A Newton-Raphson algorithm for maximum likelihood factor analysis

This paper demonstrates the feasibility of using a Newton-Raphson algorithm to solve the likelihood equations which arise in maximum likelihood factor analysis. The algorithm leads to clean easily identifiable convergence and provides a means of verifying that the solution obtained is at least a local maximum of the likelihood function. It is shown that a popular iteration algorithm is numerically unstable under conditions which are encountered in practice and that, as a result, inaccurate solutions have been presented in the literature. The key result is a computationally feasible formula for the second differential of a partially maximized form of the likelihood function. In addition to implementing the Newton-Raphson algorithm, this formula provides a means for estimating the asymptotic variances and covariances of the maximum likelihood estimators. This research was supported by the Air Force Office of Scientific Research, Grant No. AF-AFOSR-4.59-66 and by National Institutes of Health, Grant No. FR-3.     

A computational procedure for tau correlation

Thetau coefficient is defined, and a computational procedure for tied ranks is described. The procedure maintains continuous computational checks, saves labor, and particularly facilitates the use oftau with large samples. It is also shown howtau correlation may be applied toQ-sorts with any shape of forced distribution or with unforced distributions.The procedure described was developed in connection with research at the Counseling Center, University of Chicago. The research is supported by a grant (PHS M 903) from the National Institute of Mental Health, of the National Institutes of Health, Public Health Service.     

F tests for the absolute invariance of dominance and composition scales

Significance tests are developed for evaluating the absolute invariance of the dominance and composition scales presented in a previous paper [Bechtel, 1967]. These tests derive from the multivariate normality of the estimated scale values—this multinormality stemming from that of the observations upon which these estimated scale parameters are based. The scales compared by means of the present techniques will typically be constructed under distinct experimental conditions, which may take the concrete form of treatments, occasions, individuals, or groups. Thus the present tests possess a wide range of applicability including various experimental designs in which scale configuration is the dependent variable. Illustrative data are used in statistically comparing the scale structures of two different individuals.This research was supported in part by National Institutes of Health Grant MH-04439-06. The author would like to express his appreciation to Fred C. Andrews of the University of Oregon and J. E. Keith Smith of the University of Michigan for their helpful comments concerning aspects of this work. Computing assistance was obtained from the Health Sciences Computing Facility, UCLA, sponsored by NIH Grant FR-3.     

Why convene rater teams: An investigation of the benefits of anticipated discussion,consensus, and rater motivation

This study explores the importance of anticipated group discussion, the consensus decision rule, and rater motivation in determining how well rater teams identify ratee behaviors, i.e., behavioral accuracy. Results, based on 382 raters in 111 teams, suggest that the anticipation of group discussion can improve behavioral accuracy, but it appears that the benefits of discussion-only teams are limited to this anticipation effect. Furthermore, it also appears that rater motivation plays an important role in this type of team. Rater teams required to reach consensus, however, appear to show improved behavioral accuracy, regardless of whether raters can anticipate the consensus discussion and regardless of rater motivation levels. Implications, especially for assessment centers, are discussed.     

Peer review: Selecting the best science

The major challenge facing today’s biomedical researchers is the increasing competition for available funds. The competitive review process, through which the National Institutes of Health (NIH) awards grants, is built upon review by a committee of expert scientists. The NIH is firmly committed to ensuring that its peer review system is fair and objective. Wendy Baldwin, Ph.D., is Deputy Director for Extramural Research, National Institutes of Health. This paper is based on a presentation at a workshop, “Advances in Peer Review Research”, American Association for the Advancement of Science Meeting, Baltimore, MD, February 9, 1996.     

Health-Risking Social Behaviors: Moving Forward

The National Institute of Mental Health (NIMH) and the National Institute on Drug Abuse (NIDA) have a long history of supporting investigator-initiated research and research training to enhance the scientific understanding of and effective interventions for a range of problems associated with youth violence. New technologies are emerging and basic research has promise for increasing our understanding of how biological factors operate in conjunction with other factors to contribute to violent behavior, psychopathology, and drug abuse. This article describes emerging areas and directions for research in this important area of public health.The views expressed are those of the authors and do not necessarily represent those of the National Institute of Mental Health, the National Institute on Drug Abuse, the National Institutes of Health, the Department of Health and Human Services, or the U.S. Government.     

