Search

The need for early detection and appropriate management of flags in physical therapy has been established. The lack of early detection has been shown to lead to poor outcomes such as serious pathology, increased disability, prolonged symptoms, and increased healthcare utilization. The main purpose of this survey study was to assess third-year Doctor of Physical Therapy (DPT) students' adherence to clinical practice guidelines specifically in the identification and management of red and yellow flags through a case-based approach. A survey including three different flag case scenarios was sent to DPT students in 15 geographically diverse physical therapy programs. Previously published case scenarios measuring adherence to practice guidelines were used. Correlational analyses were performed to link student demographic details and guideline adherent management. The survey was completed by 64 students. Guideline adherent management was greater for red flags (85%) than yellow flag cases (25% and 42%). No significant relationship was noted between the student details and guideline adherent management. DPT students may need additional educational content related to yellow flag screening. Educators may consider utilizing published red and yellow flag cases to guide decision-making and highlight best screening practices. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine sexual orientation-based disparities in six self-reported health outcomes among millennial aged military veterans. We collected data using The Millennial Veteran Health Study, a cross-sectional internet-based survey with extensive quality control measures. The survey was fielded April through December 2020 and targeted millennial aged veterans across the United States. A total of 680 eligible respondents completed the survey. We assessed six binary health outcomes: alcohol use, marijuana use, frequent chronic pain, opioid misuse, high psychological distress, and fair or poor health status. Using logistic regression adjusted for a range of demographic, socioeconomic, and military-based covariates, we find that bisexual veterans consistently report worse health than straight veterans for all six health outcomes tested. Results for gay or lesbian, compared to straight veterans, were less consistent. Sensitivity models with continuous outcomes, and stratified by gender, found similar results. These results have implications for improving the health of bisexual individuals, including addressing discrimination, belonging, and social identity, particularly in institutional settings that have traditionally heteronormative and masculine cultures such as the military. [ABSTRACT FROM AUTHOR]

Purpose: Research suggests social support may protect sexual minorities from the harmful effects of victimization that undermine mental and sexual health wellness; however, this relationship has been underexplored among a diverse youth population. We examined the association between lifetime homonegative victimization, perceived stress in the last month, and resilience factors among a diverse sample of adolescent sexual minority males. Methods: Data were collected between June 2018 and April 2020 as part of the MyPEEPS Mobile study, a multi-site randomized controlled trial evaluating the effectiveness of a mobile behavioral HIV prevention intervention for adolescents living in the U.S. We analyzed baseline survey data from 542 sexual minority males, aged 13–18 years. We used bivariate analyses to examine relationships among variables and multivariable linear regression models to determine if resilience factors attenuated the association between homonegative victimization and perceived stress. Results: Perceived stress was positively associated with younger age, internalized homophobia, experiencing verbal victimization, threats of being outed, and threats of physical violence. Relying on online friends for support and having good family relations both attenuated the relationship between verbal victimization and perceived stress. However, neither of these resilience factors significantly weakened the associations between perceived stress, threats of physical violence, and being outed. Conclusion: Resilience factors, including peer and family support, may play an attenuating role in the relationship between homonegative victimization and perceived stress among adolescent sexual minority males. ClinicalTrials.gov Identifier: NCT03167606 [ABSTRACT FROM AUTHOR]

Non-binary and genderqueer (NBGQ) individuals do not identify with a binary gender identity. Some but not all NBGQ individuals identify as transgender, and it is currently unclear on which aspects of mental and sexual well-being NBGQ and binary transgender individuals may differ. To compare NBGQ, binary transgender and cisgender individuals on variables related to mental well-being, sexual well-being, and sexual self-concept discrepancies. We conducted an online questionnaire study in 125 transgender men, 72 transgender women, 78 NBGQ individuals, 98 cisgender men, and 107 cisgender women. For most variables, NBGQ individuals did not differ from binary transgender individuals. These two groups differed only on gender dysphoria and transgender specific body image worries, which were both lower in the NBGQ group. Compared to the cisgender group, NBGQ individuals scored higher on gender dysphoria, actual/ought sexual self-concept discrepancies, and actual/ideal sexual self-concept discrepancies, and lower on general life satisfaction and sexual esteem related to body perception. These results offer a first quantitative analysis of sexual well-being in NBGQ individuals, and highlight that – while both groups face unique challenges – NBGQ individuals encounter similar difficulties concerning mental and sexual well-being as binary transgender individuals. [ABSTRACT FROM AUTHOR]

