磋商·交流·分享·对话--中加统计政策会议扫描

享誉天下的苏州是一座既古老而又充满活力的城市；建设中的苏州工业园区，更是我国改革开放政策所催生的全新发展模式。五月的苏州，春风拂面，细雨绵绵。中加统计政策会议之所以选择在苏州召开，正如国家统计局局长朱之鑫所言，不但合适，而且更有其特殊的意义。因为把现代统计理论引入我国的先行者，著名统计学家——金国宝先生就诞生于苏州。无庸多言，我们的前辈也非常愿意看到一个现代高效率的国家统计体系早日在中国建立。 中加统计政策会议是根据中国国家统计局和加拿大统计局统计信息管理合作项目安排的。加方出席会议的除统计局…     

Purposes, methods, philosophies

Peter Armitage has enjoyed a long and distinguished career in biostatistics, and has also given considerable thought to the way in which statistics is taught to non-mathematicians, perhaps because, he says jokingly, he always found maths a bit difficult himself. Now in retirement, he is still communicating statistical ideas in his rôle as Editor of the Encyclopedia of Biostatistics .     

Sample surveys versus experiments,controlled observations,censuses, registers,and local studies

The relative merits and drawbacks of data obtained from the following sources are compared: sample surveys, experimental projects, controlled observations, censuses, registers, and local studies. The importance of representation as the criterion for comparing the value of the data obtained by the various methods is stressed.     

“Who,What, Where,and Why”

The North Carolina Serials Conference was very fortunate to have secured Rachel Frick for its keynote speaker for 2013. The conference was a homecoming for Frick, who is a graduate of the University of North Carolina MSLS program and is currently the Director of the Digital Library Federation Program for the Council on Library and Information Resources (CLIR), a think tank and research organization located in Washington, D.C. The Digital Library Federation (DLF) has been in existence since 1995, its target audiences being digital library practitioners and other interested parties who are on the front-lines of teaching and learning in this specialty. In her address entitled “Who, What, Where, Why, and How,” Frick discussed some of the major initiatives and issues currently occurring within and around librarianship, exploring the effect that these large scale initiatives can, and should, have at the local level. She can be reached at her Twitter feed, @rlfrick.     

Mixtures,embedding, and ancillarity

Ancillary statistics, proposed by Fisher (1925), can be constructed by forming a mixture model (Birnbaum 1962) or can be extracted or derived from a transformation-parameter model (Peisakoff 1951, Fraser 1961) or from the corresponding error-based structural model (Fraser 1968, 1979); these latter models involve an implicit mixture structure. Compound models with ancillaries can also be formed by a cross embedding, discussed from a technical viewpoint in this paper. Of the 25 examples in Buehler (1982), 22 are mixtures or implicit mixtures and 3 correspond to cross embedding. The cross embedding examples exemplify the nonuniqueness difficulties with ancillaries. This paper discusses a simple and two generalized versions of cross embedding but makes no general valuations of these for statistical inference; their role within inference is discussed in Evans, Fraser, and Monette (1984, 1985).     

Censoring,conditionally, and likelihood

The censoring principle is shown to imply a principle similar to the likelihood principle. Further, it is demonstrated that the censoring principle and a weak form of the conditionality principle jointly imply the likelihood principle.     

Some Remarks on Failure-times,Surrogate Markers,Degradation, Wear,and the Quality of Life

Suppose that data are available on failure-times and on a time-evolving process on each individual, called in some contexts wear or degradation. Four rather different types of relation between such a process and failure are described and brief comments on appropriate analysis sketched.     

Frequentist,Bayes, or Other?

ABSTRACT

Both philosophically and in practice, statistics is dominated by frequentist and Bayesian thinking. Under those paradigms, our courses and textbooks talk about the accuracy with which true model parameters are estimated or the posterior probability that they lie in a given set. In nonparametric problems, they talk about convergence to the true function (density, regression, etc.) or the probability that the true function lies in a given set. But the usual paradigms' focus on learning the true model and parameters can distract the analyst from another important task: discovering whether there are many sets of models and parameters that describe the data reasonably well. When we discover many good models we can see in what ways they agree. Points of agreement give us more confidence in our inferences, but points of disagreement give us less. Further, the usual paradigms’ focus seduces us into judging and adopting procedures according to how well they learn the true values. An alternative is to judge models and parameter values, not procedures, and judge them by how well they describe data, not how close they come to the truth. The latter is especially appealing in problems without a true model.     

跨方言区流动、自选择与劳动力收入

本文基于2012和2014年中国劳动力动态调查（CLDS）数据,采用内生转换回归模型考察劳动力跨方言区流动对收入的影响。实证结果表明,与在同一方言区流动的个体相比,跨方言区流动收入要高31.9%;对于跨方言区流动的劳动力而言,跨方言区流动对收入的平均处理效应为30.5%,如果在同一方言区流动的劳动力选择跨方言区流动,其收入反而会减少3.9%,说明不同个体在流入地的选择上是基于其比较优势做出的决策。进一步,本文还发现跨方言区流动的劳动力无论选择在同一方言区流动还是跨方言区流动,均能获得较高的收入,在流动决策上具有绝对优势。在考虑了测量误差和极端值以及排除其他干扰因素后,上述结论依然稳健。     

Marginal homogeneity,symmetry, and independence

A contingency table of the mc form provides a convenient summary of data when c individuals in a matched set9 each belonging to a different one of c classifications, are identified as belonging to one of m categories, A study in which matched sets (c=3) of 1 case, 1 hospital control, and 1 neighborhood control are classified into one of m=4 occupational categories would be an example, Independence in the cxm tables for each of the matched sets implies symmetry in the summary mc table with consequent marginal homogeneity. Adaptation of the Mantel-Haenszel procedure for testing independence to the case of many cxm tables so as to yield a chi square with (cl)(ml) degrees of freedom (DF) provides a test of marginal homogeneity in the summary mc table. This can be viewed as a test of symmetry directed against alternatives which would make for marginal inhomogeneity and can differ     

To Aggregate,Pool, or Neither

It is well known that, even if all forecasters are rational, unbiasedness tests using consensus forecasts are inconsistent because forecasters have private information. However, if all forecasters face a common realization, pooled estimators are also inconsistent. In contrast, we show that when predictions and realizations are integrated and cointegrated, microhomogeneity ensures that consensus and pooled estimators are consistent. Therefore, contrary to claims in the literature, in the absence of microhomogeneity, pooling is not a solution to the aggregation problem. We reject microhomogeneity for a number of forecasts from the Survey of Professional Forecasters. Therefore, for these variables unbiasedness can only be tested at the individual level.