季节性时间序列资料预测的半参数回归模型

本文利用半参数回归的原理与方法建立了时间序列的半参数回归模型，并通过模拟得到了模型误差的一个估计公式进而得到了模型参数的假设检验及预测的区间估计。     

胎儿双顶径估计孕龄的方法研究

目的建立基于人群基础的双顶径估计孕龄公式和参照图表,并与国内外其他孕龄估计公式或对照表进行比较。方法研究有效样本18933例,孕龄区间为12～20 w。将双顶径数据和孕龄进行多元线性模型拟合,并使用Z-记分方法将得到的最终双顶径估计孕龄公式与公开发表或正在使用的其他双顶径估计孕龄公式或对照表进行比较分析。结果国内孕龄估计公式或对照表之间差异较大,本文所得孕龄估计公式与内地孕龄估计公式或对照表差异也参差不齐,但与香港孕龄估计公式较为接近,且在各孕周差异校正标准差前提下较为恒定。结论建立了新的基于人群的双顶径估计孕龄的公式,并将之应用于临床和相关研究。     

平均角的可信区间估计

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。     

患病人数未知时患病率的点估计及区间估计方法

目的研究患病人数未知时患病率的点估计及区间估计方法。方法根据概率论和数理统计原理导出患病率和阳性检出率、实验灵敏度、特异度间的定量关系,用代数推导和医学实例验证导出的公式。结果在已知实验灵敏度、特异度条件下,导出并验证了由阳性检出率计算患病率的点估计和区间估计方法。结论在患病人数未知条件下,使用阳性检出率和检验方法灵敏度、特异度等信息,可准确估计患病率,这一方法具有重要的公共卫生学意义。     

线性模型中自变量相对重要性优势分析法估计及其应用

目的在多元线性回归模型中,估计各自变量的相对重要性,并探索区间估计方法。方法在自变量间存在相关时,运用Budescu(1993),Azen(2003)提出的优势分析法估计肝手术病例预计存活时间的影响因素重要性,并运用Bootstrap法探索区间估计方法以此来评价估计结果的变异性。结果血凝素、预后指数、酶功能对预计存活时间的相对贡献分别为0.1415、0.3408和0.490,其Bootstrap法95%可信区间分别为(0.0573,0.2744)、(0.2359,0.4545)和(0.3411,0.6090)。结论酶功能对肝手术病例预计存活时间的影响最大,预后指数次之,血凝素最小。当自变量间存在相关时,优势分析法估计的自变量相对重要性结果更精确稳定,值得推广应用。     

单个正态总体均数和两个正态总体均数差别的区间估计设计

本文推导出单个正态总体均数和两个正态总体均数差别的区间估计的样本含量设计公式，不但考虑了区间估计准确程度的可信度，还考虑了区间估计精密程度的把握度，并制作了相应的样本含量设计表，便于实际运用。     

象山县麻疹疫情监测及时间序列分析

目的应用时间序列模型对象山县麻疹疫情进行分析和预测。方法采用描述流行病学方法分析象山县2002—2013年麻疹疫情监测数据,并对该序列资料进行平稳化、定阶并估计参数;建立时间序列模型,以2014年发病资料作为模型预测效果的考核样本来评价模型可靠性。结果象山县麻疹发病率自2008年明显上升后,一直维持较低水平,但有小幅波动,且疫情按月分布没有明显集中性。对麻疹发病数序列建立ARMA模型,并应用该模型预测已知的2014年1—4月份麻疹发病数,模型预测值与实际值基本一致,且实际值均处于预测值95%的可信区间内。结论 ARMA模型对象山县麻疹发病情况的拟合结果满意,预测效果良好,可为该县麻疹的预测预警提供依据。     

分段指数模型的拟合及SAS实现

目的 以实例阐述生存分析分段指数模型的拟合及SAS实现.方法 将生存时间划分为几个区间,利用SAS中的PROC GENMOD过程或PROC LIFEREG过程,对生存资料进行分段指数模型拟合,并通过参数估计结果,计算各时间区间的风险率及生存率.结果 该资料拟合分段指数分布的结果比较满意,三个时间区间的死亡风险均不相同,且第一个和第二、三个区间的差别有统计学意义(P<0.05).结论 分段指数模型不仅模型形式简单,参数易于估计,若拟合得当可提高统计效率.     