Statistical literacy is key in this heavily polarized information age for an informed and critical citizenry to make sense of arguments in the media and society. The responsibility of developing statistical literacy is often left to the K-12 mathematics curriculum. In this article, we discuss our investigation of K-8 students' current opportunities to learn statistics created by state mathematics standards. We analyze the standards for alignment to the Guidelines for the Assessment and Instruction in Statistics Education (GAISE II) PreK-12 report and summarize the conceptual themes that emerged. We found that while states provide K-8 students opportunities to analyze and interpret data, they do not offer many opportunities for students to engage in formulating questions and collecting/considering data. We discuss the implications of the findings for policy makers and researchers and provide recommendations for policy makers and standards writers. [ABSTRACT FROM AUTHOR]

To assist creators of public service announcements and anti-drinking campaigns, this study provides an in-depth examination of the risks of binge drinking from the perspective of college students. Using current risk models for guidance, key elements from the qualitative data in the study are addressed, including perceived risks and their severity, vulnerability to risks, self-efficacy, response efficacy, benefits from ritual functions, and other costs or benefits based on students' attitudes and beliefs. An integrated risk perception model is introduced. Student participants enumerated extensive risks; however, they generally felt invulnerable to the consequences. Most adopted a management style of 'taking chances' when binge drinking because they perceived a built-in safety net in the college environment. Three ritual functions and various attitudes and beliefs help explain why a cost and benefit analysis favors binge drinking. Recommendations are given. [ABSTRACT FROM AUTHOR]

We present a surprising though obvious result that seems to have been unnoticed until now. In particular, we demonstrate the equivalence of two well-known problems—the optimal allocation of the fixed overall sample sizenamongLstrata under stratified random sampling and the optimal allocation of theH= 435 seats among the 50 states for apportionment of the U.S. House of Representatives following each decennial census. In spite of the strong similarity manifest in the statements of the two problems, they have not been linked and they have well-known but different solutions; one solution is not explicitly exact (Neyman allocation), and the other (equal proportions) is exact. We give explicit exact solutions for both and note that the solutions are equivalent. In fact, we conclude by showing that both problems are special cases of a general problem. The result is significant for stratified random sampling in that it explicitly shows how to minimize sampling errorwhen estimating a totalTYwhile keeping the final overall sample size fixed atn; this is usually not the case in practice with Neyman allocation where the resulting final overall sample size might be nearn+Lafter rounding. An example reveals that controlled rounding with Neyman allocation does not always lead to the optimum allocation, that is, an allocation that minimizes variance. [ABSTRACT FROM PUBLISHER]

The Ethical Guidelines for Statistical Practice of the American Statistical Association (ASA) have evolved over a span of more than 60 years, going back to 1949. The Interim version of the Guidelines was published in 1980, the Trial version was published in 1983 and revised and formalized in 1989, the current version was approved by the Board of Directors and made available on the ASA's Web site in 1999, and ASA accreditation now requires statistical practitioners to agree to abide by them. The new century brings new ethical concerns for statisticians. As examples, bioethics is booming, climate science is newsworthy for both science and ethics, and issues of statistical integrity in research keeps the U.S. Department of Health and Human Services Office of Research Integrity very busy. In this century, we see a rapid increase in the ability to collect massive amounts of data, with complex structure and a sometimes sensitive nature. With these unparalleled opportunities for statisticians comes an increased need for clear guidelines on professional ethics. The evolution of the Guidelines therefore needs to continue. In this article, we examine the long history of the ASA Ethical Guidelines for Statistical Practice, and discuss potential areas for revision to meet the needs of our expanding profession. [ABSTRACT FROM AUTHOR]

Statistical relationships between annual floods at 200 long-term (85–127 years of record) streamgauges in the coterminous United States and the global mean carbon dioxide concentration (GMCO2) record are explored. The streamgauge locations are limited to those with little or no regulation or urban development. The coterminous US is divided into four large regions and stationary bootstrapping is used to evaluate if the patterns of these statistical associations are significantly different from what would be expected under the null hypothesis that flood magnitudes are independent of GMCO2. In none of the four regions defined in this study is there strong statistical evidence for flood magnitudes increasing with increasing GMCO2. One region, the southwest, showed a statistically significant negative relationship between GMCO2 and flood magnitudes. The statistical methods applied compensate both for the inter-site correlation of flood magnitudes and the shorter-term (up to a few decades) serial correlation of floods. Citation Hirsch, R.M. and Ryberg, K.R., 2012. Has the magnitude of floods across the USA changed with global CO2 levels? Hydrolological Sciences Journal, 57 (1), 1–9. [ABSTRACT FROM AUTHOR]

