第五次全国人口普查表长表抽样方法

20 0 0年第五次全国人口普查首次采用了普查表长短表技术。论述了人口普查长短表技术的特点、组织实施方法、长表抽样方法以及长表抽样误差分析     

旅游图书过目疑误

本文通过诸多实例，指出当代旅游文化类图书中存在叙述不合史实、引文不核原著、数字标注不确、行文自相矛盾等问题，强调应该进一步提高旅游文化类图书的质量。     

门诊西药房药品调剂差错的防范措施

目的保证合理安全用药,提高门诊药学服务质量。方法结合笔者经验,从环境、管理制度、药师自身因素等着手,提出几项具体药品调剂差错防范措施。结果减少了药品调剂差错的发生,提高药学服务质量。结论防止和减少差错发生是一项长期进行的工作,药学人员应坚持不懈地努力,最大限度地减少差错发生。     

A New Method to Measure the Performance of Leveraged Exchange‐Traded Funds

We examine the effects of daily return compounding, financing costs, and management factors on the performance of leveraged exchange‐traded funds (LETFs) over various holding periods. We propose a new method to measure LETFs’ tracking errors that allows us to disentangle these effects. Our results show that the compounding effect generally has more influence on tracking errors than other factors, especially for long holding periods and in a “sideways” market. The explicit costs (i.e., the expense ratios) and other factors (e.g., financing costs) can materially affect the performance of LETFs, especially for those with high leverage ratios and bear funds.     

Time-series–cross-section Data

This article treats the analysis of 'time-series–cross-section' (TSCS) data. Such data consists of repeated observations on a series of fixed units. Examples of such data are annual observations on the political economy of OECD nations in the post-war era. TSCS data is distinguished from 'panel' data, in that asymptotics are in the number of repeated observations, not the number of units.
The article begins by treating the complications of TSCS data in an 'old-fashioned' manner, that is, as a nuisance which causes estimation difficulties. It claims that TSCS data should be analyzed via ordinary least squares with 'panel correct standard errors' rather than generalized least squares methods. Dynamics should be modeled via a lagged dependent variable or, if appropriate, a single equation error correction model.
The article then treats more modern issues, in particular, the modeling of spatial effects and heterogeneity. It also claims that heterogeneity should be assessed with 'panel cross-validation' as well as more standard tests. The article concludes with a discussion of estimation in the presence of a binary dependent variable.     

Prevalence and cost of hospital medical errors in the general and elderly United States populations

Abstract

Objective:

The primary objective of this study was to quantify the differences in the prevalence rate and costs of hospital medical errors between the general population and an elderly population aged ≥65 years.

Methods:

Methods from an actuarial study of medical errors were modified to identify medical errors in the Premier Hospital Database using data from 2009. Visits with more than four medical errors were removed from the population to avoid over-estimation of cost. Prevalence rates were calculated based on the total number of inpatient visits.

Results:

There were 3,466,596 total inpatient visits in 2009. Of these, 1,230,836 (36%) occurred in people aged ≥ 65. The prevalence rate was 49 medical errors per 1000 inpatient visits in the general cohort and 79 medical errors per 1000 inpatient visits for the elderly cohort. The top 10 medical errors accounted for more than 80% of the total in the general cohort and the 65+ cohort. The most costly medical error for the general population was postoperative infection ($569,287,000). Pressure ulcers were most costly ($347,166,257) in the elderly population.

Limitations:

This study was conducted with a hospital administrative database, and assumptions were necessary to identify medical errors in the database. Further, there was no method to identify errors of omission or misdiagnoses within the database.

Conclusions:

This study indicates that prevalence of hospital medical errors for the elderly is greater than the general population and the associated cost of medical errors in the elderly population is quite substantial. Hospitals which further focus their attention on medical errors in the elderly population may see a significant reduction in costs due to medical errors as a disproportionate percentage of medical errors occur in this age group.     

Sample size determination of binomial data with the presence of misclassification

We propose a double sampling scheme with two classifiers to address the problem of optimal sample size when misclassification among binomial observations is observed. The classifiers vary with respect to the classifying cost and precision. Furthermore, since the data are unknown, an additional constraint is set on the probability of observing ``undesirable' data. The method is developed following the Bayesian point of view.     

Time Series Based Errors and Empirical Errors in Fertility Forecasts in the Nordic Countries*

We use ARCH time series models to derive model based prediction intervals for the Total Fertility Rate (TFR) in Norway, Sweden, Finland, and Denmark up to 2050. For the short term (5–10 yrs), expected TFR‐errors are compared with empirical forecast errors observed in historical population forecasts prepared by the statistical agencies in these countries since 1969. Medium‐term and long‐term (up to 50 years) errors are compared with error patterns based on so‐called naïve forecasts, i.e. forecasts that assume that recently observed TFR‐levels also apply for the future.     

The effect of repeat restructuring charges on analysts’ forecast revisions and accuracy

The primary objective of this study is to examine the effect of prior restructuring charges on analyst forecast revisions and accuracy. We find evidence that analysts respond differently to first-time restructuring firms than to repeat restructuring firms. Analysts revise their forecasts of both one-year-ahead earnings and five-year long-term growth in earnings more negatively for first-time restructuring firms than for firms with prior charges. When we examine forecast errors in the year subsequent to the restructuring, we find that current charges complicate analysts’ earnings forecast task. We further find that the decline in analyst forecast accuracy is mitigated by prior charges within past two years.     

THE STATISTICS OF LONG-HORIZON REGRESSIONS REVISITED1

This paper compares commonly used approaches for estimating the relation between long-horizon returns and a predetermined variable X₁, such as dividend yields. Specifically, we look at regression of (i) nonoverlapping multiperiod returns on X_t (ii) overlapping multiperiod returns on X_t, (iii) single-period returns on multiperiod X_t, and (iv) single-period returns on X_t and its implied long-horizon regression coefficient. We provide analytical formulae which quantify the efficiency of the estimators used in the various approaches. Using the formulae, as well as Monte Carlo simulations, we demonstrate that the relative efficiency of the estimators used in the various approaches differs remarkably, depending on the dynamic structure of the regressor. of special interest for financial economists, when the regressors are highly autocorrelated, we find that the regressions (ii) (iii), and (iv) provide only marginal efficiency gains above and beyond the nonoverlapping long-horizon regression.