Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.

<p>Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.</p>

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主要作者: Anubhuti Shukla (12152228) (author)
其他作者: Bhavya Vaishnavi Amrutham (22676313) (author), Sheetal Manchanda (16951417) (author)
出版: 2025
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author Anubhuti Shukla (12152228)
author2 Bhavya Vaishnavi Amrutham (22676313)
Sheetal Manchanda (16951417)
author2_role author
author
author_facet Anubhuti Shukla (12152228)
Bhavya Vaishnavi Amrutham (22676313)
Sheetal Manchanda (16951417)
author_role author
dc.creator.none.fl_str_mv Anubhuti Shukla (12152228)
Bhavya Vaishnavi Amrutham (22676313)
Sheetal Manchanda (16951417)
dc.date.none.fl_str_mv 2025-11-24T18:23:56Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0337471.t002
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Regression_model_using_Generalized_Linear_equation_age_ethnicity_primary_language_location_and_insurance_status_on_preventive_dental_services_utilization_/30696579
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biotechnology
Evolutionary Biology
Science Policy
Virology
Biological Sciences not elsewhere classified
urban zip code
preventive dental services
year dental students
younger age group
older age group
indiana university school
xlink "> inequities
demographic variables among
based clinical rotations
indiana </ p
xlink ">
identified among
demographic characteristics
d4 students
via redcap
underserved population
study utilizes
private practices
multicultural ethnicities
insurance status
every patient
descriptive statistics
72 ).
17 years
&# 8221
&# 8220
dc.title.none.fl_str_mv Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <p>Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.</p>
eu_rights_str_mv openAccess
id Manara_70cac54c8ee3463e1d6357aa6e7c08ee
identifier_str_mv 10.1371/journal.pone.0337471.t002
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/30696579
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.Anubhuti Shukla (12152228)Bhavya Vaishnavi Amrutham (22676313)Sheetal Manchanda (16951417)BiotechnologyEvolutionary BiologyScience PolicyVirologyBiological Sciences not elsewhere classifiedurban zip codepreventive dental servicesyear dental studentsyounger age groupolder age groupindiana university schoolxlink "> inequitiesdemographic variables amongbased clinical rotationsindiana </ pxlink ">identified amongdemographic characteristicsd4 studentsvia redcapunderserved populationstudy utilizesprivate practicesmulticultural ethnicitiesinsurance statusevery patientdescriptive statistics72 ).17 years&# 8221&# 8220<p>Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.</p>2025-11-24T18:23:56ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0337471.t002https://figshare.com/articles/dataset/Regression_model_using_Generalized_Linear_equation_age_ethnicity_primary_language_location_and_insurance_status_on_preventive_dental_services_utilization_/30696579CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306965792025-11-24T18:23:56Z
spellingShingle Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
Anubhuti Shukla (12152228)
Biotechnology
Evolutionary Biology
Science Policy
Virology
Biological Sciences not elsewhere classified
urban zip code
preventive dental services
year dental students
younger age group
older age group
indiana university school
xlink "> inequities
demographic variables among
based clinical rotations
indiana </ p
xlink ">
identified among
demographic characteristics
d4 students
via redcap
underserved population
study utilizes
private practices
multicultural ethnicities
insurance status
every patient
descriptive statistics
72 ).
17 years
&# 8221
&# 8220
status_str publishedVersion
title Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
title_full Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
title_fullStr Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
title_full_unstemmed Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
title_short Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
title_sort Regression model using Generalized Linear equation (age, ethnicity, primary language, location, and insurance status) on preventive dental services utilization.
topic Biotechnology
Evolutionary Biology
Science Policy
Virology
Biological Sciences not elsewhere classified
urban zip code
preventive dental services
year dental students
younger age group
older age group
indiana university school
xlink "> inequities
demographic variables among
based clinical rotations
indiana </ p
xlink ">
identified among
demographic characteristics
d4 students
via redcap
underserved population
study utilizes
private practices
multicultural ethnicities
insurance status
every patient
descriptive statistics
72 ).
17 years
&# 8221
&# 8220