Statistics are developed to test for the presence of an asymptotic discontinuity (or infinite density or peakedness) in a probability density at the median. The approach makes use of work by Knight (1998) on L1 estimation asymptotics in conjunction with nonparametric kernel density estimation methods. The size and power of the tests are assessed, and conditions under which the tests have good performance are explored in simulations. The new methods are applied to stock returns of leading companies across major U.S. industry groups. The results confirm the presence of infinite density at the median as a new significant empirical evidence for stock return distributions. [ABSTRACT FROM AUTHOR]

We demonstrate a methodology for estimating, with a specified probability, the interval within which the true DEA efficiency of an individual Decision Making Unit occurs. With this procedure, decisions based on DEA scores are made under conditions of risk, as opposed to the current practice in which decisions are made under uncertainty. The method applies statistical Panel Data Analysis (PDA), which provides proven and powerful methodologies for diagnostic testing of residuals and estimation of confidence intervals. Using PDA, we demonstrate, with a sample of real-world data, that DEA score residuals sometimes are independent and Normally distributed, and estimate confidence intervals based on these validated assumptions. Then, using another sample of real-world data in which violations of these assumptions do occur, we demonstrate well-known PDA Generalized Least Squares statistical models that account for the violations in the estimation of confidence intervals. [ABSTRACT FROM AUTHOR]

The article discusses the use of U.S. Census data in teaching mathematics for social justice. It aims to provide middle grade teachers with a resource to assist students in learning and applying numeracy, data and statistics, and algebra to a real-world, social justice context. It explores the history of the U.S. Census and emphasizes on the census' importance. It describes three mathematics activities related to the 2000 U.S. Census as developed by the author including the mean center of the U.S. population, line of best fit, and family tree. The said activities aimed at helping sixth grade students learn important mathematics skills and concepts.

We consider a local post-stratification approach to analyze the capture–recapture dual system Accuracy and Coverage Evaluation (A.C.E.) data associated with the 2000 U.S. Census. The local post-stratification is carried out via a nonparametric regression estimation of the census enumeration and the correct enumeration functions. We propose a nonparametric population size estimator that is designed to accommodate some key aspects of the A.C.E.: missing values, erroneous enumerations, and extra covariates affecting the missingness and correct enumeration. The resulting estimates are compared with estimates from a conventional post-stratification and a logistic regression approach in an analysis on the 2000 Census A.C.E. data. [ABSTRACT FROM AUTHOR]

Those of us whose careers and personal lives focus on environmental issues do not want to admit any deficiency in ecological intelligence. Unfortunately, we have to face facts, and that includes me, which is part of the reason for writing this essay. Insufficient ecological intelligence results partly because of the phenomenon of information overload, but it is also due to the absence of systems, policies, or sometimes even intentions to make certain pieces of information open and public. Ecolabels are one way to remedy these problems. My own experience with the United States Green Building Council's green building rating system (Leadership in Energy and Environmental Design) and its success as a tool for transforming the building sector has demonstrated that these labeling programs can create massive market change. This essay aims 1) to pull together in one place a wide variety of statistics related to ecological intelligence, 2) to distill ten statements worth consideration regarding ecolabels, and 3) to advance a discussion on the trends, potential, and limitations of ecolabels in order to make doing the right thing by the environment and our health, for both individuals and organizations, much easier than it is now. [ABSTRACT FROM AUTHOR]

Since the U.S. Environmental Protection Agency began widespread monitoring of PM2.5 (particulate matter <2.5 p in diameter) concentration levels in the late 1990s, the epidemiological community has performed several observational studies directly relating PM2.5 concentration to various health endpoints including mortality and morbidity. However, recent research suggests that human exposure to the constituents of PM2.5 may differ significantly from ambient (or outdoor) PM2.5 concentration measured by monitors because people spend a great deal of time in environments, such as various indoor environments, where they are partially shielded from ambient sources of PM and are exposed to nonambient sources of PM. Recent research has provided some ways to include exposure information, but little has been done to determine the impact of including such information in a statistical model. To address this concern, we develop a three-stage Bayesian hierarchical model based on the Poisson regression model that is traditionally used to characterize the relationship between PM2.5 concentration and health endpoints. Our approach includes a spatial model relating monitor readings to average county PM2.5 concentration and an exposure simulator that links average ambient PM2.5 concentration to average personal exposure using activity pattern data. We apply our model to a study population in North Carolina and explore the impact of various exposure modeling assumptions on the conclusions that can be drawn about the link between PM2.5 exposure and cardiovascular mortality. [ABSTRACT FROM AUTHOR]

