Practical bayesian approaches to the analystcs of a 2×2 contingency table with incompletely categorized data

To assess the efficacy of a treatment, patients are administered a pre-test, the treatment, and a post-test (identical to the pre-test). These patients are then categorized according to their outcomes observed on both tests,e.g., (S,S), (S,F), etc. Also, we observe "incomplete" information on the pre-tests' outcomes for some patients and the results of only the post-test being known for thers, A Bayesian framework is fit to the problem and Bayes factors, posterior odds ratios, and utility functions are given to evaluate th e treatment, A method of assessing the prior distribution is specified and a numerical example is worked.     

Multivariate analysis with a stationary time series covariance structure

When a covariance matrix has a pattern associated with a stationary time series on the errors, it is shown how certain hypothesis testing problems In multivariate analysis can be transformed into a product of two similar multivariate problems that each involve unpatterned covariance matrices.     

The best subset of parameters in min-max linear regression

These Fortran-77 subroutines provide building blocks for Generalized Cross-Validation (GCV) (Craven and Wahba, 1979) calculations in data analysis and data smoothing including ridge regression (Golub, Heath, and Wahba, 1979), thin plate smoothing splines (Wahba and Wendelberger, 1980), deconvolution (Wahba, 1982d), smoothing of generalized linear models (O'sullivan, Yandell and Raynor 1986, Green 1984 and Green and Yandell 1985), and ill-posed problems (Nychka et al., 1984, O'sullivan and Wahba, 1985). We present some of the types of problems for which GCV is a useful method of choosing a smoothing or regularization parameter and we describe the structure of the subroutines.Ridge Regression: A familiar example of a smoothing parameter is the ridge parameter X in the ridge regression problem which we write.     

Robust estimation methods for exponential data: a monte-carlo comparison

We compare the performance of seven robust estimators for the parameter of an exponential distribution. These include the debiased median and two optimally-weighted one-sided trimmed means. We also introduce four new estimators: the Transform, Bayes, Scaled and Bicube estimators. We make the Monte Carlo comparisons for three sample sizes and six situations. We evaluate the comparisons in terms of a new performance measure, Mean Absolute Differential Error (MADE), and a premium/protection interpretation of MADE. We organize the comparisons to enhance statistical power by making maximal use of common random deviates. The Transform estimator provides the best performance as judged by MADE. The singly-trimmed mean and Transform method define the efficient frontier of premium/protection.     

Testing Variability in the Two-Sample Case

A number of robust methods for testing variability have been reported in previous literature. An examination of these procedures for a wide variety of populations confirms their general robustness. Shoemaker's improvement of the F test extends that test use to a realistic variety of population shapes. However, a combination of the Brown–Forsythe and O'Brien methods based on testing kurtosis is shown to be conservative for a wide range of sample sizes and population distributions. The composite test is also shown to be more powerful in most conditions than other conservative procedures.     

Reflections of an ordinary life

Philip Anderson (not his real name) was one of thirty people who talked to Wendy Booth and Tim Booth as part of their recently published study Growing Up with Parents who have Learning Difficulties (London: Routledge, 1998). Philip's stoy illustrates many of the themes common to the experience of this group: resilience in the face of risk; the importance of family, especially grandma; social exclusion; the effects of hardship; and the enduring nature of parent-child bonds.     

Internal Migration and Urban Change in Poland

The paper investigates population change and migration over the period 1984–1994 for communes. There are important conclusions emerging from this study. The first is that we are watching now a profound change of population redistribution patterns in Poland. We observed that direct upwards hierarchical mobility has been markedly modified. The first modification is the substantial reduction of migration from rural to urban locations. There were important changes in the role of cities and towns. Largest cities, massive gainers of the seventies and eighties, have tended to lose population in the mid-nineties. It is likely that they lose population mainly to the neighbouring communes. We believe that a suburbanization process has been put into motion. Medium to large sized towns and cities, in the range between 50,000 and 500,000 as well as small, but not the smallest, towns attract substantial parts of the migration pool.     

The Elementary Forms of Place and Their Transformations: A Durkheimian Model

Due to the fragmentary nature of research findings and conceptual models, the Durkheimian legacy remains undervalued in contemporary spatial theory. The paper addresses this neglect by proposing a unified Durkheimian model of place which can be applied to case history and comparative analyses. It draws together the fragmented insights of Durkheimian theory to characterize four elementary forms of place: sacred, profane, liminal and mundane. These place/space identities are maintained and transformed through rituals and narratives which depend upon contingent human actions for their sustenance. The paper concludes with an extended case study which deploys the model to explain the changing meanings of the site of the Bastille (Paris, France) over the past two centuries.     

Using Mand Training to Establish an Echoic Repertoire in Young Children with Autism

The Analysis of Verbal Behavior - This research describes a method that initially establishes a mand repertoire as the first component in producing echoic and tact repertoires in young children...     

Identification of Standard Auction Models

This paper presents new identification results for models of first–price, second–price, ascending (English), and descending (Dutch) auctions. We consider a general specification of the latent demand and information structure, nesting both private values and common values models, and allowing correlated types as well as ex ante asymmetry. We address identification of a series of nested models and derive testable restrictions enabling discrimination between models on the basis of observed data. The simplest model—symmetric independent private values—is nonparametrically identified even if only the transaction price from each auction is observed. For richer models, identification and testable restrictions may be obtained when additional information of one or more of the following types is available: (i) the identity of the winning bidder or other bidders; (ii) one or more bids in addition to the transaction price; (iii) exogenous variation in the number of bidders; (iv) bidder–specific covariates. While many private values (PV) models are nonparametrically identified and testable with commonly available data, identification of common values (CV) models requires stringent assumptions. Nonetheless, the PV model can be tested against the CV alternative, even when neither model is identified.