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1.
目的对目前惯用的正态近似法计算总体率可信区间的应用条件进行评价,为正确应用该法提供理论基础和应用指导.方法应用二项分布原理计算总体率精确可信区间并与正态近似法计算结果相比较;采用蒙特卡洛模拟抽样评价可信度;应用SAS和Excel软件绘制二项分类数据概率分布图.结果以n×p=5作为近似条件,用正态近似法计算总体率可信区间可造成显著的相对误差.当n×p为常数时,随着p减小,相对误差在一定范围内呈线性增加;随着n增加,相对误差呈非线性增加.结论目前惯用的估计总体率可信区间的正态近似法应用条件并不能保证总体率估计的可信度和准确度.根据实验结果,提出了使用正态近似法估计总体率95%可信区间一套新的应用条件.  相似文献   

2.
彭斌  易东  田考聪  钟晓妮 《现代预防医学》2007,34(13):2472-2474,2476
[目的]对基于二项分布的小样本总体率可信区间估计方法-Clopper-Pearson提出的精确法进行校正,以减少精确法的保守性,提高可信区间的精密度.[方法]运用SAS软件,编制二项分布的Monte Carlo模拟抽样程序,通过计算95%可信区间的实际可信度寻找合适的校正系数k.[结果]校正系数k=0.5时校正法所估计的95%可信区间的实际可信度比精确法更接近期望可信度(95%),其可信区间宽度比精确法更窄;而当样本含量小于15时,k=0.6的校正结果最理想.[结论]校正法可以减少精确法的保守性,提高可信区间的精密度.  相似文献   

3.
目的探讨设计以率作为终点评价指标的单组目标值试验时,不同样本量计算方法间的区别。方法通过样本量计算原理与计算结果的比较,分析不同样本量计算方法间的差异,进一步通过MonteCarlo随机模拟方法,探讨使用不同方法所得样本量估计实际的检验把握度,验证所得结果的正确性。结果当预计事件发生率P和目标值P。相差10%时,近似正态法和一般精确概率法所得样本量和把握度较相近,但是当P接近1.0时(P〉0.85),精确概率法所得样本量略低于近似正态法,且把握度明显低于近似正态法。小概率事件的精确概率法所需样本量始终低于近似正态法和一般精确概率法。随机模拟显示,在相同的参数设置下,近似正态法给出的样本量能够提供足够的研究把握度,而小概率事件的精确概率法所得样本量能提供的把握度过低。结论如果要检验某医疗器械的使用成功率是否不低于某个临床认可的标准,按照近似正态法计算的样本量,更能提供足够的检验把握度,尤其对于小规模的临床试验。  相似文献   

4.
目的应用Monte-Carlo模拟进行基于人时的相对危险度的分布估计。方法结合实例进行相对危险度的模型构建、拉丁超立方抽样和概率分布的拟合及RR可信区间的几种计算方法比较。结果模拟的RR频率分布经拟合符合Pearson5、Lognorm、Gamma和InvGauss4种分布,以Pearson5分布拟合最佳。模拟的RR值95%可信区间结果与统计量函数计算值、Wald法和Score法大致相当,但其上限值和下限值均略小。结论应用Monte-Carlo模拟结合拉丁超立方抽样技术,实现了基于人时的相对危险度的分布估计,该方法可应用于更为复杂的参数分布估计。  相似文献   

5.
刘沛 《中国卫生统计》2004,21(5):297-299
目的在对现有总体率可信区间计算方法优缺点进行评价的基础上,研究计算总体率可信区间的一次近似法.方法根据中心极限定理和连续性校正原理,给出一次近似法和校正一次近似法计算总体率可信区间的公式.结果得出了一次近似法计算总体率1-α可信区间的公式和校正一次近似法计算总体率1-α可信区间的公式,并对这两个公式的可解性、合理性、对称性和实用性等特征进行了讨论.结论在进行总体率区间估计时,一次近似法在理论上优于目前通用的二次近似法.  相似文献   

6.
在成组病例对照研究中,可通过计算优势比(OR)对相对危险度(RR)作出估计[1],常涉及到优势比(OR)的可信区间估计,其中常用的方法有直接计算概率法、Woolf法、Cornfield法和Test-based法(Miettinen 法)[2].本文利用Stata7.0软件[3-5]进行模拟实验,比较这四种方法的适用范围及检验效能.  相似文献   

