【摘要】： 疾病地圖經(jīng)常應(yīng)用于疾病地理分布的研究,構(gòu)成疾病地圖的數(shù)據(jù)通常是計(jì)數(shù)型數(shù)據(jù)。幾十年來,統(tǒng)計(jì)工作者對(duì)疾病風(fēng)險(xiǎn)的空間差異模型進(jìn)行了深入細(xì)致的研究,無論在理論上還是應(yīng)用上,都取得了許多優(yōu)秀成果。 由于相鄰的區(qū)域之間,疾病相對(duì)風(fēng)險(xiǎn)比較相似,通常使用隨機(jī)效應(yīng)模型的方法,通過向相鄰的區(qū)域借力來估計(jì)區(qū)域相對(duì)風(fēng)險(xiǎn),這樣可以使估計(jì)值更為穩(wěn)定。為進(jìn)一步研究空間疾病風(fēng)險(xiǎn)的差異程度,我們提出了新的疾病風(fēng)險(xiǎn)結(jié)構(gòu)模型。 論文的結(jié)構(gòu)安排如下: 首先,介紹了空間統(tǒng)計(jì)的概況,回顧了疾病地圖在空間流行病學(xué)上的發(fā)展歷史,并結(jié)合論文的內(nèi)容,給出了一些相關(guān)的基本概念及方法。 其次,我們提出了一個(gè)構(gòu)建相關(guān)結(jié)構(gòu)模型的新方法,將離散的區(qū)域疾病風(fēng)險(xiǎn)連續(xù)化,把區(qū)域總體的風(fēng)險(xiǎn)視為一個(gè)連續(xù)的風(fēng)險(xiǎn)曲面,這樣我們不僅可以估計(jì)每個(gè)區(qū)域個(gè)體的相對(duì)風(fēng)險(xiǎn),還可以估計(jì)區(qū)域總體的疾病風(fēng)險(xiǎn)。同時(shí),出于方便計(jì)算的考慮,論文對(duì)區(qū)域相對(duì)風(fēng)險(xiǎn)的分布函數(shù)進(jìn)行了近似分析。 再次,我們結(jié)合隨機(jī)效應(yīng)方法及回歸模型的有關(guān)應(yīng)用,建立了非空間和空間的疾病風(fēng)險(xiǎn)模型,分別給出了Possion-lognormal模型和聯(lián)合模型,并針對(duì)先驗(yàn)分布函數(shù)的選擇進(jìn)行比較分析。 最后,為驗(yàn)證模型準(zhǔn)確性和穩(wěn)定性,我們借助Matlab軟件對(duì)提出的模型進(jìn)行模擬檢驗(yàn)。在模擬實(shí)驗(yàn)中,使用了MCMC方法進(jìn)行相關(guān)的隨機(jī)抽樣。
[Abstract]:Disease maps are often applied to the study of geographical distribution of diseases. In recent decades, statisticians have made a thorough and detailed study on the spatial difference model of disease risk, and many excellent results have been obtained both in theory and in application. Because the relative risk of disease is similar between adjacent regions, the method of stochastic effect model is usually used to estimate the relative risk of the region by borrowing from adjacent regions, which can make the estimated value more stable. In order to further study the difference of spatial disease risk, we propose a new disease risk structure model. The structure of the paper is as follows: firstly, the general situation of spatial statistics is introduced, and the development history of disease map in spatial epidemiology is reviewed. Combined with the contents of the paper, some basic concepts and methods are given. Secondly, we propose a new method to construct the relevant structural model, which makes the discrete regional disease risk continuous, and treats the regional overall risk as a continuous risk surface. In this way, we can estimate not only the relative risk of individuals in each region, but also the overall disease risk of the region. At the same time, for the convenience of calculation, the distribution function of regional relative risk is analyzed approximately. Thirdly, combining the application of stochastic effect method and regression model, we establish non-spatial and spatial disease risk models, give Possion-lognormal model and joint model, and compare and analyze the choice of prior distribution function. Finally, in order to verify the accuracy and stability of the model, we use Matlab software to test the proposed model. In the simulation experiment, the MCMC method is used to carry out the related random sampling.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2008
【分類號(hào)】：R311

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相關(guān)期刊論文 前2條

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本文編號(hào)：2383661