This article develops an information criterion for determining the number q of common shocks in the general dynamic factor model developed by Forni et al., as opposed to the restricted dynamic model considered by Bai and Ng and by Amengual and Watson. Our criterion is based on the fact that this number q is also the number of diverging eigenvalues of the spectral density matrix of the observations as the number n of series goes to infinity. We provide sufficient conditions for consistency of the criterion for large n and T (where T is the series length). We show how the method can be implemented and provide simulations and empirics illustrating its very good finite-sample performance. Application to real data adds a new empirical facet to an ongoing debate on the number of factors driving the U.S. economy. [ABSTRACT FROM AUTHOR]

We present two models for the short-term prediction of the number of deaths arising from common cancers in the United States. The first is a local linear model, in which the slope of the segment joining the number of deaths for any two consecutive time period is assumed to be random with a nonparametric distribution, which has a Dirichlet process prior. For slightly longer prediction periods, we present a local quadratic model. This extension of the local linear model includes an additional "acceleration" term that allows it to quickly adjust to sudden changes in the time series. The proposed models can be used to obtain the predictive distributions of the future number of deaths. as well their meals and variances through Markov chain Monte Carlo techniques. We illustrate our methods by runs on data from selected cancer sites. [ABSTRACT FROM AUTHOR]

We consider quantile autoregression (QAR) models in which the autoregressive coefficients can be expressed as monotone functions of a single, scalar random variable. The models can capture systematic influences of conditioning variables on the location, scale, and shape of the conditional distribution of the response, and thus constitute a significant extension of classical constant coefficient linear time series models in which the effect of conditioning is confined to a location shift. The models may be interpreted as a special case of the general random-coefficient autoregression model with strongly dependent coefficients. Statistical properties of the proposed model and associated estimators are studied. The limiting distributions of the autoregression quantile process are derived. QAR inference methods are also investigated. Empirical applications of the model to the U.S. unemployment rate, short-term interest rate, and gasoline prices highlight the model's potential. [ABSTRACT FROM AUTHOR]

Profiling is currently an important, and hotly debated, topic in health care and other industries looking for ways to control costs, increase profitability, and increase service quality. Managed care in particular has seen a proliferation in the use of statistical profiling methodology, particularly with regard to monitoring expenditure data. This article focuses on the specific problem of developing statistical methods appropriate for profiling physician contributions to patient pharmacy expenditures incurred in a managed care setting. The two-part hierarchical model with a correlated random-effects structure considered here accounts for both the skewed, zero-inflated nature of pharmacy expenditure data and the fact that patient pharmacy expenditures are correlated within physicians. The random-effects structure has an attractive interpretation in terms of a conceptual model for physician prescribing patterns. Using this model, we propose to rank physicians based on an appropriately constructed provider-level performance measure. This information is subsequently used to develop a novel financial incentive scheme. Inference is conducted in a Bayesian framework using Markov chain Monte Carlo. [ABSTRACT FROM AUTHOR]

We propose a new test for superior predictive ability. The new test compares favorably to the reality check (RC) for data snooping, because it is more powerful and less sensitive to poor and irrelevant alternatives. The improvements are achieved by two modifications of the RC. We use a studentized test statistic that reduces the influence of erratic forecasts and invoke a sample-dependent null distribution. The advantages of the new test are confirmed by Monte Carlo experiments and an empirical exercise in which we compare a large number of regression-based forecasts of annual U.S. inflation to a simple random-walk forecast. The random-walk forecast is found to be inferior to regression-based forecasts and, interestingly, the best sample performance is achieved by models that have a Phillips curve structure. [ABSTRACT FROM AUTHOR]

