Contested Numbers: The failed negotiation of objective statistics in a methodological review of Kinsey et al.'s sex research.

From 1950 to 1952, statisticians W.G. Cochran, C.F. Mosteller, and J.W. Tukey reviewed A.C. Kinsey and colleagues' methodology. Neither the history-and-philosophy of science literature nor contemporary theories of interdisciplinarity seem to offer a conceptual model that fits this forced interaction, which was characterized by significant power asymmetries and disagreements on multiple levels. The statisticians initially attempted to exclude all non-technical matters from their evaluation, but their political and personal investments interfered with this agenda. In the face of McCarthy's witch hunts, negotiations with Kinsey and his funding institutions became integral to the review group's work. This paper analyzes the heavy burden of emotional and affective labor in this collaboration, the conflicts caused by competing visions of objectivity, and the uses of statistical knowledge to gain and sustain authority. Kinsey's refusal to adopt the recommended probability sample damaged his already precarious position even further and marked him as a biased researcher who put his personal agenda above methodological rigor. Kinsey's uncooperative demeanor can be explained by distrust resulting from numerous adverse reactions to his work and by fear of having his sexuality exposed. This case study illustrates that the very concept of valid numbers can become an arena for power struggles and that quantification alone does not guarantee productive exchanges across disciplines. It calls for a deeper conceptual analysis of the prerequisites for successful scientific collaborations.

Dr. Hossein Malekafzali: A Pioneer in Iran's Health Evolution and Development.

Dr Malekafzali, an elite biostatistics professor at Tehran University of Medical Sciences, in his more than 50 years of glorious service, has played a crucial role in creation of fundamental evolution in public health, reproductive health and development of applied research in Iran. He has left lasting activities in administrative positions such as health and research deputies, health minister consultant, director of health faculty and director of health research institutes. He published several books and articles on statistics, epidemiology and public health. This article is a review of his worthy and interesting activities in the country's health, research and education.

From Many to One to Many-the Search for Causes of Psychiatric Illness.

The search for the causes of medical and psychiatric disorders has gone through 3 historical phases. First, up until the mid-19th century, causes of illness were anecdotally recorded from individual cases, resulting in long and diverse lists for all disorders. Second, in the latter half of the 19th century, with the use of microbiological methods, single causes were found for many infectious diseases that led to specific diagnostic tests, effective preventions, and, in some cases, treatments. Causal thinking in medicine shifted from the earlier multicausal approaches to monocausal theories of etiology. Indeed, proving monocausal etiology became a way to establish the legitimacy of a disorder. Through the writings of Kahlbaum and Hecker, psychiatry was deeply influenced by this monocausal perspective, the importance of which was substantially amplified by a twist of fate: the increasing clinical importance of general paresis of the insane throughout the 19th century and the eventual proof that it too was a monocausal condition. However, in the mid-20th century, the third phase began. With decreasing deaths from infectious diseases, epidemiology and clinical medicine shifted to a chronic disease model in which paradigmatic disorders, such as cancer and cardiovascular disease, were shown to be highly multicausal. Biostatistics evolved from deterministic to probabilistic models of disease risk factors. Paradoxically, at this time, biological psychiatry, then rising to dominance in American psychiatry, vigorously pursued monocausal theories, first of neurochemical origin and then of genetic origin. We were trying to establish the legitimacy of our field by pursuing an outmoded model-that "real" diseases are monocausal. Despite ample evidence to the contrary, monocausal thinking continues to influence our field, for example, in the popular but improbable view that we can, with a few key advances, move easily from descriptive to etiologically based diagnoses.

Statistical Reasoning and Methods in Epidemiology to Promote Individualized Health: In Celebration of the 100th Anniversary of the Johns Hopkins Bloomberg School of Public Health.

Epidemiology is concerned with determining the distribution and causes of disease. Throughout its history, epidemiology has drawn upon statistical ideas and methods to achieve its aims. Because of the exponential growth in our capacity to measure and analyze data on the underlying processes that define each person's state of health, there is an emerging opportunity for population-based epidemiologic studies to influence health decisions made by individuals in ways that take into account the individuals' characteristics, circumstances, and preferences. We refer to this endeavor as "individualized health." The present article comprises 2 sections. In the first, we describe how graphical, longitudinal, and hierarchical models can inform the project of individualized health. We propose a simple graphical model for informing individual health decisions using population-based data. In the second, we review selected topics in causal inference that we believe to be particularly useful for individualized health. Epidemiology and biostatistics were 2 of the 4 founding departments in the world's first graduate school of public health at Johns Hopkins University, the centennial of which we honor. This survey of a small part of the literature is intended to demonstrate that the 2 fields remain just as inextricably linked today as they were 100 years ago.

In pursuit of a science of agriculture: the role of statistics in field experiments.

Since the beginning of the twentieth century statistics has reshaped the experimental cultures of agricultural research taking part in the subtle dialectic between the epistemic and the material that is proper to experimental systems. This transformation has become especially relevant in field trials and the paper will examine the British agricultural institution, Rothamsted Experimental Station, where statistical methods nowadays popular in the planning and analysis of field experiments were developed in the 1920s. At Rothamsted statistics promoted randomisation over systematic arrangements, factorisation over one-question trials, and emphasised the importance of the experimental error in assessing field trials. These changes in methodology transformed also the material culture of agricultural science, and a new body, the Field Plots Committee, was created to manage the field research of the agricultural institution. Although successful, the vision of field experimentation proposed by the Rothamsted statisticians was not unproblematic. Experimental scientists closely linked to the farming community questioned it in favour of a field research that could be more easily understood by farmers. The clash between the two agendas reveals how the role attributed to statistics in field experimentation defined different pursuits of agricultural research, alternately conceived of as a scientists' science or as a farmers' science.

A Mathematician's Odyssey.

In this overview of my research, I have aimed to give the background as to how I came to be involved in my various areas of interest, with an emphasis on the early phases of my career, which largely determined my future directions. I had the enormous good fortune to have worked under two of the most outstanding scientists of the twentieth century, R.A. Fisher and Joshua Lederberg. From mathematics and statistics, I went to population genetics and the early use of computers for modeling and simulation. Molecular biology took me into the laboratory and eventually to somatic cell genetics and human gene mapping. One chance encounter led me into the HLA field and another led me into research on cancer, especially colorectal cancer. On the way, I became a champion of the Human Genome Project and of the need for scientists to help promote the public understanding of science.