Bootstrap方法在Cox模型参数估计中的应用

目的：探讨自变量分布极偏时Cox模型的参数以及区间估计是否准确，引入Bootstrap法对其加以验证。方法：拟合Cox模型研究痰检结果与肺癌发病风险的关系，使用非参数Bootstrap法验证Cox模型的参数估计值、可信区间是否有效。结果：两的参数估计值和大部分可信区间基本一致，个别变量的可信区间不一致，Bootstrap可信区间的下界更低，甚至变为负值。结论：当自变量分布极偏时，Cox模型所估计的参数可信区间可能有偏，Bootstrap可信区间更准确。     

周期性回归在季节分析中应注意的一个问题

余弦模型和圆形分布方法是常用的季节性统计分析方法 ,广泛应用于疾病或健康事件的医学周期性现象的研究中。故又被称为周期性回归分析。由于这两种方法的基本计算方法相同 ,结果一致 ,均可求分布高峰时点和集中趋势值 ,且算式简单 ,Ａ值和ｒ值可相互求得。余弦模型还可作拟合效果分析和预测。因此 ,在实际工作中更具优越性和实用价值。但在应用中常有时间区间估计不一致 ,结果分析不准确 ,或把余弦模型和圆形分布方法视为两种不同的方法等。我们在研究中已进行了深入的探讨并给予更正 ,但不同样本平均值及集中趋势的显著性检验分析尚需进一…     

Test characteristics of self-reported hypertension among the Hispanic population: findings from the Hispanic Health and Nutrition Examination Survey

Data from the Hispanic Health and Nutrition Examination Survey conducted from 1982 to 1984 were analyzed for the sensitivity, specificity, and positive and negative predictive value of self-reported hypertension in 5195 Hispanics of both sexes between the ages of 18 and 74 years. On the basis of a hypertension definition of 140/90 mmHg or of the use of antihypertensive medications, overall sensitivity of self-reported hypertension was 56% for Mexican-Americans, 71% for Cuban-Americans and 72% for Puerto Ricans. Sensitivity was higher among women, among the obese, and among those with access to a regular place for medical care; increased with increasing age; and decreased with education and the time interval since last medical visit. Independent associations for sensitivity were noted for sex, body mass index (BMI), and time interval since last medical visit among Mexican-Americans; and for time interval since last medical visit and for being divorced or separated for Cuban-Americans. Overall positive predictive value reached 49% among Mexican-Americans, 53% among Cuban-Americans, and 39% among Puerto Ricans. Raising the hypertension-threshold to 160/95 mmHg tended to increase the sensitivity but reduced the positive predictive value.     

差分—指数平滑预测模型在医院管理统计中应用的探讨

目的 探讨差分—指数平滑预测模型在医院管理统计中的应用。方法 根据某院1977年～1996年门诊总诊疗人次历史资料,建立差分——指数平滑预测模型,对该院1997年总诊疗人次进行预测。结果 本例预测模型评价:①平均百分误差MPE=0.001％,接近于0;②平均绝对百分误差MAPE=7.97％<10％,说明本预测模型是无偏的,且为高精度预测模型。本例1997年总诊次点估计值为60.78万人次,区间预测值为53.30～68.26万人次,实际值为64.79万人次,确在预测区间内,与点估计值相对误差为6.19％<10％,实际预测效果满意。结论 差分—指数平滑预测模型经医院统计工作者在统计实践中应用,效果满意,是医院管理统计中值得推广应用的一种定量预测方法。     

Misleading measurements: modeling the effects of blood pressure misclassification in a United States population.

