{
"@context": "https://schema.org",
"@graph": [
{
"@type": "MedicalWebPage",
"name": "Modèles économétriques : Questions médicales les plus fréquentes",
"headline": "Modèles économétriques : Comprendre les symptômes, diagnostics et traitements",
"description": "Guide complet et accessible sur les Modèles économétriques : explications, diagnostics, traitements et prévention. Information médicale validée destinée aux patients.",
"datePublished": "2024-05-22",
"dateModified": "2025-02-16",
"inLanguage": "fr",
"medicalAudience": [
{
"@type": "MedicalAudience",
"name": "Grand public",
"audienceType": "Patient",
"healthCondition": {
"@type": "MedicalCondition",
"name": "Modèles économétriques"
},
"suggestedMinAge": 18,
"suggestedGender": "unisex"
},
{
"@type": "MedicalAudience",
"name": "Médecins",
"audienceType": "Physician",
"geographicArea": {
"@type": "AdministrativeArea",
"name": "France"
}
},
{
"@type": "MedicalAudience",
"name": "Chercheurs",
"audienceType": "Researcher",
"geographicArea": {
"@type": "AdministrativeArea",
"name": "International"
}
}
],
"reviewedBy": {
"@type": "Person",
"name": "Dr Olivier Menir",
"jobTitle": "Expert en Médecine",
"description": "Expert en Médecine, Optimisation des Parcours de Soins et Révision Médicale",
"url": "/static/pages/docteur-olivier-menir.html",
"alumniOf": {
"@type": "EducationalOrganization",
"name": "Université Paris Descartes"
}
},
"isPartOf": {
"@type": "MedicalWebPage",
"name": "Modèles économiques",
"url": "https://questionsmedicales.fr/mesh/D018803",
"about": {
"@type": "MedicalCondition",
"name": "Modèles économiques",
"code": {
"@type": "MedicalCode",
"code": "D018803",
"codingSystem": "MeSH"
},
"identifier": {
"@type": "PropertyValue",
"propertyID": "MeSH Tree",
"value": "N06.850.520.830.500.600"
}
}
},
"about": {
"@type": "MedicalCondition",
"name": "Modèles économétriques",
"alternateName": "Models, Econometric",
"code": {
"@type": "MedicalCode",
"code": "D017059",
"codingSystem": "MeSH"
}
},
"author": [
{
"@type": "Person",
"name": "James Heckman",
"url": "https://questionsmedicales.fr/author/James%20Heckman",
"affiliation": {
"@type": "Organization",
"name": "The University of Chicago, Department of Economics, 1126 E. 59 St., Chicago, IL 60637."
}
},
{
"@type": "Person",
"name": "Rodrigo Pinto",
"url": "https://questionsmedicales.fr/author/Rodrigo%20Pinto",
"affiliation": {
"@type": "Organization",
"name": "University of California at Los Angeles, Department of Economics, 315 Portola Plaza, Room 8385, Los Angeles, CA 90095."
}
},
{
"@type": "Person",
"name": "Tamás Krisztin",
"url": "https://questionsmedicales.fr/author/Tam%C3%A1s%20Krisztin",
"affiliation": {
"@type": "Organization",
"name": "International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria."
}
},
{
"@type": "Person",
"name": "Philipp Piribauer",
"url": "https://questionsmedicales.fr/author/Philipp%20Piribauer",
"affiliation": {
"@type": "Organization",
"name": "Austrian Institute of Economic Research (WIFO) Vienna Austria."
}
},
{
"@type": "Person",
"name": "Gagan Deep Sharma",
"url": "https://questionsmedicales.fr/author/Gagan%20Deep%20Sharma",
"affiliation": {
"@type": "Organization",
"name": "University School of Management Studies, Guru Gobind Singh Indraprastha University, New Delhi-110078, India."
