Measurement and analysis of demographic processes: the characteristics of generation

Since it would take too long (100 years) to ascertain all demographic data about a given age group, i.e., all those born in a given year, these data are determined hypothetically by measuring the various characteristics of persons of all ages in a given time period (1-2 years). Also needed is an indicator of the population as a whole; cumulative coefficients are used for this purpose. One of these is the overall coefficient of births, meaning the number of children a women would have over her whole period of fertility if she had the precise number of children at each period in her life as other women of that age. An analogous indicator is used for measuring mortality--the average life expectancy of a person at each stage in his life. The crude coefficient of population reproduction represents the number of girls to which each woman will give birth between the ages of 15 and 50. This has to be corrected by the number of those who will not live to reproductive age. The result is the corrected coefficient of reproduction of the female population. This coefficient is often thought to reflect the population's growth prospects; if less than unity, therefore, the population will not reproduce itself. This is an incorrect interpretation. The impact of immigration and emigration on the population must also be incorportated. In addition to the above hypothetical indicators, we must also develop real population indicators. Techniques must also be employed to evaluate the reliability of these demographic indicators.     

A methodological approach to the comparison of municipal balance-sheet figures

In the comparison of municipalities balance sheets figures, the per-resident ratios lose some of their relevance as indicators of municipal expenditure or taxation behaviour. At this level of spatial disaggregation, the resident population is generally not in a direct relationship with balance sheets figures; the problem is evident especially for those municipalities with significant flows of non-residents, demanding and paying for services. The paper provides a frame of reference within which the measurement of municipal behaviour is conditioned to the approximation of the unobserved “real” size of each individual municipality. The joint use of several types of information about the structure of municipalities yields composite indicators of greater statistical relevance than the usual indicators based on the residential population alone.     

Graphical representation of survival curves in the presence of time-dependent categorical covariates with application to liver transplantation

Graphical representation of survival curves is often used to illustrate associations between exposures and time-to-event outcomes. However, when exposures are time-dependent, calculation of survival probabilities is not straightforward. Our aim was to develop a method to estimate time-dependent survival probabilities and represent them graphically. Cox models with time-dependent indicators to represent state changes were fitted, and survival probabilities were plotted using pre-specified times of state changes. Time-varying hazard ratios for the state change were also explored. The method was applied to data from the Adult-to-Adult Living Donor Liver Transplantation Cohort Study (A2ALL). Survival curves showing a ‘split’ at a pre-specified time t allow for the qualitative comparison of survival probabilities between patients with similar baseline covariates who do and do not experience a state change at time t. Time since state change interactions can be visually represented to reflect changing hazard ratios over time. A2ALL study results showed differences in survival probabilities among those who did not receive a transplant, received a living donor transplant, and received a deceased donor transplant. These graphical representations of survival curves with time-dependent indicators improve upon previous methods and allow for clinically meaningful interpretation.     

Statistical analysis of performance indicators in UK higher education

Summary.  Attempts to measure the quality with which institutions such as hospitals and universities carry out their public mandates have gained in frequency and sophistication over the last decade. We examine methods for creating performance indicators in multilevel or hierarchical settings (e.g. students nested within universities) based on a dichotomous outcome variable (e.g. drop-out from the higher education system). The profiling methods that we study involve the indirect measurement of quality, by comparing institutional outputs after adjusting for inputs, rather than directly attempting to measure the quality of the processes unfolding inside the institutions. In the context of an extended case-study of the creation of performance indicators for universities in the UK higher education system, we demonstrate the large sample functional equivalence between a method based on indirect standardization and an approach based on fixed effects hierarchical modelling, offer simulation results on the performance of the standardization method in null and non-null settings, examine the sensitivity of this method to the inadvertent omission of relevant adjustment variables, explore random-effects reformulations and characterize settings in which they are preferable to fixed effects hierarchical modelling in this type of quality assessment and discuss extensions to longitudinal quality modelling and the overall pros and cons of institutional profiling. Our results are couched in the language of higher education but apply with equal force to other settings with dichotomous response variables, such as the examination of observed and expected rates of mortality (or other adverse outcomes) in investigations of the quality of health care or the study of retention rates in the workplace.     

