Hierarchical random effect models for coastal erosion of cliffs in the Holderness coast

Prediction of possible cliff erosion at some future date is fundamental to coastal planning and shoreline management, for example to avoid development in vulnerable areas. Historically, to predict cliff recession rates deterministic methods were used. More recently, recession predictions have been expressed in probabilistic terms. However, to date, only simplistic models have been developed. We consider the cliff erosion along the Holderness Coast. Since 1951 a monitoring program has been started in 118 stations along the coast, providing an invaluable, but often missing, source of information. We build hierarchical random effect models, taking account of the known dynamics of the process and including the missing information.     

Estimating the movement among staging areas of the barnacle goose ( Branta leucopsis )

Barnacle geese ( Branta leucopsis ) make annual migrations between breeding colonies in northern Europe and Eurasia to wintering grounds in Holland. During the migration, they sojourn for several weeks in five areas on the northern coast of Germany. Observers traverse these areas during the course of studying the flocks. Previous belief was that there was little exchange of birds among the five areas; however, some banded birds were observed in more than one area indicating that some movement takes place. In this presentation, we estimate the movement rates among the areas using open- and closed-population models.     

Estimating the movement among staging areas of the barnacle goose ( Branta leucopsis )

Barnacle geese ( Branta leucopsis ) make annual migrations between breeding colonies in northern Europe and Eurasia to wintering grounds in Holland. During the migration, they sojourn for several weeks in five areas on the northern coast of Germany. Observers traverse these areas during the course of studying the flocks. Previous belief was that there was little exchange of birds among the five areas; however, some banded birds were observed in more than one area indicating that some movement takes place. In this presentation, we estimate the movement rates among the areas using open- and closed-population models.     

Bayesian inference and data cloning in the calibration of population projection matrices

Discrete time models are used in Ecology for describing the dynamics of an age-structured population. They can be introduced from a deterministic or from a stochastic viewpoint. We analyze a stochastic model for the case in which the dynamics of the population is described by means of a projection matrix. In this statistical model, fertility rates and survival rates are unknown parameters which are estimated by using a Bayesian approach and also data cloning, which is a simulation-based method especially useful with complex hierarchical models.

Both methodologies are applied to real data from the population of Steller sea lions located in the Alaska coast since 1978–2004. The estimates obtained from these methods show a good behavior when they are compared to the nonmissing actual values.     

Characterizing persistent disturbing behavior using longitudinal and multivariate techniques

Persistent disturbing behavior (PDB) refers to a chronic condition in therapy-resistant psychiatric patients. Since these patients are highly unstable and difficult to maintain in their natural living environment and even in hospital wards, it is important to properly characterize this group. Previous studies in the Belgian province of Limburg indicated that the size of this group was larger than anticipated. Here, using a score calculated from longitudinal psychiatric registration data in 611 patients, we characterize the difference between PDB patients and a set of control patients. These differences are studied both at a given point in time, using discriminant analysis, as well as in terms of the evolution of the score over time, using longitudinal data analysis methods. Further, using clustering techniques, the group of PDB patients is split into two subgroups, characterized in terms of a number of ordinal scores. Such findings are useful from a scientific as well as from an organizational point of view.     

集聚经济与中国城市体系优化──跨省迁移视角的研究

改革开放后实施的中小城市偏向型城市化政策导致了扁平化的城市体系,使得经济增长无法充分利用规模经济效应提高生产效率。利用全国人口普查数据研究发现,中国的城市体系在1990-2000年间变得更加扁平化。但随着城市化政策的调整,2000-2010年间,大城市的增长更具优势,扁平化的城市体系逐渐得到优化。使用跨省迁移人口作为城市经济集聚能力的衡量指标,研究结果显示,沿海100万人口以上的大城市提供的经济集聚力是中国城市体系优化的原因。依据城市体系演进的一般规律和中国城市化发展的现状,预测中国大规模城市仍将以较快速度增长,城市体系将进一步优化,而实现这一目标的关键是努力降低迁移成本。     

Higher female than male mortality in some countries of South Asia: a digest

A statistical study was made of sex ratios and mortality in Ceylon, Pakistan, and India. Contrary to general expectations, female mortality was higher than male mortality. A greater divergence in the sex ratio was found with increased age. Female emigration and abnormal sex ratios at birth are discounted as explanations of the phenomenon. It is considered that underenumeration of females in the census and higher female mortality rates, especially during the reproductive years and childhood, are responsible for the inverted sex ratio. The projected sex ratios for these countries are not reflected in the model life tables derived from international experience.     

Model-based estimation of individual fitness

Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes ( Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).     

Updating small area population estimates in England and Wales

"Population estimates have important implications for resource allocation within government and commerce, and are often assumed to be without error. Currently, central government provides annual population estimates for all the local and health authority districts in Britain, but estimates are needed for smaller areas, typically for electoral wards and postal sectors. Small area estimates are provided by some local authorities and commercial organizations, using different methods; the accuracy of these estimates is modelled here within a multilevel framework. Certain characteristics of the small area and of the method of estimation are included as explanatory variables. Results show that the method of estimation used is of great importance."     

