A Non-parametric Method for Hazard Rate Estimation in Acute Myocardial Infarction Patients: Kernel Smoothing Approach.
Background: Kernel smoothing method is a non-parametric or graphical method for statistical estimation. In the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. Methods: By employing non-parametric regression methods, t...
| Publicado en: | Journal of Research in Health Sciences Vol. 12; no. 1; pp. 19 - 25 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Hamadan University of Medical Sciences, School of Public Health
Jan2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=78168495&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 78168495 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 22287795 903Q jtl: Journal of Research in Health Sciences issn: 22287795 maglogo: N pubinfo: dt: Jan2012 vid: 12 iid: 1 pid: 54266 pub: Hamadan University of Medical Sciences, School of Public Health artinfo: ui: 78168495 78168495 104484164 78168495 ppf: 19 ppct: 6 formats: fmt: @attributes: type: P tig: atl: A Non-parametric Method for Hazard Rate Estimation in Acute Myocardial Infarction Patients: Kernel Smoothing Approach. aug: au: Reza Soltanian, Ali Mahjub, Hossein affil: Department of Biostatistics & Epidemiology and Research Center for Health Sciences, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran sug: subj: Myocardial Infarction Mortality Death Risk Factors Funding Source Human Iran Descriptive Statistics Kaplan-Meier Estimator Data Analysis, Statistical Data Analysis Software P-Value Confidence Intervals Male Female Cross Sectional Studies Regression Male Female ab: Background: Kernel smoothing method is a non-parametric or graphical method for statistical estimation. In the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. Methods: By employing non-parametric regression methods, the curve estimation, may have some complexity. In this article, four indices of Epanechnikov, Biquadratic, Triquadratic and Rectangle kernels were used under local and k-nearest neighbors' bandwidth. For comparing the models, were employed mean integrated squared error. To illustrate in the study, was used the dataset of acute myocardial infraction patients in Bushehr port, in the south of Iran. To obtain proper bandwidth, was used generalized cross-validation method. Results: Corresponding to a low bandwidth value, the curve is unreadable and the regression curve is so roughly. In the event of increasing bandwidth value, the distribution has more readable and smooth. In this study, estimate of death hazard rate for the patients based on Epanechnikov kernel under local bandwidth was 1.011×10-11, which had the lowest mean square error compared to k-nearest neighbors bandwidth. We obtained the death hazard rate in 10 and 30 months after the first acute myocardial infraction using Epanechnikov kernelas were 0.0031 and 0.0012, respectively. Conclusion: The Epanechnikov kernel for obtaining death hazard rate of patients with acute myocardial infraction has minimum mean integrated squared error compared to the other kernels. In addition, the mortality hazard rate of acute myocardial infraction in the study was low. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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