}
}
],
"citation": [
{
"@type": "ScholarlyArticle",
"name": "Patient Activeness During Online Medical Consultation in China: Multilevel Analysis.",
"datePublished": "2022-05-27",
"url": "https://questionsmedicales.fr/article/35622403",
"identifier": {
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.2196/35557"
}
},
{
"@type": "ScholarlyArticle",
"name": "Apical periodontitis and associated factors in a rural population of southern Brazil: a multilevel analysis.",
"datePublished": "2023-02-06",
"url": "https://questionsmedicales.fr/article/36746818",
"identifier": {
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.1007/s00784-023-04886-7"
}
},
{
"@type": "ScholarlyArticle",
"name": "A multilevel analysis of trends and predictors associated with teenage pregnancy in Zambia (2001-2018).",
"datePublished": "2023-01-18",
"url": "https://questionsmedicales.fr/article/36653839",
"identifier": {
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.1186/s12978-023-01567-2"
}
},
{
"@type": "ScholarlyArticle",
"name": "Globalization and social distance: Multilevel analysis of attitudes toward immigrants in the European Union.",
"datePublished": "2022-10-03",
"url": "https://questionsmedicales.fr/article/36190963",
"identifier": {
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.1371/journal.pone.0274988"
}
},
{
"@type": "ScholarlyArticle",
"name": "Antenatal and postnatal factors associated with neonatal death in the Indian subcontinent: a multilevel analysis.",
"datePublished": "2023-06-08",
"url": "https://questionsmedicales.fr/article/37300975",
"identifier": {
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.1016/j.puhe.2023.05.004"
}
}
],
"breadcrumb": {
"@type": "BreadcrumbList",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "questionsmedicales.fr",
"item": "https://questionsmedicales.fr"
},
{
"@type": "ListItem",
"position": 2,
"name": "Environnement et santé publique",
"item": "https://questionsmedicales.fr/mesh/D004778"
},
{
"@type": "ListItem",
"position": 3,
"name": "Santé publique",
"item": "https://questionsmedicales.fr/mesh/D011634"
},
{
"@type": "ListItem",
"position": 4,
"name": "Méthodes épidémiologiques",
"item": "https://questionsmedicales.fr/mesh/D004812"
},
{
"@type": "ListItem",
"position": 5,
"name": "Statistiques comme sujet",
"item": "https://questionsmedicales.fr/mesh/D013223"
},
{
"@type": "ListItem",
"position": 6,
"name": "Modèles statistiques",
"item": "https://questionsmedicales.fr/mesh/D015233"
},
{
"@type": "ListItem",
"position": 7,
"name": "Modèles économiques",
"item": "https://questionsmedicales.fr/mesh/D018803"
},
{
"@type": "ListItem",
"position": 8,
"name": "Modèles économétriques",
"item": "https://questionsmedicales.fr/mesh/D017059"
}
]
}
},
{
"@type": "MedicalWebPage",
"name": "Article complet : Modèles économétriques - Questions et réponses",
"headline": "Questions et réponses médicales fréquentes sur Modèles économétriques",
"description": "Une compilation de questions et réponses structurées, validées par des experts médicaux.",
"datePublished": "2025-05-05",
"inLanguage": "fr",
"hasPart": [
{
"@type": "MedicalWebPage",
"name": "Diagnostic",
"headline": "Diagnostic sur Modèles économétriques",
"description": "Comment identifier un modèle économétrique approprié ?\nQuels tests sont utilisés pour valider un modèle ?\nQu'est-ce qu'un modèle de régression ?\nComment évaluer la performance d'un modèle ?\nQu'est-ce qu'un modèle à variables instrumentales ?",
"url": "https://questionsmedicales.fr/mesh/D017059?mesh_terms=Multilevel+Analysis&page=3#section-diagnostic"
},
{
"@type": "MedicalWebPage",
"name": "Symptômes",
"headline": "Symptômes sur Modèles économétriques",
"description": "Quels sont les signes d'un modèle mal spécifié ?\nComment détecter l'hétéroscédasticité ?\nQuels effets peut avoir la multicolinéarité ?\nQu'est-ce qu'un biais d'échantillonnage ?\nQuels sont les signes d'une autocorrélation ?",