Approximate confidence intervals for the weighted kappa coefficient of a binary diagnostic test subject to a case–control design

Case–control design to assess the accuracy of a binary diagnostic test (BDT) is very frequent in clinical practice. This design consists of applying the diagnostic test to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. The sensitivity of the diagnostic test is estimated from the case sample and the specificity is estimated from the control sample. Another parameter which is used to assess the performance of a BDT is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, confidence intervals are studied for the weighted kappa coefficient subject to a case–control design and a method is proposed to calculate the sample sizes to estimate this parameter. The results obtained were applied to a real example.     

Semi-parametric Bayesian Analysis of the Proportional Hazard Rate Model An Application to the Effect of Training Programs on Graduate Unemployment

In this paper, we introduce a semi-parametric Bayesian methodology based on the proportional hazard model that assumes that the baseline hazard function is constant over segments but, by contrast to what is usually assumed in the literature, with the periods at which the function changes not being specified in advance. The methodology is applied to explore the impact of Vocational Training courses offered by the University of Zaragoza (Spain) on the duration of the initial periods of unemployment experienced by graduate leavers. The framework is very flexible and allows us, in particular, to capture the presence of seasonality in the job insertion of graduates.     

Point estimation of lower quantiles based on two-sampling scheme

ABSTRACT

Consider a two-sampling scheme in which an initial sample is first taken from the underlying population and then by assuming a suitable restriction on this sample, some more data points are observed as a new restricted sample. This sampling scheme is used to do inference about the lower quantiles of the underlying distribution. The results are compared with those of simple random sampling in view of mean squared error and Pitman’s measure of closeness criteria for exponential and uniform distributions. It will be shown that the proposed sampling scheme would improve the performance of the point estimators of the lower quantiles of the population.     

Population projections--a forecast or a perspective calculation

The author argues that population projections should not be treated as forecasts but as provisional calculations based on certain known or assumed relationships. Therefore, when these relationships change, so should the projections that are based on them. It is suggested that many users think of population projections as forecasts, which often do not materialize because the assumptions on which they are based turn out to be invalid. The policy implications of such a distinction are considered.     

Accounting for Follow-up Bias in Estimation of Human Immunodeficiency Virus Incidence Rates

The objective of this paper is to describe methods for estimating current incidence rates for human immunodeficiency virus (HIV) that account for follow-up bias. Follow-up bias arises when the incidence rate among individuals in a cohort who return for follow-up is different from the incidence rate among those who do not return. The methods are based on the use of early markers of HIV infection such as p24 antigen. The first method, called the cross-sectional method, uses only data collected at an initial base-line visit. The method does not require follow-up data but does require a priori knowledge of the mean duration of the marker (μ). A confidence interval procedure is developed that accounts for uncertainty in μ. The second method combines the base-line data from all individuals together with follow-up data from those individuals who return for follow-up. This method has the distinct advantage of not requiring prior information about μ. Several confidence interval procedures for the incidence rate are compared by simulation. The methods are applied to a study in India to estimate current HIV incidence. These data suggest that the epidemic is growing rapidly in some subpopulations in India.     

What Difference Does the Dependence Between Durations Make? Insights for Population Studies of Aging

The interpretation of age-specific changes in hazards, relative risks, genetic parameters and other indicators of aging calculated from data on related individuals should take into account the regularities of bivariate selection. Due to such selection the hazard rate calculated for twins who have survived to a certain age may be lower than for singletons, even if marginal chances of survival for all individuals are the same. In a mixed population of relatives the proportion of pairs with closer family links increases with age, even if all marginal individual chances of survival are the same. The proportion of chronic conditions for MZ twins observed in a cross-sectional study may be different from that of DZ twins. The age-dependence of relative risks calculated in genetic-epidemiological studies of twins does not necessarily reflect changes in genetic influence on individual susceptibility to disease and death during the aging process. The age-related changes in heritability of susceptibility estimated in twin studies may have nothing to do with changes in the genetic determination of diseases with age. These issues are illustrated by empirical graphs together with the results of modeling and statistical analysis.     

