Optimal designs for multivariate logistic mixed models with longitudinal data

This paper considers the optimal design problem for multivariate mixed-effects logistic models with longitudinal data. A decomposition method of the binary outcome and the penalized quasi-likelihood are used to obtain the information matrix. The D-optimality criterion based on the approximate information matrix is minimized under different cost constraints. The results show that the autocorrelation coefficient plays a significant role in the design. To overcome the dependence of the D-optimal designs on the unknown fixed-effects parameters, the Bayesian D-optimality criterion is proposed. The relative efficiencies of designs reveal that both the cost ratio and autocorrelation coefficient play an important role in the optimal designs.     

Welfare analysis of a tax reform for Germany: a comparison of the unitary and collective models of household labour supply

We compare results of a tax reform analysis obtained with the collective and unitary models of household behaviour. We simulate real world micro-data by means of a collective approach, using a compound procedure of estimation and calibration based on the 1998 wave of the German socio-economic panel. We estimate a unitary model on this ‘collective’ data set. Investigating a move from joint to individual taxation on the basis of both models, we obtain important discrepancies between predicted adjustments to labour supply and distortions in the welfare analysis of the reform on the basis of unitary estimates.      

Fractional replication in simulation studies

It is shown how to use fractional replication in simulation studies. Examples are given. Considerable savings in number of runs required can be achieved through the use of fractional replication ideas.     

Use of balanced bipartite weighing designs as chemical balance designs

This paper deals with the use of balanced bipartite weighing designs as chemical balance designs when there Is a restriction on the number of objects that can be placed on either pan..The variance of each estimated weight and the covarlance of each pair of estimated weights are worked out.The use of additional weighing when the design matrix is singular is discussed.     

The Effects of E-journal Management Tools and Services on Serials Cataloging

Abstract

E-journal management tools and services such as MARC record services, A-to-Z lists, and link resolvers are changing e-journal cataloging. This column explores these changes in the academic environment through interviews with ten librarians representing eight universities. Three areas of change in serials cataloging are explored: (1) changes to the MARC record, including how libraries are adding/creating MARC records for their catalogs, the number and type of MARC records being created and linking within MARC bibliographic and holdings records; (2) the manner in which serials catalogers are being informed of changes; and (3) the evolving role of the serials cataloger. Future trends and advice for evolving workflow practices conclude the discussion.     

D-Optimum Designs for Optimum Mixture in a Quadratic Log Contrast Model

Optimal designs for estimating the optimum mixing proportions in a quadratic mixture model was first investigated by Pal and Mandal (2006). In this article, similar investigation is carried out when mean response in a mixture experiment is described by a quadratic log contrast model. It is found that in a symmetric subspace of the finite dimensional simplex, there exists a D-optimal design that puts weights at the centroid of the sub-space and the vertices of the experimental domain. The optimality is checked by numerical computation using Equivalence Theorem.     

The conditional maximum of Poisson random variables

The conditional maxima of independent Poisson random variables are studied. A triangular array of row-wise independent Poisson random variables is considered. If condition is given for the row-wise sums, then the limiting distribution of the row-wise maxima is concentrated onto two points. The result is in accordance with the classical result of Anderson. The case of general power series distributions is also covered. The model studied in Theorems 2.1 and 2.2 is an analogue of the generalized allocation scheme. It can be considered as a non homogeneous generalized scheme of allocations of at most n balls into N boxes. Then the maximal value of the contents of the boxes is studied.     

Lone mothers' time allocations: choices and satisfactions

This paper uses the 2006 Australian Time Use Survey to examine the allocation of time to personal care, employment‐related activities, home duties, leisure and child care of lone mothers, in comparison to the time allocations of single women, women in childless couples and partnered mothers. Both primary and secondary time allocations are considered. The satisfactions that women report concerning their current time allocations are also analysed. The time use and satisfaction data are described using both tabulations and multiple regression methods. Lone mothers are shown to have similar time allocations as the other types of households, even though they have different financial and time resources. This raises the concern that lone mothers' desire or need to maintain such time allocations may lead to task overload. Consistent with this, lone mothers are found to be less satisfied with the way they allocate their time than single women and partnered mothers. The tensions associated with time use among lone mothers discussed in the literature are real, and important.     

Locally and maximin optimal designs for multi-factor nonlinear models

This paper considers the search for locally and maximin optimal designs for multi-factor nonlinear models from optimal designs for sub-models of a lower dimension. In particular, sufficient conditions are given so that maximin D-optimal designs for additive multi-factor nonlinear models can be built from maximin D-optimal designs for their sub-models with a single factor. Some examples of application are models involving exponential decay in several variables.