死因監(jiān)測(cè)整群抽樣設(shè)計(jì)方案的比較研究
[Abstract]:The cause of death surveillance is the scientific basis for understanding the level and order of death, mastering the influencing factors of residents' health, making health policy for the government, and evaluating the quality and effect of health work. It is also an important content of studying the law of natural change of population. Among them, the determination of the cause of death monitoring point is a primary problem. In this study, the determination of cause of death monitoring points in Shaanxi Province as an example, with 107 county (city, district) units as sampling frame, the following parts of the study: 1. Develop different sampling schemes. According to the actual situation in China, this paper introduces the unequal probability sampling method, and establishes four feasible sampling methods, that is, complete random cluster sampling, stratified cluster sampling, unequal probability stratified cluster sampling. Taking 5 / 10 / 15% of the total population as the sampling ratio, it is combined into twelve sampling schemes, each of which is sampled 100 times by computer. 2. The sampling accuracy of different sampling schemes is calculated. The results show that the complete random cluster sampling ratio is more than 10%, the stratified cluster sampling ratio is more than 15%, and the stratified cluster sampling ratio is better than 15%. When the proportion of unequal probability cluster sampling is more than 15%, it can be better representative of the whole population, and the proportion of unequal probability stratified cluster sampling more than 15% can be better representative of the whole population. 3. The average sampling standard deviation of different sampling schemes is calculated and compared. The results show that: 1) with the increase of sampling ratio (from 10% to 15%), the mean of standard deviation of regional GDP decreases with the increase of sampling proportion except 5%. 2) in different sampling methods, The mean of standard deviation of regional GDP is minimum by stratified cluster sampling with unequal probability. The standard deviation of the mean of mortality shows that the standard deviation of stratified cluster sampling with unequal probability is the smallest among the different sampling methods. 4. The design efficiency of different sampling schemes is calculated and compared. The results show that: 1) in the complete random cluster sampling, the average of the design efficiency of the regional GDP with different sampling proportions is the same, all of which are 1; Except for the sampling ratio of 5, as the sampling ratio increases (from 10% to 15%), the average of the design efficiency of the region's gross domestic product decreases. 2) in different sampling methods, The mean of design efficiency of regional GDP with stratified cluster sampling with unequal probability is the smallest. Mortality: 1) in complete random cluster sampling, the mean of mortality design efficiency of different sampling proportions is the same, all of them are 1; With the exception of a sampling ratio of 5, the average of the mortality design efficiency decreases as the sampling ratio increases (from 10% to 15%). 2) in different sampling methods, The mean of mortality design efficiency of stratified cluster sampling with unequal probability is the smallest. 5. The best sampling scheme is stratified cluster sampling with unequal probability. The main innovations of this study are as follows: (1) unequal probability sampling is proposed and applied to the sampling study with a clear sampling frame. (2) repeated sampling calculation and comparison are made for each sampling scheme. Average sampling error, (3) the best sampling scheme with definite sampling frame is stratified cluster sampling with unequal probability.
【學(xué)位授予單位】:第四軍醫(yī)大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2010
【分類號(hào)】:R311
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