Fraction of design space plots for generalized linear models

The use of graphical methods for comparing the quality of prediction throughout the design space of an experiment has been explored extensively for responses modeled with standard linear models. In this paper, fraction of design space (FDS) plots are adapted to evaluate designs for generalized linear models (GLMs). Since the quality of designs for GLMs depends on the model parameters, initial parameter estimates need to be provided by the experimenter. Consequently, an important question to consider is the design's robustness to user misspecification of the initial parameter estimates. FDS plots provide a graphical way of assessing the relative merits of different designs under a variety of types of parameter misspecification. Examples using logistic and Poisson regression models with their canonical links are used to demonstrate the benefits of the FDS plots.     

Bayesian demography: projecting the Iraqi Kurdish population, 1977-1990

"Projecting populations that have sparse or unreliable data, such as those of many developing countries, presents a challenge to demographers. The assumptions that they make to project data-poor populations frequently fall into the realm of ?educated guesses', and the resulting projections, often regarded as forecasts, are valid only to the extent that the assumptions on which they are based reasonably represent the past or future, as the case may be. These traditional projection techniques do not incorporate a demographer's assessment of uncertainty in the assumptions. Addressing the challenges of forecasting a data-poor population, we project the Iraqi Kurdish population using a Bayesian approach. This approach incorporates a demographer's uncertainty about past and future characteristics of the population in the form of elicited prior distributions."     

Simultaneous modelling of multiple traffic safety performance indicators by using a multivariate generalized linear mixed model

Summary.  Traffic safety in the UK is one of the increasing number of areas where central government sets targets based on 'outcome-focused' performance indicators (PIs). Judgments about such PIs are often based solely on rankings of raw indicators and simple league tables dominate centrally published analyses. There is a considerable statistical literature examining health and education issues which has tended to use the generalized linear mixed model (GLMM) to address variability in the data when drawing inferences about relative performance from headline PIs. This methodology could obviously be applied in contexts such as traffic safety. However, when such models are applied to the fairly crude data sets that are currently available, the interval estimates generated, e.g. in respect of rankings, are often too broad to allow much real differentiation between the traffic safety performance of the units that are being considered. Such results sit uncomfortably with the ethos of 'performance management' and raise the question of whether the inference from such data sets about relative performance can be improved in some way. Motivated by consideration of a set of nine road safety performance indicators measured on English local authorities in the year 2000, the paper considers methods to strengthen the weak inference that is obtained from GLMMs of individual indicators by simultaneous, multivariate modelling of a range of related indicators. The correlation structure between indicators is used to reduce the uncertainty that is associated with rankings of any one of the individual indicators. The results demonstrate that credible intervals can be substantially narrowed by the use of the multivariate GLMM approach and that multivariate modelling of multiple PIs may therefore have considerable potential for introducing more robust and realistic assessments of differential performance in some contexts.     

贫困缺口总指数的构造、分解与应用

本文构造了一个新贫困指数 ,通过对 指数的因素分解及衍生指数的构造,提出了一些重要贫困指标的预测和推算办法。基于CHNS1991-2011年跨度20年的8轮调查数据进行实证分析,结果表明,我国农村近20年来总贫困缺口率呈现年均6.39%的缩减率,其贡献全部来自贫困人口总规模递减这一因素的影响,而另外两个因素,即平均贫困缺口水平和贫困差异度则呈现年均小幅上升趋势,表明减贫质量不容乐观;以现有减贫模式对我国农村2020年的平均贫困缺口水平、贫困不平等程度、贫困规模等指标进行预测显示,减贫目标依然任重道远;提出了采用精准减贫,重心在于提升贫困人口获取收入的能力和缩小贫困不平等程度的相关建议。     

数据包络方法评价企业绩效的有效性研究

旨在研究数据包络方法评价企业绩效的有效性。首先从理论上提出了四个假设,其次选取了2012年中国803家制造业上市公司作为样本数据,对四个假设从绝对有效性和相对有效性两个方面进行了实证检验。最后得出结论:数据包络方法测算的企业效率值与传统绩效评价指标显著正相关,而且在不同的效率水平上、不同地区、不同行业,该效率值作为评价企业绩效的指标既是绝对有效的,也是相对有效的。     