7.
目的介绍隐函数Delta法计算调整人群归因危险度(PAR)可信区间的基本原理和SAS编程方法.方法实例介绍用SAS PROC IML过程,实现病例-对照研究中调整PAR及其可信区间的估计.结果利用此程序计算了上海市男性食管癌病例-对照研究资料吸烟、饮酒和水果摄入过少因素的调整PAR及其95%可信区间分别46.59%(34.92X.26%),20.87%(10.281.47%)34.54%(19.81%~49.29%).结论对符合条件的病例-对照资料,隐函数Delta法可以对暴露因素调整PAR及其可信区间进行较为准确的估计.  相似文献   

8.
平均角的可信区间估计   总被引:4,自引:0,他引:4  
本文得出平均角可信区间的估计公式。尽管公式是依据中心极限定理,用于大样本时平均角可信区间的近似估计,实例表明,即使对小样本资料,估计精度也很满意。  相似文献   

9.
ROC曲线下面积的ML估计与假设检验   总被引:5,自引:0,他引:5  
目的 探讨诊断试验中配对设计资料的ROC分析方法。方法 在双正态模型基础下应用ML估计方法计算ROC曲线下面积,正态近似法估计面积的可信区间及假设检验。结果 由迭代法进行参数估计,得到ROC曲线下的面积、面积的标准误及置信区间,可计算出面积比较的U检验统计量。结论 可用于配对设计的诊断试验的比较和评价,包括对连续性和等级分类资料的处理。  相似文献   

10.
我国18岁以上居民高血压患病率的区间估计   总被引:1,自引:0,他引:1  
目的估计我国18岁以上居民的高血压患病率及其95%的可信区间。方法对复杂样本加权调整,使用SUDAAN 10.0.1软件,计算我国18岁以上居民的高血压患病率,并用泰勒级数法估计其方差和95%可信区间。结果我国18岁以上居民的高血压患病率及其95%可信区间为19.14%(18.15%~20.12%),平均收缩压及其95%可信区间为120.0 mmHg(119.4~120.6 mmHg),平均舒张压为76.4 mmHg,95%可信区间为76.0~76.8 mmHg。结论简单随机抽样的公式不适用于复杂抽样的数据点估计和区间估计值,应该根据具体的抽样设计来估计。同时,对复杂抽样数据进行抽样权重调整可以避免结果偏倚。  相似文献   

11.
目的 建立含区间数据Gamma分布的参数估计方法,并用于SARS潜伏期的推算。方法 采用EM算法构造出求解含区间数据Gamma分布参数极大似然估计的迭代公式,并应用于SARS潜伏期分布的拟合。结果 基于EM算法的极大似然估计方法可以计算出含区间数据Gamma分布的两个参数,从而得到均值估计。同时,还可以根据极大似然估计的渐近性质,计算出估计量的标准误及各参数的置信区间。用于中国内地SARS爆发资料分析,发现SARS潜伏期服从Gamma(2.1,2.33)分布;潜伏期均值和方差的极大似然估计值分别为4.89天(95%CI4.43~5.35)和11.40天^2;95%的病人感染SARS-CoV后将在11.42天内发病。结论 基于EM算法的极大似然估计方法对于含区间数据Gamma分布参数的估计是强健的。可以用于含区间数据SARS潜伏期的精确估计。  相似文献   

12.
目的本次研究以第三次全国血吸虫病流行病学调查为背景,对其部分抽样过程进行计算机模拟,采用负二项分布抽样方法,得到感染率的无偏估计,并与传统的抽样方法比较,综合评价两种抽样方法的优缺点。方法分别在样本量相同及样本量不同两种情况下对抽样结果估计感染率的绝对误差、相对误差及正确率作统计学描述分析,并综合评价。结果在相同样本量下,两种抽样方法估计的感染率在绝对误差、相对误差、正确率及可信区间宽度方面差别的P值均大于0.05(当感染率为0.6%时,两者的正确率及可信区间宽度差别P值接近0.05);在样本量不同时,两种抽样方法估计的感染率在正确率方面差异无统计学意义(P值均大于0.05),在绝对误差、相对误差及可信区间方面差别的P值均小于0.01,仅在感染率较高时(大于10%)两者差异无统计学意义。结论在样本量一致情况下,两种抽样方法在不同的感染率范围内的估计精度相当。当实际感染率较小时(如小于1%),采用负二项分布抽样可实现抽到足够的患者;当实际感染率未知且无法预测时,该方法又是一种探索性的抽样方法。  相似文献   