"url": "https://questionsmedicales.fr/mesh/D017059?mesh_terms=Multilevel+Analysis&page=3#section-symptômes"
},
{
"@type": "MedicalWebPage",
"name": "Prévention",
"headline": "Prévention sur Modèles économétriques",
"description": "Comment éviter les biais dans les modèles ?\nQuelles pratiques pour une bonne collecte de données ?\nComment choisir les bonnes variables ?\nQuelles sont les bonnes pratiques de modélisation ?\nComment éviter le surajustement ?",
"url": "https://questionsmedicales.fr/mesh/D017059?mesh_terms=Multilevel+Analysis&page=3#section-prévention"
},
{
"@type": "MedicalWebPage",
"name": "Traitements",
"headline": "Traitements sur Modèles économétriques",
"description": "Comment corriger l'hétéroscédasticité ?\nQuelles méthodes pour traiter la multicolinéarité ?\nComment améliorer un modèle économétrique ?\nQu'est-ce que la régularisation ?\nComment utiliser des modèles de séries temporelles ?",
"url": "https://questionsmedicales.fr/mesh/D017059?mesh_terms=Multilevel+Analysis&page=3#section-traitements"
},
{
"@type": "MedicalWebPage",
"name": "Complications",
"headline": "Complications sur Modèles économétriques",
"description": "Quelles sont les conséquences d'un modèle mal spécifié ?\nQuels risques d'une autocorrélation non traitée ?\nComment la multicolinéarité affecte-t-elle les résultats ?\nQuelles erreurs peuvent survenir dans l'interprétation des résultats ?\nQuels effets d'un échantillonnage biaisé ?",
"url": "https://questionsmedicales.fr/mesh/D017059?mesh_terms=Multilevel+Analysis&page=3#section-complications"
},
{
"@type": "MedicalWebPage",
"name": "Facteurs de risque",
"headline": "Facteurs de risque sur Modèles économétriques",
"description": "Quels facteurs influencent la sélection des variables ?\nComment la taille de l'échantillon affecte-t-elle les résultats ?\nQuels sont les risques d'une mauvaise collecte de données ?\nComment les variables omises affectent-elles le modèle ?\nQuels sont les impacts d'une mauvaise spécification du modèle ?",
"url": "https://questionsmedicales.fr/mesh/D017059?mesh_terms=Multilevel+Analysis&page=3#section-facteurs de risque"
}
]
},
{
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "Comment identifier un modèle économétrique approprié ?",
"position": 1,
"acceptedAnswer": {
"@type": "Answer",
"text": "Il faut analyser la nature des données et les relations entre les variables."
}
},
{
"@type": "Question",
"name": "Quels tests sont utilisés pour valider un modèle ?",
"position": 2,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des tests comme le test de normalité, le test de multicolinéarité et le test de spécification."
}
},
{
"@type": "Question",
"name": "Qu'est-ce qu'un modèle de régression ?",
"position": 3,
"acceptedAnswer": {
"@type": "Answer",
"text": "C'est un modèle qui établit une relation entre une variable dépendante et une ou plusieurs variables indépendantes."
}
},
{
"@type": "Question",
"name": "Comment évaluer la performance d'un modèle ?",
"position": 4,
"acceptedAnswer": {
"@type": "Answer",
"text": "On utilise des indicateurs comme le R², l'erreur quadratique moyenne et le test de Fisher."
}
},
{
"@type": "Question",
"name": "Qu'est-ce qu'un modèle à variables instrumentales ?",
"position": 5,
"acceptedAnswer": {
"@type": "Answer",
"text": "C'est un modèle utilisé pour corriger les biais d'endogénéité en utilisant des variables externes."
}
},
{
"@type": "Question",
"name": "Quels sont les signes d'un modèle mal spécifié ?",
"position": 6,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des résidus non aléatoires, des valeurs aberrantes et des relations non linéaires."
}
},
{
"@type": "Question",
"name": "Comment détecter l'hétéroscédasticité ?",
"position": 7,
"acceptedAnswer": {
"@type": "Answer",
"text": "En utilisant des tests comme le test de Breusch-Pagan ou en observant les résidus."
