Characteristics and demographic factors of traditional Chinese medicine constitution types among elderly individuals in China:A national multistage cluster random study Author links open overlay panel

Objective:To reveal the distribution characteristics and demographic factors of traditional Chinese medicine(TCM)constitution among elderly individuals in China.Methods: Elderly individuals from seven regions in China were selected as samples in this study using a multistage cluster random sampling method.The basic information questionnaire and Constitution in Chinese Medicine Questionnaire(Elderly Edition)were used.Descriptive statistical analysis,chi-squared tests,and binary logistic regression analysis were used.Results: The single balanced constitution(BC)accounted for 23.9%.The results of the major TCM constitution types showed that BC(43.2%)accounted for the largest proportion and unbalanced constitutions ranged from 0.9%to 15.7%.East China region(odds ratio[OR]=2.097;95%confidence interval[CI],1.912 to 2.301),married status(OR=1.341;95%CI,1.235 to 1.457),and managers(OR=1.254;95%CI,1.044 to 1.505)were significantly associated with BC.Age>70 years was associated with qi-deficiency constitution and blood stasis constitution(BSC).Female sex was significantly associated with yang-deficiency constitution(OR=1.646;95%CI,1.52 to 1.782).Southwest region was significantly associated with phlegm-dampness constitution(OR=1.809;95%CI,1.569 to 2.086).North China region was significantly associated with inherited special constitution(OR=2.521;95%CI,1.569 to 4.05).South China region(OR=2.741;95%CI,1.997 to 1.3.763),Central China region(OR=8.889;95%CI,6.676 to 11.835),senior middle school education(OR=2.442;95%CI,1.932 to 3.088),and managers(OR=1.804;95%CI,1.21 to 2.69)were significantly associated with BSC.Conclusions: This study defined the distribution characteristics and demographic factors of TCM constitution in the elderly population.Adjusting and improving unbalanced constitutions,which are correlated with diseases,can help promote healthy aging through the scientific management of these demographic factors.

Research on Adaptive Cluster Sampling Method Based on PPS

This paper introduces the principle of PPS-based adaptive cluster sampling method and its modified HH estimator and HT estimator calculation method. It compares PPS-based adaptive cluster sampling method with SRS sampling and SRS-based adaptive group. The difference between the group sampling and the advantages and scope of the PPS adaptive cluster sampling method are analyzed. According to the case analysis, the relevant conclusions are drawn: 1) The adaptive cluster sampling method is more accurate than the SRS sampling;2) SRS adaptive The HT estimator of the cluster sampling is more stable than the HH estimator;3) The two estimators of the PPS adaptive cluster sampling method have little difference in the estimation of the population mean, but the HT estimator variance is smaller and more suitable;4) PPS The HH estimator of adaptive cluster sampling is the same as the HH estimator of SRS adaptive cluster sampling, but the variance is larger and unstable.

Hand Gesture Recognition by Accelerometer-Based Cluster Dynamic Time Warping

Aiming at the diversity of hand gesture traces by different people,the article presents novel method called cluster dynamic time warping( CDTW),which is based on the main axis classification and sample clustering of individuals. This method shows good performance on reducing the complexity of recognition and strong robustness of individuals. Data acquisition is implemented on a triaxial accelerometer with 100 Hz sampling frequency. A database of 2400 traces was created by ten subjects for the system testing and evaluation. The overall accuracy was found to be 98. 84% for user independent gesture recognition and 96. 7% for user dependent gesture recognition,higher than dynamic time warping( DTW),derivative DTW( DDTW) and piecewise DTW( PDTW) methods.Computation cost of CDTW in this project has been reduced 11 520 times compared with DTW.