13.
秩和的分布,区间估计和假设检验的探讨   总被引:4,自引:0,他引:4  
目的 探讨秩和比的分布理论及建立区间估计和假设检验方法。方法 假设各变量相互独立,观察单位某变量取值是随机的,则其秩的分布为均匀分布,秩和的分布是m个独立同分布变量之秩的和。结果 当m和n较小时,如m<3,秩和的分布呈单峰对称分布;m和n不太小时,秩和的分布迅速逼近正态分布。结论 对秩和与秩和比可以应用正态分布理论作区间估计和假设检验。  相似文献   

14.
目的 探讨几种捕获-再捕获分析方法间的关系,推进该法在医学尤其是在伤害研究中的广泛应用。方法 将缺失估算法与超几何分布、比例法等进行比较,进一步研究缺失估算法与超几何分布法间的关系,以及比例法与超几何分布特点,且以医学实例介绍各种方法。结果 缺失估算法与超几何分布法估算结果相同,由超几何分布可导出缺失估算法公式;伤害人群分布不服从负二项分布,比例法与超几何分布估算范围不同。结论 缺失估算法与超几何分布可任选一种方法,而超几何分布法计算较简便;比例法与超几何分布法估算范围不同,需根据具体条件选用。  相似文献   

15.

Introduction

Breast cancer control efforts could benefit from estimating mammography prevalence at the substate level because studies have primarily analyzed health survey data at the national and state levels. The purpose of this study was to evaluate the extent to which geographic disparities exist in mammography use across counties in the contiguous United States.

Methods

We estimated county-level prevalence of recent mammography (past 2 years) for women aged 40 to 79 years by using synthetic regression, a small-area estimation method. The 2000 Behavioral Risk Factor Surveillance System (BRFSS), 2000 Census, Area Resource File, and Food and Drug Administration mammography facility data were merged by BRFSS respondents'' county of residence. We conducted separate analyses to produce county-level prevalence estimates for each race and age group.

Results

Mammography use varied geographically, and the magnitude of geographic disparities differed by race and age. Nonwhite women showed the lowest prevalence of mammography and widest range in county-level estimates. Women aged 40 to 49 had generally lower prevalence than other age groups, while women aged 65 to 79 showed the greatest variation in county-level mammography estimates.

Conclusions

Small-area estimation using BRFSS data is advantageous for surveillance of mammography use at the county level. This method allows documentation of geographic disparities and improves our understanding of the spatial distribution of mammography prevalence. Future interventions should consider this county-level geographic variation, targeting women in the neediest counties.  相似文献   

16.
成本效果比五种可信区间估计法比较   总被引:2,自引:0,他引:2  
目的给出成本效果比可信区间的最佳估计方法.方法采用理论探讨和实证研究比较盒法、Taylor级数法、椭圆法、Fieller's准则和非参Bootstrap法等5种计算增量成本效果比可信区间估计方法的优缺点.结果传统的统计学方法计算卫生经济学评价中增量成本效果比的可信区间会带来偏倚,Fieller's准则和非参数Bootstrap法的估计较为精确.结论推荐采用Bootstrap法估计增量成本效果比可信区间.  相似文献   

17.
  目的  建立泊松分布95%可信区间表,基于该可信区间表估算辐射生物剂量。
  方法  根据泊松分布累积概率和的算法,用Excel函数及迭代法建立计算变量X可信区间的方法,用宏代码循环计算得到95%可信区间表,基于该可信区间表建立辐射生物剂量估算的Excel应用,并验证可信区间表以及估算剂量的准确性。
  结果  利用Excel软件建立了X取值0 ~ 500的95%可信区间表,其结果与权威教材文献给出的可信区间一致;正态近似法与泊松分布表法估算辐射生物剂量95%可信区间在畸变数较小时差别明显,在畸变数较大时差别较小,泊松分布表法的95%可信区间与国际原子能机构(IAEA)推荐的专业估算软件CABAS 2.0的结果一致。
  结论  建立的估算程序可以准确计算泊松分布的可信区间,使用该可信区间表来估算辐射生物剂量的95%可信区间更合理;该程序应用范围更广、使用更方便,可满足辐射应急事故中对大量受照人员进行生物剂量估算的需求。
  相似文献   