OBJECTIVE: The clinical diagnosis of hypertension is subject to misclassification, and this may be clinically important. This article calculates positive and negative predictive values for blood pressure measurement and assesses the frequency of clinically important blood pressure misclassification. DESIGN, SETTING, AND PARTICIPANTS: A modeling study was carried out on 4763 adults in the National Health and Nutrition Examination Survey (NHANES) POPULATION: True treatment eligibility was determined by applying Joint National Committee (JNC) VII criteria to individuals in the study population. Each individual was also allocated a series of blood pressures incorporating an error term reflecting day-to-day measurement variation. Test positives are persons classified as needing treatment on the basis of the mean of 2 blood pressure measurements. MEASUREMENTS AND MAIN RESULTS: Positive predictive values of a diagnosis of hypertension based on 2 measurements were calculated for each age-sex group. Low-risk false positives and highrisk false negatives were categorized as clinically important errors. Positive predictive values are high in persons older than age 65. In persons ages 16 to 34, the positive predictive value is 0.24 (95% confidence interval [CI]: 0.17-0.32) in men and 0.16 (95% CI: 0.06-0.26) in women. Persons younger than age 35 are almost always at low risk of cardiovascular disease, and therefore this misclassification is clinically important. Even with 24-hour ambulatory blood pressure measurement, positive predictive values in young adults are under 0.5. CONCLUSIONS: Blood pressure estimation is a poor diagnostic test in low-prevalence populations such as young adults. Estimation of blood pressure should be informed by prior estimation of cardiovascular risk.     

Survival of healthy older people.

The purpose of this study was to discover any relationships which might exist between measurable variables recorded when a healthy group of men and women, aged 70 years and over, were examined and their subsequent survival time. It was found that height, body weight, systolic and diastolic blood pressures, haemoglobin, hand grip power, cardiothoracic ratio, and pulse rate are of no predictive value in the estimation of survival time. Survival is not influenced by marital status or occupational class. For both sexes the degree of kyphosis and age are useful predictive criteria in respect of survival time. However, much research work requires to be done to explain why many people die at the time they do.     

ROC曲线下面积的ML估计与假设检验

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。     

诊断实验阳性预测值区间估计的四种方法比较

目的比较对数似然比法(log-odds法,含两种调整方法)、修正log-odds法、客观贝叶斯法估计阳性预测值区间的精密度和可靠度,探讨不同情况下的适用方法。方法以区间长度和覆盖概率为指标,比较阳性预测值区间估计的精密度和可靠度。使用SAS9.13编写MonteCarlo模拟抽样程序,完成客观贝叶斯法的计算。结果 log-odds法的精密度和可靠度均低于客观贝叶斯法。大样本时,客观贝叶斯法和修正log-odds法的精密度和可靠度相似;小样本时,后者的精密度稍高,但可靠度远低于前者。结论大样本时建议使用修正log-odds法,小样本时建议使用客观贝叶斯法。     

A multiple imputation approach for clustered interval‐censored survival data

Multivariate interval‐censored failure time data arise commonly in many studies of epidemiology and biomedicine. Analysis of these type of data is more challenging than the right‐censored data. We propose a simple multiple imputation strategy to recover the order of occurrences based on the interval‐censored event times using a conditional predictive distribution function derived from a parametric gamma random effects model. By imputing the interval‐censored failure times, the estimation of the regression and dependence parameters in the context of a gamma frailty proportional hazards model using the well‐developed EM algorithm is made possible. A robust estimator for the covariance matrix is suggested to adjust for the possible misspecification of the parametric baseline hazard function. The finite sample properties of the proposed method are investigated via simulation. The performance of the proposed method is highly satisfactory, whereas the computation burden is minimal. The proposed method is also applied to the diabetic retinopathy study (DRS) data for illustration purpose and the estimates are compared with those based on other existing methods for bivariate grouped survival data. Copyright © 2010 John Wiley & Sons, Ltd.     