A note on some equations of confirmatory factor analysis

The method of deriving the second derivatives of the goodness-of-fit functions of maximum likelihood and least-squares confirmatory factor analysis is discussed. The full set of second derivatives is reported.This research was supported by a PHS research grant No. M-10006 from the National Institutes of Mental Health, Public Health Service.     

Optimal choice of rater terms I: Theory

How can an investigator choose a good team of raters to use for measuring a continuous variable when each available rater produces only dichotomous responses? We formulate an underlying model, define an index of goodness for rater teams in terms of average mean square error of the estimate, develop a new estimator and derive the optimal rater terms. The optimal raters have characteristic curves which are linear in form and satisfy the requirements for a Guttman scale.     

A call to collaboration: the federal commitment to suicide prevention

The federal government, largely through the U.S. Department of Health and Human Services (HHS), sponsors an array of science-based suicide prevention initiatives. This article details the prevention-related agendas and collaborative efforts of five operating divisions within the Department of Health and Human Services: the Substance Abuse and Mental Health Services Administration, National Institutes of Health, Centers for Disease Control and Prevention, Indian Health Service, and Health Resources and Services Administration. The article highlights HHS's activities and their link to the National Strategy for Suicide Prevention, the plan which will guide the nation's suicide prevention efforts for the next decade.     

Imaging brain in search of mind

The fourth annual fMRI Experience was held at the National Institutes of Health (NIH), in Bethesda, Maryland, USA, on 3-14 May 2002. The conference was organized jointly by research fellows at the NIH and Institute of Psychiatry (IoP) in London, and benefited from financial support from the National Institute of Mental Health (NIMH) Intramural Research Program, the NIMH Division of Intramural Training, and the Guarantors of Brain in association with the IoP.     

Beauty is in the sex of the beholder: An examination of the effects of interviewer characteristics on assessments of respondent attractiveness

Research exploring the effects of physical attractiveness frequently assesses attractiveness by employing subjective appraisals by independent raters. However, there is reason to believe that rater characteristics – especially their sex – may systematically bias subjective ratings of physical attractiveness. The current study explores this possibility by analyzing data from the National Longitudinal Study of Adolescent Health (N = 13,330). Analyses of these data revealed that ratings of physical attractiveness are significantly influenced by the sex of the interviewer/rater. Specifically, male raters were significantly less likely than female raters to assess males as attractive, very attractive, and very unattractive. The results are explained within the context of evolutionary psychology and illustrate a methodological concern for research on physical attractiveness.     

Derivations of learning statistics from absorbing Markov chains

Learning-process statistics for absorbing Markov-chain models are developed by using matrix methods exclusively. The paper extends earlier work by Bernbach by deriving the distribution of the total number of errors, u-tuples, autocorrelation of errors, sequential statistics, and the expectation and variance of all statistics presented. The technique is then extended to latency derivations including the latencies of sequential statistics. Suggestions are made for using the sequential-statistic algorithm in a maximum-likelihood estimation procedure. The technique is important because statistics for very large absorbing matrices can be easily computed without going through tedious theoretical calculations to find explicit mathematical expressions.The author is indebted to his students Thomas Wiekens and Richard Freund who were helpful in the development of this paper. Support was received for this work from Grant MH-11255 from the National Institutes of Mental Health.     

Beauty is in the sex of the beholder: An examination of the effects of interviewer characteristics on assessments of respondent attractiveness

Research exploring the effects of physical attractiveness frequently assesses attractiveness by employing subjective appraisals by independent raters. However, there is reason to believe that rater characteristics – especially their sex – may systematically bias subjective ratings of physical attractiveness. The current study explores this possibility by analyzing data from the National Longitudinal Study of Adolescent Health (N = 13,330). Analyses of these data revealed that ratings of physical attractiveness are significantly influenced by the sex of the interviewer/rater. Specifically, male raters were significantly less likely than female raters to assess males as attractive, very attractive, and very unattractive. The results are explained within the context of evolutionary psychology and illustrate a methodological concern for research on physical attractiveness.     