}
},
{
"@type": "Question",
"name": "Quels effets peut avoir la multicolinéarité ?",
"position": 8,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elle peut rendre les estimations des coefficients instables et difficiles à interpréter."
}
},
{
"@type": "Question",
"name": "Qu'est-ce qu'un biais d'échantillonnage ?",
"position": 9,
"acceptedAnswer": {
"@type": "Answer",
"text": "C'est une erreur systématique due à un échantillon non représentatif de la population."
}
},
{
"@type": "Question",
"name": "Quels sont les signes d'une autocorrélation ?",
"position": 10,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des résidus corrélés dans le temps, souvent détectés par le test de Durbin-Watson."
}
},
{
"@type": "Question",
"name": "Comment éviter les biais dans les modèles ?",
"position": 11,
"acceptedAnswer": {
"@type": "Answer",
"text": "En s'assurant que l'échantillon est représentatif et en utilisant des méthodes de validation."
}
},
{
"@type": "Question",
"name": "Quelles pratiques pour une bonne collecte de données ?",
"position": 12,
"acceptedAnswer": {
"@type": "Answer",
"text": "Utiliser des protocoles standardisés et s'assurer de la qualité et de la fiabilité des données."
}
},
{
"@type": "Question",
"name": "Comment choisir les bonnes variables ?",
"position": 13,
"acceptedAnswer": {
"@type": "Answer",
"text": "En se basant sur la théorie, des études antérieures et des tests de significativité."
}
},
{
"@type": "Question",
"name": "Quelles sont les bonnes pratiques de modélisation ?",
"position": 14,
"acceptedAnswer": {
"@type": "Answer",
"text": "Utiliser des diagnostics appropriés, tester les hypothèses et valider le modèle sur des données nouvelles."
}
},
{
"@type": "Question",
"name": "Comment éviter le surajustement ?",
"position": 15,
"acceptedAnswer": {
"@type": "Answer",
"text": "En utilisant des techniques de validation croisée et en limitant la complexité du modèle."
}
},
{
"@type": "Question",
"name": "Comment corriger l'hétéroscédasticité ?",
"position": 16,
"acceptedAnswer": {
"@type": "Answer",
"text": "En utilisant des transformations de données ou des modèles de régression robustes."
}
},
{
"@type": "Question",
"name": "Quelles méthodes pour traiter la multicolinéarité ?",
"position": 17,
"acceptedAnswer": {
"@type": "Answer",
"text": "On peut utiliser la sélection de variables, la régularisation ou l'analyse en composantes principales."
}
},
{
"@type": "Question",
"name": "Comment améliorer un modèle économétrique ?",
"position": 18,
"acceptedAnswer": {
"@type": "Answer",
"text": "En ajoutant des variables pertinentes, en transformant les données ou en utilisant des modèles non linéaires."
}
},
{
"@type": "Question",
"name": "Qu'est-ce que la régularisation ?",
"position": 19,
"acceptedAnswer": {
"@type": "Answer",
"text": "C'est une technique pour prévenir le surajustement en ajoutant une pénalité aux coefficients."
}
},
{
"@type": "Question",
"name": "Comment utiliser des modèles de séries temporelles ?",
"position": 20,
"acceptedAnswer": {
"@type": "Answer",
"text": "Pour analyser des données chronologiques et prévoir des tendances futures à l'aide de lissage."
}
},
{
"@type": "Question",
"name": "Quelles sont les conséquences d'un modèle mal spécifié ?",
"position": 21,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des prévisions inexactes, des décisions erronées et une mauvaise interprétation des résultats."
}
},
{
"@type": "Question",
"name": "Quels risques d'une autocorrélation non traitée ?",
"position": 22,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elle peut conduire à des estimations biaisées et à des tests statistiques non fiables."
}
},
{
"@type": "Question",
"name": "Comment la multicolinéarité affecte-t-elle les résultats ?",
"position": 23,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elle rend difficile l'évaluation de l'impact individuel des variables sur la variable dépendante."