Creating a reference to a complex emergency situation using time series methods: war in Guinea-Bissau 1998-1999

Impacts of complex emergencies or relief interventions have often been evaluated by absolute mortality compared to international standardized mortality rates. A better evaluation would be to compare with local baseline mortality of the affected populations. A projection of population-based survival data into time of emergency or intervention based on information from before the emergency may create a local baseline reference. We find a log-transformed Gaussian time series model where standard errors of the estimated rates are included in the variance to have the best forecasting capacity. However, if time-at-risk during the forecasted period is known then forecasting might be done using a Poisson time series model with overdispersion. Whatever, the standard error of the estimated rates must be included in the variance of the model either in an additive form in a Gaussian model or in a multiplicative form by overdispersion in a Poisson model. Data on which the forecasting is based must be modelled carefully concerning not only calendar-time trends but also periods with excessive frequency of events (epidemics) and seasonal variations to eliminate residual autocorrelation and to make a proper reference for comparison, reflecting changes over time during the emergency. Hence, when modelled properly it is possible to predict a reference to an emergency-affected population based on local conditions. We predicted childhood mortality during the war in Guinea-Bissau 1998-1999. We found an increased mortality in the first half-year of the war and a mortality corresponding to the expected one in the last half-year of the war.     

The demography of the decline in the British willow warbler population

Since 1989, there has been a major and unprecedented decline in the breeding population of willow warblers ( Phylloscopus trochilus ) in southern Britain. Between 1986 and 1993 the numbers of willow warbler territories counted on monitoring plots declined by 47% in southern Britain, compared to a decline of 7% in northern Britain. Breeding densities of willow warblers are generally higher in the north and west of Britain, than in the south. Data from nest record cards provided evidence of only minor regional differences in breeding performance with a small but significant increase in the loss rate of nests during the nestling stage in 1989-1992 in southern Britain, compared with 1974-1988. Mark-recapture data collected at 18 constant effort sites and from one intensive study were used to estimate apparent survival rates of adults during the period 1987-1993. Program SURGE4 was used to test for differences in survival rates and recapture probabilities between years, sexes, sites and regions. Recapture probabilities differed between sites and between the sexes but not between years. Survival rates differed significantly between years (in southern Britain) but not between sexes or sites. In southern Britain, adult survival declined from 45% during 1987-1988 to 24% during 1991-1992, while in northern Britain there was no evidence that survival changed during the same period. Although the pattern of annual variation in survival differed between northern and southern Britain, this was due mainly to a much lower survival rate in southern Britain during 1991-1992. Declining survival rates of adult willow warblers have probably been a major cause of the observed population decline.     

Comparison of approaches for estimating the probability of coastal flooding

Coastal flooding is typically caused by combinations of extreme water-levels and large waves. Two extreme value methods, one univariate and the other multivariate, have been used for estimating the probability of coastal flooding at an existing flood defence structure and for aiding the design of a new structure. The properties of these two methods are compared in terms of extrapolation, sophistication and use of information for a range of extremal dependence structures. We find that, when applied to the assessment of the safety offered by an existing Dutch dike, the multivariate approach provides the more useful and accurate design information and has the substantial benefits of consistency and reduced statistical analysis when applied to several sites along a Dutch coastline.     

A case study in identifying targeted patients population in major depressive disorder by enhanced enrichment design

Despite advances in clinical trial design, failure rates near 80% in phase 2 and 50% in phase 3 have recently been reported. The challenges to successful drug development are particularly acute in central nervous system trials such as for pain, schizophrenia, mania, and depression because high‐placebo response rates lessen assay sensitivity, diminish estimated treatment effect sizes, and thereby decrease statistical power. This paper addresses the importance of rigorous patient selection in major depressive disorder trials through an enhanced enrichment paradigm. This approach led to a redefinition of an ongoing, blinded phase 3 trial algorithm for patient inclusion (1) to eliminate further randomization of transient placebo responders and (2) to exclude previously randomized transient responders from the primary analysis of the double blind phase of the trial. It is illustrated for a case study for the comparison between brexpiprazole + antidepressant therapy and placebo + antidepressant therapy. Analysis of the primary endpoint showed that efficacy of brexpiprazole versus placebo could not be established statistically if the original algorithm for identification of placebo responders was used, but the enhanced enrichment approach did statistically demonstrate efficacy. Additionally, the enhanced enrichment approach identified a target population with a clinically meaningful treatment effect. Through its successful identification of a target population, the innovative enhanced enrichment approach enabled the demonstration of a positive treatment effect in a very challenging area of depression research.     

