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  Spatial heterogeneity of quality, use and spending on medicare for the elderly

  Felipa de Mello-Sampayo

  07-05-2018

  https://doi.org/10.4081/gh.2018.655

  2101

  PDF: 913

  HTML: 113
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  Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old

  André Oliveira, Antònio J.R. Cabral, Jorge M. Mendes, Maria R.O. Martins, Pedro Cabral

  04-11-2015

  https://doi.org/10.4081/gh.2015.365

  3238

  PDF: 1426

  HTML: 1223
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  Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah

  Abdulkader Murad, Fazlay Faruque, Ammar Naji, Alok Tiwari, Mansour Helmi, Ammar Dahlan

  16-05-2022

  https://doi.org/10.4081/gh.2022.1072

  2013

  PDF: 1014

  HTML: 157

• When homogeneity meets heterogeneity: the geographically weighted regression with spatial lag approach to prenatal care utilisation

  Carla Shoff, Vivian Yi-Ju Chen, Tse-Chuan Yang

  557-568

  01-05-2014

  https://doi.org/10.4081/gh.2014.45

  2541

  PDF: 1172
• 

  Spatiotemporal analysis of hand, foot and mouth disease data using time-lag geographically-weighted regression

  Zhi-Min Hong, Hu-Hu Wang, Yan-Juan Wang, Wen-Rui Wang

  29-12-2020

  https://doi.org/10.4081/gh.2020.849

  1953

  PDF: 892

  HTML: 29

• Exploring recent spatial patterns of cutaneous leishmaniasis and their associations with climate in some countries of the Middle East using geographical information systems

  Salahuddin M. Jaber, Jwan H. Ibbini, Nawal S. Hijjawi, Nafn M. Amdar, Mohammed J. Huwail, Khalid Al-Aboud

  143-158

  01-11-2013

  https://doi.org/10.4081/gh.2013.62

  2246

  PDF: 1061

• Identifying geographical variations in poverty-obesity relationships: empirical evidence from Taiwan

  Tzai-Hung Wen, Duan-Rung Chen, Meng-Ju Tsai

  257-265

  01-05-2010

  https://doi.org/10.4081/gh.2010.205

  3685

  PDF: 1627
• 

  Neonatal mortality in East Africa and West Africa: a geographic analysis of district-level demographic and health survey data

  Sue C. Grady, April N. Frake, Qiong Zhang, Matlhogonolo Bene, Demetrice R. Jordan, Joshua Vertalka, Thania C. Dossantos, Ameen Kadhim, Judith Namanya, Lisa-Marie Pierre, Yi Fan, Peiling Zhou, Fatoumata B. Barry, Libbey Kutch

  26-05-2017

  https://doi.org/10.4081/gh.2017.501

  9441

  PDF: 4403

  HTML: 2226

• Mastering geographically weighted regression: key considerations for building a robust model

  Behzad Kiani, Benn Sartorius, Colleen L. Lau, Robert Bergquist

  29-02-2024

  https://doi.org/10.4081/gh.2024.1271

  8370

  PDF: 1566

  HTML: 872
• 

  Associating socio-economic factors with access to public healthcare facilities using geographically weighted regression in the city of Tshwane, South Africa

  Thabiso Moeti, Tholang Mokhele, Solomon Tesfamichael

  20-11-2024

  https://doi.org/10.4081/gh.2024.1288

  2166

  PDF: 648

  HTML: 90
• 

  Spatial heterogeneity in relationship between district patterns of HIV incidence and covariates in Zimbabwe: a multi-scale geographically weighted regression analysis

  Rutendo Birri Makota, Eustasius Musenge

  27-11-2023

  https://doi.org/10.4081/gh.2023.1207

  1550

  PDF: 774

  HTML: 73
• 

  Geographically weighted regression for modelling the accessibility to the public hospital network in Concepción Metropolitan Area, Chile

  Marcela Martínez Bascuñán, Carolina Rojas Quezada

  22-11-2016

  https://doi.org/10.4081/gh.2016.451

  3885

  PDF: 1822

  HTML: 2181
• 

  Spatial analysis of the relationship between out-of-pocket expenditure and socioeconomic status in South Korea

  Young-Gyu Kwon, Man-Kyu Choi

  25-05-2023

  https://doi.org/10.4081/gh.2023.1175

  1410

  PDF: 780

  HTML: 49
• 

  Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach

  Alexander Domnich, Lucia Arata, Daniela Amicizia, Alessio Signori, Roberto Gasparini, Donatella Panatto

  16-11-2016

  https://doi.org/10.4081/gh.2016.457

  3376

  PDF: 1781

  HTML: 1324
• 

  Spatial analysis and modelling of depression relative to social vulnerability index across the United States

  Kiara M. Rivera, Abolfazl Mollalo

  01-09-2022

  https://doi.org/10.4081/gh.2022.1132

  4884

  PDF: 2144

  HTML: 567
• 

  Diabetes prevalence in the state of Alabama: identifying the risk factors

  Kwaku Karikari Manu, Seth Appiah-Opoku

  31-03-2026

  https://doi.org/10.4081/gh.2026.1465

  165

  PDF: 91

  HTML: 0