}
},
{
"@type": "Question",
"name": "Quelles erreurs peuvent survenir dans l'interprétation des résultats ?",
"position": 24,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des conclusions hâtives, des généralisations inappropriées et des politiques mal orientées."
}
},
{
"@type": "Question",
"name": "Quels effets d'un échantillonnage biaisé ?",
"position": 25,
"acceptedAnswer": {
"@type": "Answer",
"text": "Il peut fausser les résultats et mener à des recommandations inappropriées."
}
},
{
"@type": "Question",
"name": "Quels facteurs influencent la sélection des variables ?",
"position": 26,
"acceptedAnswer": {
"@type": "Answer",
"text": "La théorie économique, la disponibilité des données et les objectifs de recherche."
}
},
{
"@type": "Question",
"name": "Comment la taille de l'échantillon affecte-t-elle les résultats ?",
"position": 27,
"acceptedAnswer": {
"@type": "Answer",
"text": "Un échantillon trop petit peut entraîner des estimations instables et des biais."
}
},
{
"@type": "Question",
"name": "Quels sont les risques d'une mauvaise collecte de données ?",
"position": 28,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des données inexactes peuvent fausser les résultats et compromettre la validité du modèle."
}
},
{
"@type": "Question",
"name": "Comment les variables omises affectent-elles le modèle ?",
"position": 29,
"acceptedAnswer": {
"@type": "Answer",
"text": "Elles peuvent introduire un biais et fausser les relations estimées entre les variables."
}
},
{
"@type": "Question",
"name": "Quels sont les impacts d'une mauvaise spécification du modèle ?",
"position": 30,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des prévisions erronées et des décisions basées sur des analyses incorrectes."
}
}
]
}
]
}
Online medical consultation is an important complementary approach to offline health care services. It not only increases patients' accessibility to medical care, but also encourages patients to activ...
This study aims to explore multilevel factors that influence patient activeness in online medical consultations....
A data set comprising 40,505 patients from 300 physicians in 10 specialties was included for multilevel analysis. Patient activeness score (PAS) was calculated based on the frequency and the proportio...
Patients were not equally active in online medical consultations, with PASs varying from 0 to 125.73. Patient characteristics, consultation behavioral attributes, and physician professional characteri...
Patient activeness in online medical consultation requires more scholarly attention. Patient activeness is likely to be enhanced by reducing patients' waiting times and encouraging patients' initiatio...
This study aims to evaluate the association between apical periodontitis (AP) and sociodemographic/clinical factors in a probability sample of individuals living in a rural area of southern Brazilian....
A cross-sectional study was conducted involving 584 non-edentulous adult individuals who had undergone a full-mouth radiographic survey. Periapical status was analysed using the periapical index (PAI)...
The prevalence of AP in the sample was 60.45%. AP was significantly associated with age, skin colour, schooling, periodontal disease, and frequency of dental care (P < 0.005). Among the 10,396 teeth e...
The prevalence of AP was high in the population studied. An older age, black/brown skin colour, low level of schooling, infrequent dental care, severe periodontal disease, mandibular teeth, posterior ...
Teenage pregnancy remains a major social and public health challenge in developing countries especially sub-Saharan Africa (SSA) where prevalence rates are still increasing. Even if considerable effor...
A total pooled weighted sample of 10,010 teenagers (in the age group 15-19) from four waves of the Zambia Demographic and Health Surveys were extracted. Using bivariate analysis, we investigated the t...
Results of the trends of teenage pregnancy in Zambia have shown an overall decrease of 2% between 2001 and 2018. Almost all the socioeconomic and demographic variables were consistently associated wit...
The study shows that teenage pregnancy remains a social and public health challenge in Zambia as the country has seen little decrease in the prevalence over the years under consideration. Factors asso...
Attitudes toward immigrants can, to a large extent, be determined by certain macro contextual factors. This paper tests a number of proposed hypotheses to illustrate patterns of influence generated by...
This study aimed to identify significant antenatal and postnatal factors associated with neonatal death at 2-7 days and at 2-28 days in the Indian subcontinent. Results from this study may help guide ...
