Showing papers by "Pranab Kumar Sen published in 2000"

Effect of dichotomizinlg a continuous variable on the model structure in multiple linear regression models

Abstract: This mansscript studies analytically the consequences of changing the scale of measurement of a continuous independent variable in a multiple linear regression setting. Assuming the continuous outcome variable, a continuous exposure variable, and a continuous control variable follow a trivariate Gaussian distribution, we examine the effect upon the structure of the modei of dichotomizing the continuous control variable. It is shown that, after dichotomizaiion, the condirionai expected vaiiie of the response is a quotient of two non-hear functions and hence is no longer linear in the exposure variable. Thus, when an underlying continuous independent variable is dichotomized in multiple linear regression, and one fits a linear model using the dichotomous variable, this model's linear structure is misspecified. The estimates obtained from this model are incorrect and potentially misleading.

On Stochastic Ordering and a General Class of Poverty Indexes

Abstract: Although measures of diversity and inequality have been extensively proposed in socio-economic and health perspectives, violation of a subtle monotonicity criterion (under stochastic ordering) diminishes their rationality and utility in the context of poverty and other ecomomic indexes. A modification is proposed here to develop certain stochastic ordering monotonicity preserving diversity measures that overcome this drawback. Such measures are shown to be invariant under increasing transformation, and thereby appropriate for (partially) ordered categorical response data models.AMS{2000) Subject Classification: 62H17, 62-07.

Sample size determination of steel's nonparametric many-one test

Abstract: We derive sample size formulas for the many-one test of Steel (1959) when the all-pairs power is preassigned. In this large sample approach we replace, similar to Noether (1987), the unknown variances and also the unknown correlation coefficients in the power expressions by their known values under the null hypotheses. We then obtain least favorable configurations for one-and two-sided comparisons. The reliability of our formulas is examined in computer simulations for different alternatives with various distributions.

Bioenvironmental and public health statistics

Abstract: One aspect of statistical methodology that merits special appraisal is the extent of the appropriateness of standard tools in non-standard applications. This volume adopts an unorthodox approach to ensure relevant biostatistical methods are considered in the context of fruitful applications.

1 Bioenvironment and public health: Statistical perspectives

Abstract: At this concluding phase of the present century (and the millennium too), the limelight of advancement of knowledge has been stolen primarily by the spectacular advent of information technology (IT). Modern electronics and computers have invaded each and every corne'" of the globe, and touched all walks of life, science and technolgy, and society. And yet, ma jor challanges have errupted from almost every sphere of life on earth, most noticably, in the sectors of bioenvironment and public health. Our bioenvironment constitutes the totality of entities of all socio-economic, cultutal-political, clinical and biomedical, ecological and environmental, as well as environmental health and hazard perspectives that pertain to the existence and propagation of all biosystems on earth, including, of course, the human beings. Public awareness of such bioenvironmental impacts on human health and quality of life (QOL) has been an important ingredient in the constitution and development of the public health science and practice field, and together, these two broad disciplines form a broader interdisciplinary field that deserves our utmost attention from scientific as well as humanitarian perspectives. No longer, the field of public health is specifically confined to the disease prevention and health promotion aspects of human beings, and bioenvironment has emerged as one of the most influencing factors in public health, and only taken together, they convey a much more comprehensive picture. The eco-environment of our mother planet is indeed endangered with life-threatening phenomena, not only due to escalating ecological imbalances and environmental disasters, but also due to mounting social, economic, religious, political and cultural disruptions; relatively new or hitherto unknown forms of catastrophic diseases or disorders (such as the HIV) have drastically altered the QOL of all biosystems on earth, and bioenvironmental toxicity of various kinds has attained an elevated level that poses a serious threat to the

Nondifferentiable errors in beta-compliance integrated logistic models: numerical results

Abstract: In dose-response models, there are cases where only a portion of the administered dose may have an effect. This results in a stochastic compliance of the administered dose. In a previous paper (Chen-Mok and Sen, 1999), we developed suitable adjustments for compliance in the logistic model under the assumption of nondifferential measurement error. These compliance-adjusted models were categorized into three types: (i) Low (or near zero) dose levels, (ii) moderate dose levels, and (iii) high dose levels. In this paper, we analyze a set of data on the atomic bomb survivors of Japan to illustrate the use of the proposed methods. In addition, we examine the performance of these methods under different conditions based on a simulation study. Among all three cases, the adjustments proposed for the moderate dose case do not seem to work adequately. Both bias and variance are larger when using the adjusted model in comparison with the unadjusted model. The adjustments for the low dose case seem to work in reducing...