基于相对价值的骨科医师工作量研究

目的:以骨科为例探讨医师工作量的相对价值(RVU)。方法:采用现场观察、量值估计法、德尔菲法、问卷调研、定量分析和多重回归等方法进行研究。通过德尔菲法组织专家会遴选样本医院骨科医疗处置项目39项,并以问卷形式在我国三甲医院进行调研,结果回收后结合客观数据探讨相对价值表。结果:(1)以"人工股骨头假体置换术,骨病型"的工作量为100,其余38项医疗处置的工作量相对价值范围为60~149,变异系数变动范围为14.4%~41.3%,相对价值最高的处置为"胸腰椎融合术,后路法",最低为"腱鞘囊肿切除术";(2)验证了四个维度对医师总工作量的总体解释合理性(调整R~2为0.986),脑力消耗、技能与体力消耗、心理压力对总工作量解释性较高(P<0.05)。结论:运用量值估计法对骨科医师工作量进行评价具有可行性,时间、脑力消耗指数、技能与体力消耗指数、心理压力能够合理解释39项服务项目的医师工作量,可以考虑采用本方法进行院内激励。     

年龄调整率的区间估计及其在宫颈癌患病率估计中的应用

目的 评价三种年龄调整率可信区间估计方法,探索适合江苏省宫颈癌筛查研究中年龄调整患病率可信区间估计的方法.方法 以二项分布正态近似法、Gamma分布法及"确切概率法"进行年龄调整率的区间估计,运用统计模拟考察多种率及阳性数情况下三种方法的区间覆盖率及宽度.结果 当样本量较小(阳性数较少)时,确切概率法的覆盖率离理论可信度的偏差及区间宽度均优于Gamma分布法,两者的覆盖率均明显优于正态近似法;随着阳性数增多,三法各自的覆盖率偏差及区间宽度均逐渐变小,方法间的差异亦逐渐缩小;当阳性数增至30以上时,确切概率法及正态近似法的覆盖率的偏差皆在±1%以内,此时两者的区间宽度接近;而Gamma分布法的覆盖率偏差若要达到1%以内,则要求总阳性数在100以上.无论样本构成是轻度偏离还是明显偏离总体构成,上述规律皆成立.结论 综合考虑区间覆盖率、区间宽度及计算便捷性,建议当总阳性数小于30时,采用确切概率法计算调整率的可信区间;当总阳性数大于等于30时,采用正态近似法.     

Confidence interval estimation for the changepoint of treatment stratification in the presence of a qualitative covariate-treatment interaction

The goal in stratified medicine is to administer the “best” treatment to a patient. Not all patients might benefit from the same treatment; the choice of best treatment can depend on certain patient characteristics. In this article, it is assumed that a time-to-event outcome is considered as a patient-relevant outcome and a qualitative interaction between a continuous covariate and treatment exists, ie, that patients with different values of one specific covariate should be treated differently. We suggest and investigate different methods for confidence interval estimation for the covariate value, where the treatment recommendation should be changed based on data collected in a randomized clinical trial. An adaptation of Fieller's theorem, the delta method, and different bootstrap approaches (normal, percentile-based, wild bootstrap) are investigated and compared in a simulation study. Extensions to multivariable problems are presented and evaluated. We observed appropriate confidence interval coverage following Fieller's theorem irrespective of sample size but at the cost of very wide or even infinite confidence intervals. The delta method and the wild bootstrap approach provided the smallest intervals but inadequate coverage for small to moderate event numbers, also depending on the location of the true changepoint. For the percentile-based bootstrap, wide intervals were observed, and it was slightly conservative regarding coverage, whereas the normal bootstrap did not provide acceptable results for many scenarios. The described methods were also applied to data from a randomized clinical trial comparing two treatments for patients with symptomatic, severe carotid artery stenosis, considering patient's age as predictive marker.