基于空间误差模型的R与GeoDa软件在发育不良情况下的比较

Hendra H. Dukalang, Ingka Rizkyani Akolo, Muhammad Rezky Friesta Payu, Setiati Ningsih
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摘要

哥伦塔洛市是哥伦塔洛省的首府,该省发育迟缓的发病率很高。这种高发病率需要引起重视,因为发育迟缓可能进一步成为哥伦塔洛人力资源质量低下的指标之一。空间误差模型(spatial Error Model, SEM)是分析发育不良因素的一种方法。SEM模型可以用R和GeoDa软件进行分析。本研究的目的是找出影响Gorontalo市发育不良的因素,并根据R和GeoDa软件的结果比较空间误差模型分析的结果。结果表明,有两个变量对发育不良发生率有显著影响,即完全基本免疫接种(IDL)的变量数和适当卫生设施的数量。R和GeoDa软件比较结果显示,有几个相似的输出,即LM测试输出、参数估计和R平方值,而不同的输出是Moran's I测试输出、Breusch-Pagan测试和AIC值。虽然Moran的I测试输出和Breusch-Pagan的测试不同,但是他们得出的结论是一样的。GeoDa生成的AIC值小于R软件。
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Comparison of R and GeoDa Software in Case of Stunting Using Spatial Error Model
Gorontalo city is the capital of Gorontalo province which has a high incidence of stunting. This high incidence rate needs to get attention because stunting can further become one of the indicators of the low quality of human resources in Gorontalo. One method that can be used to analyze the factors that cause stunting is the spatial regression method, namely Spatial Error Model (SEM). SEM model can analyze used R and GeoDa software. The purpose of this study is to find out the factors that affect stunting in Gorontalo City and compare the results of the Spatial Error Model analysis based on the results of R and GeoDa software. The results showed that there are two variables that have a significant effect on stunting incidence, namely the variable number of Complete Basic Immunization (IDL) and the amount of proper sanitation. The R and GeoDa software comparison results showed there were several similar outputs i.e. LM test output, parameter estimation and R-square value, while the different outputs were Moran's I test output, Breusch-Pagan test, and AIC value. Although Moran's I test output and Breusch-Pagan’s test are different, but they produce the same conclusion. The AIC value produced by GeoDa is smaller than R software.
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