纵向研究缺失数据多重填补及混合效应模型分析

目的阐明马尔可夫链蒙特卡罗(MCMC)多重填补与重复测量资料混合效应线性模型分析的原理,完成纵向监测数据缺失模型的软件实现。方法根据222例高血压患者纵向监测的完全数据,产生缺失比例为18.92%的随机缺失数据集。应用MCMC多重填补方法,进行缺失值填补的模拟研究以及实例分析,并实现重复测量混合效应线性模型分析。结果模拟研究和实例分析表明,样本例数200,缺失比例20%,MCMC法多重填补5次所得结果最稳健;填补前缺失数据与完全数据的混合效应模型分析结果不同,填补后完整数据与完全数据的混合效应模型分析结果相同。结论 MCMC多重填补可以充分利用缺失资料信息,是处理缺失数据模型分析的有效方法之一;针对出现缺失的重复测量资料,结合应用混合效应模型与MCMC多重填补2种方法,从而得出更为符合客观实际的结果。     

Streamlining the decision-making process for international DNA kinship matching using Worldwide allele frequencies and tailored cutoff log10LR thresholds

The identification of human remains belonging to missing persons is one of the main challenges for forensic genetics. Although other means of identification can be applied to missing person investigations, DNA is often extremely valuable to further support or refute potential associations. When reference DNA samples cannot be collected from personal items belonging to a missing person, a direct DNA identification cannot be carried out. However, identifications can be made indirectly using DNA from the missing person’s relatives. The ranking of likelihood ratio (LR) values, which measure the fit of a missing person for any given pedigree, is often the first step in selecting candidates in a DNA database. Although implementing DNA kinship matching in a national environment is feasible, many challenges need to be resolved before applying this method to an international configuration. In this study, we present an innovative and intuitive method to perform international DNA kinship matching and facilitate the comparison of DNA profiles when the ancestry is unknown or unsure and/or when different marker sets are used. This straightforward method, which is based on calculations performed with the DNA matching software BONAPARTE, Worldwide allele frequencies and tailored cutoff log₁₀LR thresholds, allows for the classification of potential candidates according to the strength of the DNA evidence and the predicted proportion of adventitious matches. This is a powerful method for streamlining the decision-making process in missing person investigations and DVI processes, especially when there are low numbers of overlapping typed STRs. Intuitive interpretation tables and a decision tree will help strengthen international data comparison for the identification of reported missing individuals discovered outside their national borders.     

Association between missing tooth count and mortality: A systematic review

Purpose

The purpose of this review was to analyze existing literature on the relationship between tooth count and mortality by evaluating the findings in the context of methodological variations. We aimed at addressing the question of whether preserving natural teeth can impact mortality.

医院传染病报告质量管理工作探讨——以池州市第二人民医院为例

目的:提高医院传染病报告质量,降低疫情报告漏报率、迟报率,为某院传染病管理工作提供有力保障.方法:对某院2011~2013年度的传染病报告质量和漏报情况进行分析和整改.结果:某院2011~2013年度共查出传染病1686例,报告1640例.主要迟漏报病种为肺结核、乙肝.漏报率由2011年的4.84%下降至2013年的0.36%,迟报率由2011年的7.12%下降到2013年的1.45%,完整率由96.9%提高到99.5%,准确率由90.8%提高到99.5%.结论:建立健全的传染病管理体系,增加自查力度,加强医护人员培训,奖罚分明,能有效提高传染病报告工作质量.     

Dental patients’ awareness and knowledge in using dental implants as an option in replacing missing teeth: A survey in Riyadh,Saudi Arabia

Aim

The purpose of this survey was to assess the level, sources, and need for information about dental implants among a selected sample of dental patients in Riyadh, Saudi Arabia.

Materials and methods

Patients’ knowledge and awareness in using dental implants as an option in replacing missing teeth were evaluated through a standardized self- explanatory questionnaire distributed in two places in Riyadh: Military Hospital and College of Dentistry, King Saud University (Darraiyah campus). The questionnaires were handed to the patients during their regular dental visits. A total of 379 subjects were included in this survey.

Results

The results of this study indicate that 66.4% of the subjects knew about dental implants. The subjects’ friends and their relatives were the main source of information about dental implants for 31.5% of the subjects, and dentists were the secondary source for 28.3% of the sample. About 82.4% of the subjects need more information about dental implants and 85.2% of them chose the dentist to be the desired source for such information, followed by the internet in 28.5% of the cases. Almost 74.4% of those surveyed did not know if their regular dentists use dental implants. High cost was the major factor in preventing patients from choosing implants in 86.5% of the cases while the long treatment time and fear of surgery was the factor in 71% and 68.6% of the subjects, respectively.

Conclusion

The results of this survey showed an acceptable level of awareness about dental implants among a selected sample of dental patients in Riyadh. It also showed the need for providing more general and accurate information to the patients about this treatment modality.     

