Addressing issues of face validity in the application of a clinical guideline

In 1995, a statewide project to improve the practice of electroconvulsive therapy (ECT) in the Medicare population was started in Louisiana. A retrospective baseline study found high concurrent utilization of lithium and benzodiazepines, medications considered detrimental to ECT by the second American Psychiatric Association Task Force on ECT. Resistance to a clinical guideline because of lack of face validity by clinicians was used as an opportunity to involve clinicians in using data to evaluate their clinical practices. Results of the first two quarters of the project demonstrated that the strategy was successful.     

A note on abridged life tables for Ceylon, 1900–1947

Life Tables have been calculated by Kuczynski's method for males and females in Ceylon for 1910–12, 1920–2 and 1945–7. The method is described, and the main results are presented.     

Structural versus nonstructural form of social capital: impact of ethnicity along caste and religious dimensions in Indian context

Despite much research work on the effect of social capital or the production of social capital along ethno-linguistic or racial dimensions, there is hardly any study in this line along the much fragmented character of Indian ethnicity. This article studies the impact of ethnicity along caste and religious dimensions on the growth of social capital in the Indian context. A simple theoretical model indicates that individual ethnicity formed out of individuals' separate pairwise connections with people, who are either of the same ethnic dimension or of different ethnic dimensions, is the only factor affecting endogenous social capital growth. Empirical results suggest that all forms of individual social capital are higher for people who are of the same caste or religion. It also shows that individuals' ethnicity with the same caste or religion is the only factor influencing high performance on the productivity of aggregate social capital in general and nonstructural form of social capital in particular.     

Robust tests for equality of two population means under the normal model

A robust procedure is developed for testing the equality of means in the two sample normal model. This is based on the weighted likelihood estimators of Basu et al. (1993). When the normal model is true the tests proposed have the same asymptotic power as the two sample Student's t-statistic in the equal variance case. However, when the normality assumptions are only approximately true the proposed tests can be substantially more powerful than the classical tests. In a Monte Carlo study for the equal variance case under various outlier models the proposed test using Hellinger distance based weighted likelihood estimator compared favorably with the classical test as well as the robust test proposed by Tiku (1980).     

Controlling Bayes directional false discovery rate in random effects model

Starting with a decision theoretic formulation of simultaneous testing of null hypotheses against two-sided alternatives, a procedure controlling the Bayesian directional false discovery rate (BDFDR) is developed through controlling the posterior directional false discovery rate (PDFDR). This is an alternative to Lewis and Thayer [2004. A loss function related to the FDR for random effects multiple comparison. J. Statist. Plann. Inference 125, 49–58.] with a better control of the BDFDR. Moreover, it is optimum in the sense of being the non-randomized part of the procedure maximizing the posterior expectation of the directional per-comparison power rate given the data, while controlling the PDFDR. A corresponding empirical Bayes method is proposed in the context of one-way random effects model. Simulation study shows that the proposed Bayes and empirical Bayes methods perform much better from a Bayesian perspective than the procedures available in the literature.     

A new estimator combining the ridge regression and the restricted least squares methods of estimation

It is well-known in the literature on multicollinearity that one of the major consequences of multicollinearity on the ordinary least squares estimator is that the estimator produces large sampling variances, which in turn might inappropriately lead to exclusion of otherwise significant coefficients from the model. To circumvent this problem, two accepted estimation procedures which are often suggested are the restricted least squares method and the ridge regression method. While the former leads to a reduction in the sampling variance of the estimator, the later ensures a smaller mean square error value for the estimator. In this paper we have proposed a new estimator which is based on a criterion that combines the ideas underlying these two estimators. The standard properties of this new estimator have been studied in the paper. It has also been shown that this estimator is superior to both the restricted least squares as well as the ordinary ridge regression estimators by the criterion of mean sauare error of the estimator of the regression coefficients when the restrictions are indeed correct. The conditions for superiority of this estimator over the other two have also been derived for the situation when the restrictions are not correct.     

Supersaturated designs with high searching probability

A supersaturated design is essentially a fractional factorial design whose number of experimental variables is greater than or equal to its number of experimental runs. Under the effect sparsity assumption, a supersaturated design can be very cost-effective. In this paper, our prime objective is to compare the existing two-level supersaturated designs for the noisy case through the probability of correct searching—a powerful criterion proposed by Shirakura et al. [1996. Searching probabilities for nonzeroeffects in search designs for the noisy case. Ann. Statist. 24, 2560–2568]. An algorithm is proposed to construct supersaturated designs with high probability of correct searching. Examples are given for illustration.     

On a method of identification of best subset model from full ar-model

An usual approach for selection of the best subset AR model of known maximal order is to use an appropriate information criterion, like AIC or SIC with an exhaustive selection of regressors and to choose the subset model that produces the optimum (minimum) value of AIC or SIC. This method is computationally intensive. Proposed is a method based on the use of singular value decomposition and QR with column pivoting factorization for extracting a reduced subset from the exhaustive candidate set of regressors and to use AIC or SIC on the reduced subset to obtain the best subset AR model. The result is substantially reduced domain of exhaustive search for the computation of the best subset AR model.     

Likelihood ratio type unit root tests for ar(1)models with nonconsecutive observations

For the nonconsecutively observed or missing data situation likelihood ratio type unit root tests in AR(1)models containing an intercept or both an intercept and a time trend are proposed and are shown to have the same limiting distributions as the likelihood ratio tests for the complete data case as tabulated by Dickey and Fuller(1981). Some simulation results on our tests in finite samples under A–B sampling schemes are also presented.     

Muslim women and the politics of (in)visibility in late colonial Bengal

The paper attempts to understand ways in which gender and racially defined communal ideologies worked simultaneously to produce Muslim women in colonial Bengal as invisible within nationalist historiography. It argues that the negative representations of Muslim women underpinned the construction of other identity categories in colonial Bengal, and highlights the participation of Hindu/Brahmo women writers in this process.