORDT: Organization for Research Development and TrainingJournal of Interdisciplinary Sciences2594-34052024-11-01822445Models for Ordered Categorical Variables: An ApplicationÖznur İşçi Güneri0Burcu Durmuş 1Aynur İncekırık2Department of Statistics, Faculty of Science, Muğla Sıtkı Koçman University, Muğla, TürkiyeDepartment of Statistics, Faculty of Science, Muğla Sıtkı Koçman University, Muğla, TürkiyeDepartment of Econometrics, Faculty of Economics and Administrative Sciences, Manisa Celal Bayar University, Manisa, TürkiyeOrdered logit and ordered probit models, commonly used ordered categorical variable models, are used when the dependent variable is categorical and ordered. The validity of the predictions of these models depends on the assumption of parallel slopes. These models can be used if the assumption of parallel slopes is met. When this assumption is not met, the generalized ordered logit/probit model, which is more flexible in terms of assumption, or the multinomial logit model can be used by ignoring the assumption. In this connection, an exemplary data set was taken, and first of all, the assumption of parallel slopes was investigated. These models were compared using loglikelihood, Akaike Information Criteria (AIC), and Bayes Information Criteria (BIC) statistics for the validity of the models. In this way, the lowest log-likelihood, AIC, and BIC values were found for the generalized logit model.https://journalofinterdisciplinarysciences.com/wp-content/uploads/2024/11/2-Models-for-Ordered-Categorical-Variables-An-Application.pdfordered logit modelordered probit modelgeneralized logit modelgeneralized probit model |
| spellingShingle | Öznur İşçi Güneri Burcu Durmuş Aynur İncekırık Models for Ordered Categorical Variables: An Application Journal of Interdisciplinary Sciences ordered logit model ordered probit model generalized logit model generalized probit model |
| title | Models for Ordered Categorical Variables: An Application |
| title_full | Models for Ordered Categorical Variables: An Application |
| title_fullStr | Models for Ordered Categorical Variables: An Application |
| title_full_unstemmed | Models for Ordered Categorical Variables: An Application |
| title_short | Models for Ordered Categorical Variables: An Application |
| title_sort | models for ordered categorical variables an application |
| topic | ordered logit model ordered probit model generalized logit model generalized probit model |
| url | https://journalofinterdisciplinarysciences.com/wp-content/uploads/2024/11/2-Models-for-Ordered-Categorical-Variables-An-Application.pdf |
| work_keys_str_mv | AT oznurisciguneri modelsfororderedcategoricalvariablesanapplication AT burcudurmus modelsfororderedcategoricalvariablesanapplication AT aynurincekırık modelsfororderedcategoricalvariablesanapplication |