Propensity Score Matching of The Gymnastics for Diabetes Mellitus Using Logistic Regression

被引:2
|
作者
Otok, Bambang Widjanarko [1 ]
Aisyah, Amalia [1 ]
Purhadi [1 ]
Andari, Shofi [1 ]
机构
[1] Inst Teknol Sepuluh Nopember, Fac Math & Nat Sci, Dept Stat, Surabaya, Indonesia
来源
INTERNATIONAL CONFERENCE AND WORKSHOP ON MATHEMATICAL ANALYSIS AND ITS APPLICATIONS (ICWOMAA 2017) | 2017年 / 1913卷
关键词
confounding; diabetes mellitus; propensity score matching;
D O I
10.1063/1.5016668
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Diabetes Mellitus (DM) is a group of metabolic diseases with characteristics shows an abnormal blood glucose level occurring due to pancreatic insulin deficiency, decreased insulin effectiveness or both. The report from the ministry of health shows that DMs prevalence data of East Java province is 2.1%, while the DMs prevalence of Indonesia is only 1,5%. Given the high cases of DM in East Java, it needs the preventive action to control factors causing the complication of DM. This study aims to determine the combination factors causing the complication of DM to reduce the bias by confounding variables using Propensity Score Matching (PSM) with the method of propensity score estimation is binary logistic regression. The data used in this study is the medical record from As-Shafa clinic consisting of 6 covariates and health complication as response variable. The result of PSM analysis showed that there are 22 of 126 DMs patients attending gymnastics paired with patients who didnt attend to diabetes gymnastics. The Average Treatment of Treated (ATT) estimation results showed that the more patients who didnt attend to gymnastics, the more likely the risk for the patients having DMs complications.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Estimation of propensity score using spatial logistic regression
    Nisa, Hilwin
    Mitakda, Maria B. T.
    Astutik, Suci
    9TH ANNUAL BASIC SCIENCE INTERNATIONAL CONFERENCE 2019 (BASIC 2019), 2019, 546
  • [2] Performance evaluation of some propensity score matching methods by using binary logistic regression model
    Olmus, Hulya
    Bespinar, Esra
    Nazman, Ezgi
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2022, 51 (04) : 1647 - 1660
  • [3] COMPARISON OF MULTIVARIABLE-ADJUSTED LOGISTIC REGRESSION WITH PROPENSITY SCORE-MATCHED, PROPENSITY SCORE-STRATIFIED, AND PROPENSITY SCORE-ADJUSTED LOGISTIC REGRESSION MODELS
    Khoza, S.
    Barner, J. C.
    Richards, K.
    VALUE IN HEALTH, 2011, 14 (03) : A92 - A93
  • [4] Propensity Score Matching Using Support Vector Machine in Case of Type 2 Diabetes Mellitus (DM)
    Hasanah, Silviatul
    Otok, Bambang Widjanarko
    Purhadi
    2018 2ND INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED): SMART TECHNOLOGY FOR BETTER SOCIETY, 2018, : 132 - 137
  • [5] The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching
    Szeker, Szabolcs
    Vathy-Fogarassy, Agnes
    HEALTH INFORMATICS MEETS EHEALTH: BIOMEDICAL MEETS EHEALTH - FROM SENSORS TO DECISIONS, 2018, 248 : 1 - 8
  • [6] Estimating the Return to College in Britain Using Regression and Propensity Score Matching
    Fan, Wen
    LABOUR-ENGLAND, 2012, 26 (01): : 31 - 45
  • [7] Failure of regression adjustment against propensity score matching
    Baser, O
    VALUE IN HEALTH, 2006, 9 (03) : A87 - A87
  • [8] Trends, Prevalence, and Outcomes of Ulcerative Colitis in Diabetes Mellitus: A Propensity Score Matching Analysis Study
    Uwagbale, Ese
    Adeniran, Olayemi
    Zavgorodneva, Zhanna
    Siddiqui, Samrah
    Omaliko, Chidiebele
    Sharma, Rutwik Pradeep
    Agbroko, Solomon
    Khalid, Nida
    Chathuranga, Dileepa
    Moza, Dasha
    Dunnigan, Karin
    Okolo, Patrick
    AMERICAN JOURNAL OF GASTROENTEROLOGY, 2023, 118 (10): : S857 - S858
  • [9] Trends and Outcomes of Crohn's Diseases in Patients With Diabetes Mellitus: A Propensity Score Matching Analysis
    Uwagbale, Ese
    Adeniran, Olayemi
    Siddiqui, Samrah
    Zavgorodneva, Zhanna
    Sharma, Rutwik Pradeep
    Omaliko, Chidiebele
    Agbroko, Solomon
    Chathuranga, Dileepa
    Khalid, Nida
    Moza, Dasha
    Dunnigan, Karin
    Okolo, Patrick
    AMERICAN JOURNAL OF GASTROENTEROLOGY, 2023, 118 (10): : S858 - S859
  • [10] COVID-19 in Kidney Transplant Recipients With Diabetes Mellitus: A Propensity Score Matching Analysis
    Rangel, Erika B.
    de Lucena, Debora D.
    Aguiar-Brito, Isabella
    Modelli de Andrade, Luis Gustavo
    Veronese-Araujo, Alexandre
    Cristelli, Marina P.
    Tedesco-Silva, Helio
    Medina-Pestana, Jose O.
    TRANSPLANT INTERNATIONAL, 2022, 35