18.
A method, PIAMOD (Prevalence, Incidence, Analysis MODel), which allows the estimation and projection of cancer prevalence patterns by using cancer registry incidence and survival data is presented. As a first step the method involves the fit of incidence data by an age, period and cohort model to derive incidence projections. Prevalence is then estimated from modelled incidence and survival estimates. Cancer mortality is derived as a third step from modelled incidence, prevalence and survival. An application to female breast cancer is given for the Connecticut State by using data from the Connecticut Tumor Registry (CTR), 1973-1993. The age, period and cohort model fitted incidence quite well and allowed us to derive long-term projections up to 2030. Patients' survival was also projected to future years according to a scenario approach based on two extreme hypotheses: steady, that is, no more improvements after 1993 (conservative), and continuously improving at the same rate as during the observation period. Age-standardized estimated incidence shows a changing trend around the year 2005, when it starts decreasing. Age-standardized prevalence is expected to increase and change trend at a later date. Breast cancer mortality is projected as decreasing, as the combined result of no further increase in incidence and improving cancer patients' survival. An easy-to-use PIAMOD software package, on which work is in progress, will be made available to individual cancer registries and/or health planning institutions or authorities once it is developed. The use of the PIAMOD method for cancer registries will allow them to provide results of paramount importance for the whole community involved in the assessment of future disease burden scenarios in an evolving society.  相似文献   

19.
Data on concentrations of trihalomethanes (THMs) in raw and chlorinated water collected from three water treatment plants in Taiwan and estimates of the lifetime cancer risk for THMs from drinking water, using age-adjusted factors and volatilization terms, are presented. Data on THM levels in drinking water were obtained from the annual reports of the Environmental Protection Administration (EPA) of Taiwan. The methodology for estimation of lifetime cancer risks was taken from the USEPA. Chloroform was the major species of THMs, especially in the water plant of south Taiwan. Chloroform contributed the majority of the lifetime cancer risks (range: 87.5-92.5%) of total risks from the three water supply areas. All lifetime cancer risks for CHCl(3), CHBrCl(2), CHBr2Cl, and CHBr3 from consuming tap water in the three water supply areas were higher than 10(-6). The sum of lifetime cancer risks for CHCl(3), CHBrCl(3), CHBr2Cl, and CHBr3 was highest (total risk for total THMs<1.94x10(-4)) for tap water from south Taiwan.  相似文献   

20.
If several risk factors for disease are considered in the same multiple logistic regression model, and some of these risk factors are measured with error, the point and interval estimates of relative risk corresponding to any of these factors may be biased either toward or away from the null value. A method is provided for correcting point and interval estimates of relative risk obtained from logistic regression for measurement error in one or more continuous variables. The method requires a separate validation study to estimate the coefficients from the multivariate linear regression model relating the surrogate variables to the vector of true risk factors. Similar methods have been suggested by other authors, but none provides a means of correcting the confidence intervals which include a component of variability due to estimation of the measurement error parameters from a validation study. An example is provided from a prospective study of dietary fat, calories, and alcohol in relation to breast cancer, and from a validation study of the questionnaire used to assess these nutrients. Before correcting for measurement error, the age-adjusted relative risk for a 25 g increment in alcohol intake was 1.33 (95% confidence interval (CI) 1.14-1.55); after correcting for measurement error, the relative risk increased to 1.62 (95% CI 1.23-2.12). Similarly, for a 10 g increment in saturated fat intake, the age-adjusted relative risk was 0.94 (95% CI 0.83-1.06); after correcting for measurement error, the relative risk was 0.84 (95% CI 0.59-1.20). These results indicate that the failure to find a substantial positive association between breast cancer risk and saturated fat intake cannot be explained by measurement error in fat, calories, or alcohol.  相似文献   

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