晚期非鳞状非小细胞肺癌患者直接非医疗经济负担及影响因素分析

目的系统分析无表皮生长因子/间变性淋巴瘤激酶(epidermal grouth factor receptor/anaplastic lymphoma kinase,EGFR/ALK)突变的晚期非鳞状非小细胞肺癌(non-small cell lung cancer,NSCLC)患者在疾病治疗过程中发生的直接非医疗费用,分析疾病所致直接非医疗经济负担及其影响因素,以期为制定降低非鳞癌患者疾病相关经济负担的有效措施提供决策建议与参考依据。方法采用方便抽样与整群抽样结合的方法,于2020年11月—2021年6月对上海市、江苏省、福建省、山东省和四川省12家医院的晚期非鳞状NSCLC患者进行一对一问卷调查,收集社会人口学信息和疾病信息,计算患病以来的直接非医疗费用,并利用广义线性回归模型分析其影响因素。结果本研究共纳入目标患者361名,患者自确诊以来的例均直接非医疗费用为13277.33元,其中,营养费用占比最高(30.3%),营养费用、就诊过程相关食宿费用的累积占比为84.6%。将直接非医疗费用及其5类组成部分分别作为因变量,与各变量纳入广义线性回归模型,结果显示:住院次数、平均住院天数对患者的总直接非医疗费用、住宿费用及伙食费用的影响具有统计学意义(P<0.05);病程对患者的总直接非医疗费用及营养费用的影响具有统计学意义(P<0.05);职业类型显著影响患者的总直接医疗费用、伙食及营养费用;独居情况显著影响患者的护工费用;住院次数和户籍显著影响患者的交通费用。结论晚期非鳞状NSCLC患者的直接非医疗负担不可忽视,建议:继续提升国家整体的肿瘤诊疗水平,持续强化县级龙头医院肿瘤综合防治能力,缩小城乡及省际诊疗水平差距;积极推进NSCLC的早诊早治与早期干预,提高患者生存率;通过健全多层次保障体系,提供多方经济补助;推动营养干预早期介入、提倡多样化护理形式等,借助多途径缓解晚期非鳞状NSCLC患者的直接非医疗负担。

Structural equation modeling analysis of factors influencing architects' trust in project design teams

This paper describes a structural equation modeling （SEM） analysis of factors influencing architects＇ trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural design institutes selected radomly from the altogether 59 ones in Shenzhen, P. R. China, and received 130 valid questionnaires. We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trus~ is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

Calibration of a Confidence Interval for a Classification Accuracy

Coverage of nominal 95% confidence intervals of a proportion estimated from a sample obtained under a complex survey design, or a proportion estimated from a ratio of two random variables, can depart significantly from its target. Effective calibration methods exist for intervals for a proportion derived from a single binary study variable, but not for estimates of thematic classification accuracy. To promote a calibration of confidence intervals within the context of land-cover mapping, this study first illustrates a common problem of under and over-coverage with standard confidence intervals, and then proposes a simple and fast calibration that more often than not will improve coverage. The demonstration is with simulated sampling from a classified map with four classes, and a reference class known for every unit in a population of 160,000 units arranged in a square array. The simulations include four common probability sampling designs for accuracy assessment, and three sample sizes. Statistically significant over- and under-coverage was present in estimates of user’s (UA) and producer’s accuracy (PA) as well as in estimates of class area proportion. A calibration with Bayes intervals for UA and PA was most efficient with smaller sample sizes and two cluster sampling designs.

Quantitative study of poplar plantations in three Iranian provinces

Fast growing poplar species enjoy a highly favored position in Iran’s forest product industries. However, information on poplar plantations, such as areas, growing stock and harvest volumes, are largely obtained by non scientific means and poorly executed methods. A few studies have been conducted to obtain data on the capacity of poplar plantations, their extent, existing growing stock, distribution and species choice in three provinces, i.e., Western Azerbaijan, Kurdistan and Hamedan, with relatively well developed management systems. We opted for a cluster method, a standard sampling method for conducting similar investigations, consisting of two phases. In the first phase we collected library information and conducted half-open interviews with villagers. In the second phase field measurements in the villages of these three provinces were carried out. Information from field measurements on growing stock, cultivated areas, dominant species were used to estimate volumes by way of volume and weight tables. Results obtained from the present study indicate that the average annual volume of timber harvested in the three provinces was 697,723 m3, with an average sampling error of 22.7 per cent. This annual volume of poplar timber harvested from the three provinces was estimated to amount to about 25 per cent of overall harvest; at that rate, the overall annual utilization potential of poplar plantations will be 10 million m3, which constitutes a reliable resource of raw timber for use in wood and paper industries.