A rapid non-parametric estimate of multi-judge reliability

A technique is presented for obtaining a rapid estimate of reliability between judges, with special reference to qualitative judgments. It is shown that reliability and discrimination are independent and that estimates of both are needed. A method of obtaining an independent estimate of multi-judge discrimination is developed. It is shown that the size of item-samples is specified by the latter method. Tests of significance for both reliability and discrimination are described.This technique was developed in connection with research at the Counseling Center, University of Chicago. This investigation was supported by a research grant (PHS M 903) from the National Institute of Mental Health, of the National Institutes of Health, Public Health Service. Acknowledgment is made to Dr. Lyle V. Jones, University of Chicago, for valuable discussions relevant to the technique. Responsibility rests, however, entirely with the writer.     

Laboratory Safety and Nanotechnology Workers: an Analysis of Current Guidelines in the USA

Although some regulatory frameworks for the occupational health and safety of nanotechnology workers have been developed, worker safety and health issues in these laboratory environments have received less attention than many other areas of nanotechnology regulation. In addition, workers in nanotechnology labs are likely to face unknown risks and hazards because few of the guidelines and rules for worker safety are mandatory. In this article, we provide an overview of the current health and safety guidelines for nanotechnology laboratory workers by exploring guidelines from different organizations, including the Department of Energy Nanoscale Science Research Centers (DOE-NSRC), Massachusetts Institute of Technology (MIT), the National Institutes of Health (NIH), the National Institute for Occupational Safety and Health (NIOSH), the Occupational Safety and Health Administration (OSHA), Texas A&M University (TAMU), and University of Massachusetts-Lowell (UML). After discussing these current guidelines, we apply an ethical framework to each set of guidelines to explore any gaps that might exist in them. By conducting this gap analysis, we are able to highlight some of the weaknesses that might be important for future policy development in this area. We conclude by outlining how future guidelines might address some of these gaps, specifically the issue of workers’ participation in the process of establishing safety measures and the development and enforcement of more unified (and mandatory) guidelines.     

New analysis of variance formulas for treating data from mutually paired subjects

The experimental design considered in this paper is one in which each of a group of several subjects is observed in the presence of each of the other subjects of the group, the entire set of possible pairings being repeated or replicated on several occasions. Analysis of variance formulas are described for this somewhat unusual design. Both the model of constants and mixed model are considered. Reliability formulas growing out of the analysis of variance calculations are developed.This work was supported in part by grants M-627; M-627C from the National Institutes of Health, Public Health Service.     

Maximum likelihood estimation of parameters of signal detection theory—A direct solution

Ogilvie and Creelman have recently attempted to develop maximum likelihood estimates of the parameters of signal-detection theory from the data of yes-no ROC curves. Their method involved the assumption of a logistic distribution rather than the normal distribution in order to make the mathematics more tractable. The present paper presents a method of obtaining maximum likelihood estimates of these parameters using the assumption of underlying normal distributions.This research was supported in part by grants from the National Institutes of Health, MH-10449-02, and from the National Science Foundation, NSF GS-1466.     

Qualitative Cancer Genetic Counseling Research, Part I: Ethnography in a Cancer Clinic

This is a report of the experience of several months' ethnographic research by a genetic counselor researcher in a cancer treatment clinic. One goal of the exercise was to directly experience a method of qualitative research known as ethnography, which relies heavily on participant-observation, in an applied clinical setting. Another goal was to explore a previously undescribed research area in the genetic counseling literature, namely, the meaning of cancer and cancer treatment for affected individuals and their support companions. Here we report on a personal account of the experiences of conducting and publishing the research. The preliminary analysis and results of this field experience are published elsewhere (Peters et al. (2001) J Genet Counsel 10(2):151–168.). These initial findings support the feasibility of genetic counselors, who are trained in specific social science methodologies, to conduct qualitative research pertinent to genetic counseling practice.This work was completed at the University of Pittsburgh before employment at the National Cancer Institute (NCI) and does not represent the views of the NCI, the National Institutes of Health, the Department of Health and Human Services, or the Federal Government     

Introduction

Clinical research is now a global enterprise. However, research ethics capacity has lagged behind the growth and expansion of clinical research in low and middle income countries. To address this mismatch, the Fogarty International Center of the National Institutes of Health has created a program to fund education in research ethics. This series of articles describes the experiences of graduates from 5 nations of the University of Toronto’s Joint Centre for Bioethics International Masters of Health Science Program. The program has graduated 32 students to return to their institutions to build research ethics capacity.