The split sample permutation t-tests

Without the exchangeability assumption, permutation tests for comparing two population means do not provide exact control of the probability of making a Type I error. Another drawback of permutation tests is that it cannot be used to test hypothesis about one population. In this paper, we propose a new type of permutation tests for testing the difference between two population means: the split sample permutation t-tests. We show that the split sample permutation t-tests do not require the exchangeability assumption, are asymptotically exact and can be easily extended to testing hypothesis about one population. Extensive simulations were carried out to evaluate the performance of two specific split sample permutation t-tests: the split in the middle permutation t-test and the split in the end permutation t-test. The simulation results show that the split in the middle permutation t-test has comparable performance to the permutation test if the population distributions are symmetric and satisfy the exchangeability assumption. Otherwise, the split in the end permutation t-test has significantly more accurate control of level of significance than the split in the middle permutation t-test and other existing permutation tests.     

Approximate MLEs of the parameters of location-scale models under type II censoring

Log-location-scale distributions are widely used parametric models that have fundamental importance in both parametric and semiparametric frameworks. The likelihood equations based on a Type II censored sample from location-scale distributions do not provide explicit solutions for the para-meters. Statistical software is widely available and is based on iterative methods (such as, Newton Raphson Algorithm, EM algorithm etc.), which require starting values near the global maximum. There are also many situations that the specialized software does not handle. This paper provides a method for determining explicit estimators for the location and scale parameters by approximating the likelihood function, where the method does not require any starting values. The performance of the proposed approximate method for the Weibull distribution and Log-Logistic distributions is compared with those based on iterative methods through the use of simulation studies for a wide range of sample size and Type II censoring schemes. Here we also examine the probability coverages of the pivotal quantities based on asymptotic normality. In addition, two examples are given.     

Quality Control Chart for the Mean using Double Ranked Set Sampling

In this paper, an attempt is made to develop Quality Control Charts for monitoring the process mean based on Double Ranked Set Sampling (DRSS) rather than the traditional Simple Random Sampling (SRS). Considering a normal population and several shift values, the performance of the Average Run Length (ARL) of these new charts was compared with the control charts based on Ranked Set Sampling (RSS) and SRS with the same number of observations. It is shown that the new charts do a better job of detecting changes in process mean compared with SRS and RSS.     

LOCAL KERNEL CANONICAL CORRELATION ANALYSIS WITH APPLICATION TO VIRTUAL DRUG SCREENING

Drug discovery is the process of identifying compounds which have potentially meaningful biological activity. A major challenge that arises is that the number of compounds to search over can be quite large, sometimes numbering in the millions, making experimental testing intractable. For this reason computational methods are employed to filter out those compounds which do not exhibit strong biological activity. This filtering step, also called virtual screening reduces the search space, allowing for the remaining compounds to be experimentally tested.In this paper we propose several novel approaches to the problem of virtual screening based on Canonical Correlation Analysis (CCA) and on a kernel-based extension. Spectral learning ideas motivate our proposed new method called Indefinite Kernel CCA (IKCCA). We show the strong performance of this approach both for a toy problem as well as using real world data with dramatic improvements in predictive accuracy of virtual screening over an existing methodology.     

Why is Six Sigma so successful?

There can be little doubt that Motorola, General Electric, Black and Decker, Allied Signal (now Honeywell), ABB and Bombardier, have achieved impressive business performance in recent years. Their annual reports document this success. Furthermore, in several cases, the Annual Report clearly attributes this success to having followed a Six Sigma strategy. Not surprisingly, many other companies wish to learn what Six Sigma can do for them, and their first question is 'What exactly is Six Sigma?'. Unfortunately it is rather difficult, if not impossible, to define Six Sigma in one or two sentences. This paper identifies the essential elements of Six Sigma. Some are obvious, such as the extensive use of statistical techniques by employees known as Blackbelts. However, other more subtle, but very important, features of Six Sigma are concealed within the business culture of these successful companies. It is clear to those who have participated in this success, that any company embarking on Six Sigma will not succeed if it focuses on statistics whilst failing to develop a supporting culture.