Comparison of Cost Incurred in Two Survey Methodologies for Measles Vaccine Coverage

Background: The World Health Organization (WHO) initiated the Expanded Program on Immunization (EPI) in 1974. It has been widely used in different studies. Along with this, other survey methodologies have been compared to study immunization coverage at different regions. To consider different survey methodologies, one of the most important factors is the cost incurred that survey methodology. A survey method is considered as more efficient or better than the other survey method if the cost incurred in a particular method is less than the other one. Methods: In this study, cost incurred in two stage (30 × 30) cluster sampling and systematic sampling methods have been compared using a cost function for measles vaccine coverage. Measles vaccine coverage data has been taken from the survey “Comparison of Two Survey Methodologies to Estimates Total Vaccination Coverage” sponsored by Indian Council of Medical Research (ICMR), New Delhi. Results: The results show that there are no significant differences between the point estimates of measles vaccine coverage under the considered survey methodologies. But the cost incurred in systematic sampling is more than that of two stage cluster sampling. Conclusion: It can be concluded that systematic sampling survey is costlier than that of two stage cluster sampling for this study population.

Modifications on the Strand’s Sampling Method Applied to Stands of Pinus elliottii Engelm

This work was carried out with the objective of proposing some changes in the Strand’s sampling method, in which the trees are selected in sampling units with probability proportional to its diameter for the calculation of the stand density and basal area, and proportional to its height for the calculation of volume per hectare. Data used to evaluate the efficiency of the sampling of Strand in clusters were collected in stands of Pinus elliottii Engelm, located in a National Forest, Rio Grande do Sul State, Brazil. In the course of this research work it was proposed to convert the sampling unit into a cluster, structurally more efficient to obtain consistent estimates of volume and of dominant heights, using volumetric equivalence, which results in a form factor equal to one for the final calculation of volume per hectare and an indirect method to obtain the average height of Lorey. The objectives of this study were achieved, because with this methodology it is not necessary to measure heights of trees in the sampling unit, except a dominant height by cluster to evaluate sites. The development of independent estimators for basal area and volume gave rise to the proposition of an estimator for average height of Lorey, but without measuring any tree height in the sampling. The proposed methodology is an attractive solution to reduce costs in forest inventories, with the ability to have greater accuracy and scope for information at the level of compartments, without increasing the cost of sampling in comparison to that performed with units of fixed area. The use of smaller permanent sampling units with higher intensity in the compartments before the final cut will substantially increase the precision of the estimators in these management units, which will enable them to eliminate the pre-cut inventory in forest enterprises.

Maternal and neonatal outcomes in multiple pregnancy: A multicentre study in the Beijing population

Objective:To compare the adverse maternal and neonatal outcomes of multiple pregnancy and singleton pregnancy from multiple medical centers in Beijing.Methods:Data concerning maternal and neonatal adverse outcomes in multiple and singleton pregnancies were collected from 15 hospitals in Beijing by a systemic cluster sampling survey conducted from 20 June to 30 November 2013.The SPSS software (version 20.0) was used for data analysis.The x2 test was used tbr statistical analyses.Results:The rate of caesarean deliveries was much higher in women with multiple pregnancies (85.8％) than that in women with singleton pregnancies (42.6％,X2 =190.8,P ＜ 0.001).The incidences of anemia (X2 =40.023,P ＜ 0.001),preterm labor (X2 =1021.172,P ＜ 0.001),gestational diabetes mellitus (X2 =9.311,P ＜ 0.01),hypertensive disorders (X2 =122.708,P ＜ 0.001)and post-partum hemorrhage (X2-48.550,P ＜ 0.001) was significantly increased with multiple pregnancy.In addition,multiple pregnancy was associated with a significantly higher rate of small-for-gestational-age infants (X2 =92.602,P ＜ 0.001),low birth weight (X2 =1141.713,P ＜ 0.001),and neonatal intensive care unit (NICU) admission (X2 =340.129,P＜ 0.001).Conclusions:Multiple pregnancy is a significant risk factor for adverse maternal and neonatal outcomes in Beijing.Improving obstetric care for multiple pregnancy,particularly in reducing preterm labor,is required to reduce the risk to mothers and infants.