城镇贫困的特征演变

本文利用中国家庭收入调查数据研究了1988-2013年间我国城镇居民的贫困问题。以利用“马丁法”计算的各省历年贫困线作为贫困识别标准,发现25年间城镇地区的贫困率下降明显,尤其暂时性贫困和持久性贫困的贫困率已经很低,贫困人口以选择性贫困为主,即消费不足成为我国城镇人口贫困的主要特征。家庭人口多、有未成年子女会有更大概率陷入贫困,而教育和稳定的就业则可以有效缓解贫困。当前我国城镇地区的贫困人口认定和救助主要以收入为标准,本文认为应充分重视贫困人口消费不足的问题,拓展专项救助的范围,同时增大对教育、卫生、住房等基本民生保障的投入,减少低收入群体的过度储蓄,并特别关注贫困青少年的精神和物质消费需求。     

Latent transition models with latent class predictors: attention deficit hyperactivity disorder subtypes and high school marijuana use

Summary.  Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder which is most often diagnosed in childhood with symptoms often persisting into adulthood. Elevated rates of substance use disorders have been evidenced among those with ADHD, but recent research focusing on the relationship between subtypes of ADHD and specific drugs is inconsistent. We propose a latent transition model (LTM) to guide our understanding of how drug use progresses, in particular marijuana use, while accounting for the measurement error that is often found in self-reported substance use data. We extend the LTM to include a latent class predictor to represent empirically derived ADHD subtypes that do not rely on meeting specific diagnostic criteria. We begin by fitting two separate latent class analysis (LCA) models by using second-order estimating equations: a longitudinal LCA model to define stages of marijuana use, and a cross-sectional LCA model to define ADHD subtypes. The LTM model parameters describing the probability of transitioning between the LCA-defined stages of marijuana use and the influence of the LCA-defined ADHD subtypes on these transition rates are then estimated by using a set of first-order estimating equations given the LCA parameter estimates. A robust estimate of the LTM parameter variance that accounts for the variation due to the estimation of the two sets of LCA parameters is proposed. Solving three sets of estimating equations enables us to determine the underlying latent class structures independently of the model for the transition rates and simplifying assumptions about the correlation structure at each stage reduces the computational complexity.     

Type I and Type II error rates in the last observation carried forward method under informative dropout

Dropout is a persistent problem for a longitudinal study. We exhibit the shortcomings of the last observation carried forward method. It produces biased estimates of change in an outcome from baseline to study endpoint under informative dropout. We developed a theoretical quantification of the effect of such bias on type I and type II error rates. We present results for a setup where a subject either completes the study or drops out during one particular interval, and also under the setup in which subjects could drop out at any time during the study. The type I error rate steadily increases when time to dropout decreases or the common sample size increases. The inflation in type I error rate can be substantially high when reasons for dropout in the two groups differ; when there is a large difference in dropout rates between the control and treatment groups and when the common sample size is large; even when dropout subjects have one or two fewer observations than the completers. Similar results are also observed for type II error rates. A study can have very low power when early recovered patients in the treatment group and worsening patients in the control group drop out even near the end of the study.     

A spatial random-effects model for interzone flows: commuting in Northern Ireland

Government policy on employment, transport, and housing often depends on reliable information about spatial variation in commuting flows across a region. Simple commuting rates summarising inter-area flows may not provide a full perspective on the underlying levels of commuting attractivity of different areas (as destinations), or the varying dependence of different areas (as origins) on outside employment. Areas also vary in the degree of commuting self-containment, as expressed in intra-area flows. This paper uses a spatial random-effects model to develop indices of attractivity, extra-dependence, and self-containment using a latent factor method. The methodology allows consideration of the degree to which different explanatory influences (e.g. socioeconomic structure, characteristics of road networks, employment density) affect these aspects of commuting. The particular application is to commuting flows in Northern Ireland, using 139 zones that aggregate smaller areas (wards), so avoiding undue sparsity in the flow matrix. The analysis involves Bayesian estimation, with the outputs comprising full densities for extra-dependence, and attractivity scores and scores for intra-area containment of zones. Spatial patterning in these aspects of commuting is allowed for in the model used. One key pattern is the difference in latent effect estimates for urban (in particular, Belfast) and rural areas reflecting variable job opportunities in these areas.     

Calculating the total vote where the district magnitude is greater than one: A test of some algorithms using British local election data

Electoral analysis using aggregate data relies on the availability of accurate voting statistics. One vital piece of information, often missing from official electoral returns, particularly British local government elections, is the total number of valid ballot papers. This figure is essential for the calculation of electoral turnout. When voters have a single vote and official information about the number of ballot papers issued is missing, a figure for the total vote can still be derived. However, local elections in Britain frequently use a system of multiple-member wards, where voters have as many votes as there are seats to be filled. In such cases, calculating the total vote and, hence, the turnout does present a real problem. It cannot be assumed that all voters will use their full quota of votes or that voters will cast a ballot in favour of a single party. This paper develops and tests diff erent algorithms for calculating the total vote in such circumstances. We conclude that the accuracy of an algorithm is closely related to the structure of party competition. The findings of this paper have a number of important implications. First, the difficulties in calculating the turnout in multiple-member wards are identified. This will inform the debate about public participation in the local electoral process. Second, the method for deriving a figure for the total vote has an important bearing on a number of other statistics widely employed in electoral analysis.