Multilevel logistic regression models with each negative emotions as a predictor.
<p>Multilevel logistic regression models with each negative emotions as a predictor.</p>
সংরক্ষণ করুন:
| প্রধান লেখক: | |
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| অন্যান্য লেখক: | , , , , , |
| প্রকাশিত: |
2025
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| _version_ | 1849927628984680448 |
|---|---|
| author | Chan-Young Ahn (22683343) |
| author2 | Jin-Ha Kim (10300456) Sojung Kim (46675) Jae-Won Kim (172504) Jung-Jo Na (22683346) Dong Gi Seo (11119119) Jong-Sun Lee (4252801) |
| author2_role | author author author author author author |
| author_facet | Chan-Young Ahn (22683343) Jin-Ha Kim (10300456) Sojung Kim (46675) Jae-Won Kim (172504) Jung-Jo Na (22683346) Dong Gi Seo (11119119) Jong-Sun Lee (4252801) |
| author_role | author |
| dc.creator.none.fl_str_mv | Chan-Young Ahn (22683343) Jin-Ha Kim (10300456) Sojung Kim (46675) Jae-Won Kim (172504) Jung-Jo Na (22683346) Dong Gi Seo (11119119) Jong-Sun Lee (4252801) |
| dc.date.none.fl_str_mv | 2025-11-25T18:27:18Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0320104.t004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Multilevel_logistic_regression_models_with_each_negative_emotions_as_a_predictor_/30713653 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Sociology Mental Health Biological Sciences not elsewhere classified xlink "> non providing practical insights multilevel logistic regression low ecological validity justifying multilevel modeling experimental methods rely ecological momentary assessment address social connections 26 indicated substantial identify emotional predictors adolescents &# 8217 repeatedly sample nssi significant individual differences combining machine learning anger towards others experiencing nssi thoughts 40 ), anxiety findings highlight loneliness significant predictors machine learning nssi thoughts individual variance adolescents engaging 18 ), therefore vulnerable study aimed smartphone application related feelings past year participants reported often linked negative emotions integrated application influential predictor icc value feature importance developing tailored daily life autobiographical recall 15 years |
| dc.title.none.fl_str_mv | Multilevel logistic regression models with each negative emotions as a predictor. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Multilevel logistic regression models with each negative emotions as a predictor.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_edc0e08ad531925386b50c7c84f4e24a |
| identifier_str_mv | 10.1371/journal.pone.0320104.t004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30713653 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Multilevel logistic regression models with each negative emotions as a predictor.Chan-Young Ahn (22683343)Jin-Ha Kim (10300456)Sojung Kim (46675)Jae-Won Kim (172504)Jung-Jo Na (22683346)Dong Gi Seo (11119119)Jong-Sun Lee (4252801)MedicineSociologyMental HealthBiological Sciences not elsewhere classifiedxlink "> nonproviding practical insightsmultilevel logistic regressionlow ecological validityjustifying multilevel modelingexperimental methods relyecological momentary assessmentaddress social connections26 indicated substantialidentify emotional predictorsadolescents &# 8217repeatedly sample nssisignificant individual differencescombining machine learninganger towards othersexperiencing nssi thoughts40 ), anxietyfindings highlight lonelinesssignificant predictorsmachine learningnssi thoughtsindividual varianceadolescents engaging18 ),therefore vulnerablestudy aimedsmartphone applicationrelated feelingspast yearparticipants reportedoften linkednegative emotionsintegrated applicationinfluential predictoricc valuefeature importancedeveloping tailoreddaily lifeautobiographical recall15 years<p>Multilevel logistic regression models with each negative emotions as a predictor.</p>2025-11-25T18:27:18ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0320104.t004https://figshare.com/articles/dataset/Multilevel_logistic_regression_models_with_each_negative_emotions_as_a_predictor_/30713653CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307136532025-11-25T18:27:18Z |
| spellingShingle | Multilevel logistic regression models with each negative emotions as a predictor. Chan-Young Ahn (22683343) Medicine Sociology Mental Health Biological Sciences not elsewhere classified xlink "> non providing practical insights multilevel logistic regression low ecological validity justifying multilevel modeling experimental methods rely ecological momentary assessment address social connections 26 indicated substantial identify emotional predictors adolescents &# 8217 repeatedly sample nssi significant individual differences combining machine learning anger towards others experiencing nssi thoughts 40 ), anxiety findings highlight loneliness significant predictors machine learning nssi thoughts individual variance adolescents engaging 18 ), therefore vulnerable study aimed smartphone application related feelings past year participants reported often linked negative emotions integrated application influential predictor icc value feature importance developing tailored daily life autobiographical recall 15 years |
| status_str | publishedVersion |
| title | Multilevel logistic regression models with each negative emotions as a predictor. |
| title_full | Multilevel logistic regression models with each negative emotions as a predictor. |
| title_fullStr | Multilevel logistic regression models with each negative emotions as a predictor. |
| title_full_unstemmed | Multilevel logistic regression models with each negative emotions as a predictor. |
| title_short | Multilevel logistic regression models with each negative emotions as a predictor. |
| title_sort | Multilevel logistic regression models with each negative emotions as a predictor. |
| topic | Medicine Sociology Mental Health Biological Sciences not elsewhere classified xlink "> non providing practical insights multilevel logistic regression low ecological validity justifying multilevel modeling experimental methods rely ecological momentary assessment address social connections 26 indicated substantial identify emotional predictors adolescents &# 8217 repeatedly sample nssi significant individual differences combining machine learning anger towards others experiencing nssi thoughts 40 ), anxiety findings highlight loneliness significant predictors machine learning nssi thoughts individual variance adolescents engaging 18 ), therefore vulnerable study aimed smartphone application related feelings past year participants reported often linked negative emotions integrated application influential predictor icc value feature importance developing tailored daily life autobiographical recall 15 years |