Nationally representative recent Demographic and Health Survey data sets from five countries, including Bangladesh, India, Pakistan, Maldives and Nepal, were used....
Survey-weighted univariate distributions were used for study population characteristics and bivariate distributions, along with the chi-squared test for unadjusted associations. Finally, multilevel lo...
Among 200,499 live births, the highest neonatal death rate was observed in Pakistan, followed by Bangladesh, whereas the lowest rate was in Nepal. After adjusting for sociodemographic and maternal con...
The findings suggest that strengthening ANC and PNC services will improve newborn health in the Indian subcontinent and decrease neonatal mortality....
Timely diagnosis of oral cancers is critical, and performing biopsies of oral lesions with suspected malignancy is a crucial step in achieving this goal. The waiting time for the diagnosis may be rela...
The aim of this observational, cross-sectional, national-level study was to identify the factors associated with the waiting time for scheduling an oral biopsy, based on the identification of its need...
We used secondary data from the Brazilian public health system, obtained from the 2nd cycle of the National Program to Improve Access and Quality of Dental Specialty Centers (PMAQ-CEO). The study outc...
In 51.8% of DSC the waiting time for scheduling a biopsy was non-immediate; in 58.1% of CEOs, the sum of the weekly workload of dentists working in the Stomatology specialty is up to 20 h per week; in...
South and Southeast Asian countries (SSEA) account for the highest burden of anemia globally, nonetheless, progress towards the decline of anemia has almost been stalled. This study aimed to explore t...
Demographic and Health Surveys of SSEA countries (Bangladesh, Cambodia, India, Maldives, Myanmar, and Nepal) conducted between 2011 and 2016 were analyzed. A total of 167,017 children aged 6-59 months...
The combined prevalence of childhood anemia across six SSEA countries was 57.3% (95% CI: 56.9-57.7%). At the individual level, childhood anemia was significantly higher among (1) mothers with anemia c...
Children with anemic mothers and stunted growth were found vulnerable to developing childhood anemia. Individual and community-level factors identified in this study can be considered to develop effec...
Seasonal influenza vaccines (SIVs) can protect against influenza and substantially reduce the risk of influenza-related hospitalizations and fatalities in children. This study aimed to assess parental...
Through an anonymous online survey conducted in 19 countries in the EMR, parents or caregivers over 18 years who had at least one child above 6 months filled out the Parent Attitudes about Childhood V...
In total, 6992 respondents filled out the questionnaire. Of them, 47.4 % were residents of middle-income countries, 72.4 % of the mothers were between 26 and 45 years old, 56.5 % had at least a univer...
A high seasonal influenza VH rate was found in the EMR. Health authorities should implement different interventions targeting the identified modifiable risk factor to increase vaccine uptake among chi...
Ideal number of children (INC) is the number of children that a woman or man would have if they could go back to the time when they did not have any children and could choose accurately the number of ...
The study design was a cross-sectional study in which the data was obtained from Ethiopian Demographic and Health Survey (EDHS) in 2016. About 13,961 women ages 15-49 who fulfill the inclusion criteri...
About 33 and 12.8% of the women had four and six ideal numbers of children respectively. The highest INC per woman was recorded in Oromia region 5055 (36.1%) and the lowest in Harare 35(0.2%). The INC...
The spatial analysis revealed a significant clustering of the ideal number of children in the Ethiopia zone. Specifically, higher INC was observed in the Somali region, specifically in the Afder, Shab...
Early marriage and motherhood have long been prevalent in India, with 44.5% of women aged 20-24 reporting marriage before 18 in NFHS 3 (2005-2006), dropping to 26.8% in NFHS 4 (2015-2016). Early mothe...
Utilizing data from the fifth round of National Family Health Survey, this study employs multilevel logistic regression and geospatial analysis to assess the determinants and spatial distribution of e...
This study revealed that educational attainment emerged as a critical determinant, with uneducated women significantly more likely to marry early. Socioeconomic factors, such as poverty and limited ma...
The findings underscore the critical role of education, economic empowerment, and media literacy in mitigating early marriage and motherhood risks. The study calls for multi-sectoral interventions in ...