Two-Stage Negative Adaptive Cluster Sampling

If the population is rare and clustered,then simple random sampling gives a poor estimate of the population total.For such type of populations,adaptive cluster sampling is useful.But it loses control on the final sample size.Hence,the cost of sampling increases substantially.To overcome this problem,the surveyors often use auxiliary information which is easy to obtain and inexpensive.An attempt is made through the auxiliary information to control the final sample size.In this article,we have proposed two-stage negative adaptive cluster sampling design.It is a new design,which is a combination of two-stage sampling and negative adaptive cluster sampling designs.In this design,we consider an auxiliary variablewhich is highly negatively correlatedwith the variable of interest and auxiliary information is completely known.In the first stage of this design,an initial random sample is drawn by using the auxiliary information.Further,using Thompson’s(JAmStat Assoc 85:1050-1059,1990)adaptive procedure networks in the population are discovered.These networks serve as the primary-stage units(PSUs).In the second stage,random samples of unequal sizes are drawn from the PSUs to get the secondary-stage units(SSUs).The values of the auxiliary variable and the variable of interest are recorded for these SSUs.Regression estimator is proposed to estimate the population total of the variable of interest.A new estimator,Composite Horwitz-Thompson(CHT)-type estimator,is also proposed.It is based on only the information on the variable of interest.Variances of the above two estimators along with their unbiased estimators are derived.Using this proposed methodology,sample survey was conducted at Western Ghat of Maharashtra,India.The comparison of the performance of these estimators and methodology is presented and compared with other existing methods.The cost-benefit analysis is given.

Nonignorable item nonresponse in panel data

To estimate unknown population parameters based on panel data having nonignorable item nonresponse,we propose an innovative data grouping approach according to the number of observed components in the multivariate outcome y when the joint distribution of y and asso-ciated covariate x is nonparametric and the nonresponse probability conditional on y and x has a parametric form.To deal with the identifiability issue,we utilise a nonresponse instrument 2,an auxiliary variable related to y but not related to the nonresponse probability conditional ony and x.We apply a modified generalised method of moments to obtain estimators of the param-eters in the nonresponse probability,and a generalised regression estimation to utilise covariate information for efficient estimation of population parameters.Consistency and asymptotic nor-mality of the proposed estimators of the population parameters are established.Simulation and real data results are presented.

k-step adaptive cluster sampling with Horvitz-Thompson estimator

Adaptive cluster sampling （ACS） has been widely used for data collection of environment and natural resources. However, the randomness of its final sample size often impedes the use of this method. To control the final sample sizes, in this study, a k-step ACS based on Horvitz-Thompson （HT） estimator was developed and an unbiased estimator was derived. The k-step ACS-HT was assessed first using a simulated example and then using a real survey for numbers of plants for three species that were characterized by clustered and patchily spatial distributions. The effectiveness of this sampling design method was assessed in comparison with ACS Hansen-Hurwitz （ACS-HH） and ACS- HT estimators, and k-step ACS-HT estimator. The effectiveness of using different k- step sizes was also compared. The results showed that k-step ACS^HT estimator was most effective and ACS-HH was the least. Moreover, stable sample mean and variance estimates could be obtained after a certain number of steps, but depending on plant species, k-step ACS without replacement was slightly more effective than that with replacement. In k-step ACS, the variance estimate of one-step ACS is much larger than other k-step ACS （k 〉 1）, but it is smaller than ACS. This implies that k-step ACS is more effective than traditional ACS, besides, the final sample size can be controlled easily in population with big clusters.