Modification of Esthetics Using a Combined Orthodontic and a Prosthodontic Approach: A Case Report

A patient sometimes requires a multidisciplinary approach to correct the esthetics and to improve the occlusion. This case report describes the management of an adult female patient with a convex profile, proclined upper and lower anterior teeth, missing upper left lateral incisor and peg shaped upper right lateral incisor tooth through orthodontic and prosthodontic treatment.     

Missing data approaches in eHealth research: simulation study and a tutorial for nonmathematically inclined researchers

Background

Missing data is a common nuisance in eHealth research: it is hard to prevent and may invalidate research findings.

Objective

In this paper several statistical approaches to data “missingness” are discussed and tested in a simulation study. Basic approaches (complete case analysis, mean imputation, and last observation carried forward) and advanced methods (expectation maximization, regression imputation, and multiple imputation) are included in this analysis, and strengths and weaknesses are discussed.

Methods

The dataset used for the simulation was obtained from a prospective cohort study following participants in an online self-help program for problem drinkers. It contained 124 nonnormally distributed endpoints, that is, daily alcohol consumption counts of the study respondents. Missingness at random (MAR) was induced in a selected variable for 50% of the cases. Validity, reliability, and coverage of the estimates obtained using the different imputation methods were calculated by performing a bootstrapping simulation study.

Results

In the performed simulation study, the use of multiple imputation techniques led to accurate results. Differences were found between the 4 tested multiple imputation programs: NORM, MICE, Amelia II, and SPSS MI. Among the tested approaches, Amelia II outperformed the others, led to the smallest deviation from the reference value (Cohen’s d = 0.06), and had the largest coverage percentage of the reference confidence interval (96%).

Conclusions

The use of multiple imputation improves the validity of the results when analyzing datasets with missing observations. Some of the often-used approaches (LOCF, complete cases analysis) did not perform well, and, hence, we recommend not using these. Accumulating support for the analysis of multiple imputed datasets is seen in more recent versions of some of the widely used statistical software programs making the use of multiple imputation more readily available to less mathematically inclined researchers.     

Longitudinal Data Analysis. A Comparison Between Generalized Estimating Equations and Random Coefficient Analysis

The analysis of data from longitudinal studies requires special techniques, which take into account the fact that the repeated measurements within one individual are correlated. In this paper, the two most commonly used techniques to analyze longitudinal data are compared: generalized estimating equations (GEE) and random coefficient analysis. Both techniques were used to analyze a longitudinal dataset with six measurements on 147 subjects. The purpose of the example was to analyze the relationship between serum cholesterol and four predictor variables, i.e., physical fitness at baseline, body fatness (measured by sum of the thickness of four skinfolds), smoking and gender. The results showed that for a continuous outcome variable, GEE and random coefficient analysis gave comparable results, i.e., GEE-analysis with an exchangeable correlation structure and random coefficient analysis with only a random intercept were the same. There was also no difference between both techniques in the analysis of a dataset with missing data, even when the missing data was highly selective on earlier observed data. For a dichotomous outcome variable, the magnitude of the regression coefficients and standard errors was higher when calculated with random coefficient analysis then when calculated with GEE-analysis. Analysis of a dataset with missing data with a dichotomous outcome variable showed unpredictable results for both GEE and random coefficient analysis. It can be concluded that for a continuous outcome variable, GEE and random coefficient analysis are comparable. Longitudinal data-analysis with dichotomous outcome variables should, however, be interpreted with caution, especially when there are missing data.     

多重填补法Markov Chain Monte Carlo模型在有缺失值的妇幼卫生纵向数据中的应用

目的针对妇幼卫生纵向数据的任意缺失模式，采用多重填补方法进行填补，探求最佳填补结果，以便对数据作进一步分析与研究。方法运用SAS9．0，采用多重填补方法Markov China Monte Carlo(MCMC)模型对缺失数据进行多次填补并综合分析。结果填补5次所得结果最优。结论多重填补方法可以处理有缺失数据资料中的许多普遍问题，可提高统计效率，尤其是MCMC模型在处理复杂的缺失数据上，优势明显。     

多重填补法与Ad Hoc法对模拟纵向数据集缺失值处理的比较

目的：采用多重填补法(multiple imputation，MI)和Ad hoc法分别对模拟的纵向数据集中的缺失值进行处理，较两种方法的优劣并探讨其适用性。方法：运用SAS9．0，采用数据模拟技术，分别模拟纵向完整数据集和具有各种缺失的随机缺失数据集，分别用MI和Ad hoc法对各缺失数据集进行处理，对结果进行比较和分析。结果：数据缺失率≤％时，Ad hoc方法有一定优势；数据缺失率在20％-40％时，经MI处理后的分析结果更接近“真实”；数据缺失率≥50％时，两种方法均无效。结论：对不同缺失率的数据集，MI和Ad hoc法对缺失值的处理各有优劣。