Several authors have reported evidence of long swings in U.S. dollar exchange rates by rejecting the random walk in favor of a Markov regime-switching model. We show that this evidence is not robust to an extension of the sample period. One should, however, not conclude that long swings are thus absent, because the tests may have insufficient power. A possible reason for this is the low data frequency, because existing tests are based on quarterly data, and we find that the power can be increased substantially by raising the data frequency. Indeed, weekly data reject the random walk, so we conclude that long swings are in the data. This conclusion is supported by significant superiority of regime switching over random walk out-of-sample forecasts of the direction of change. [ABSTRACT FROM AUTHOR]

This paper reports on an application a multivariate analysis technique called Co-Plot. It replicates a study conducted among leading MBA programmes in the United States using the same technique; a statistical method especially suited for this type of analysis where there are samples with relatively few observations (business schools) and large numbers of variables (subject modules, core and elective). Using Co-Plot the paper presents a mapping of the structure of 32 Association of Masters of Business Administration (AMBA) accredited MBA programmes in the United Kingdom and compares the characteristics of the resultant groupings of MBA programmes and the relationship between group membership. The patterns of core and elective modules offered by the selected MBA programmes are then compared with the rankings of UK business schools. The research shows that in the UK, unlike in the US, the clustering is not as strong and clear. Five groups/clusters of schools are identified together with four main clusters of core and electives modules offered. Differentiation is only significant when the electives modules are taken into account unlike the US where differentiation is evident between programmes with the core modules. [ABSTRACT FROM AUTHOR]

As in all recent censuses, the U.S. Census Bureau used statistical methods in the 2000 Census to account for missing or contradictory information concerning the number of people living in some identified housing units. These statistically corrected counts were used for congressional apportionment and redistricting. In 2002, the Supreme Court ruled that this limited use of statistics was both lawful and constitutional. This article provides a context for that decision, by tracing the evolution of statistical methods in the U.S. census, and the accompanying litigation. It then summarizes the statistical and legal arguments and issues raised in Utah v. Evans. [ABSTRACT FROM AUTHOR]

Interpreting group differences observed in aggregated data is a practice that must be done with enormous care. Often the truth underlying such data is quite different than a naive first look would indicate. The confusions that can arise are so perplexing that some of the more frequently occurring ones have been dubbed paradoxes. This article describes two of these paradoxes—Simpson's paradox and Lord's paradox—and illustrates them in a single dataset. The dataset contains the score distributions, separated by race, on the biological sciences component of the Medical College Admission Test (MCAT) and Step 1 of the United States Medical Licensing Examination™ (USMLE). Our goal in examining these data was to move toward a greater understanding of race differences in admissions policies in medical schools. As we demonstrate, the path toward this goal is hindered by differences in the score distributions which gives rise to these two paradoxes. The ease with which we were able to illustrate both of these paradoxes within a single dataset is indicative of how widespread they are likely to be in practice. [ABSTRACT FROM AUTHOR]

Systems for ranking college basketball or football teams take many forms, ranging from polls of selected coaches or members of the media to so-called computer-ranking systems. Some of these are used in ways that have considerable impact on the teams. The committee responsible for the selection and seeding of teams for the postseason National Collegiate Athletic Association (NCAA) Division I men's basketball tournament is influenced by various rankings, including ones based on the ratings percentage index (RPI). The Bowl Championship Series (BCS) rankings of NCAA Division I-A football teams determine which two teams compete in a postseason national championship game and determine eligibility for other prestigious postseason games. There are certain attributes that seem desirable in any ranking system to be used in selecting or seeding teams for postseason competition or that may have some other tangible or intangible effect on the teams. These attributes include accuracy, appropriateness, impartiality, unobtrusiveness, nondisruptiveness, verifiability, and comprehensibility. The polls, the RPI, and the BCS rankings are notably deficient in several of these attributes. A system having all of the attributes, except for unobtrusiveness, can be achieved by applying least squares to a statistical model in which the expected difference in score in each game is modeled as a difference in team effects plus or minus a home court/field advantage. The potential obtrusiveness of this approach can be circumvented by introducing modifications to reward winning per se and to eliminate any incentive for "running up the score" or for deliberately surrendering a lead so as to extend a game into overtime. The modified least squares system was applied to the 1999-2000 basketball and 1999-2001 football seasons. Its accuracy in predicting the outcomes of 73 postseason football games and 93 postseason basketball games was undiminished by the modifications and was comparable to that of the betting line. [ABSTRACT FROM AUTHOR]

Quantitative performance monitoring of health care providers has become an increasingly prominent activity in health care delivery. As a consequence, multidimensional "report cards" comparing the quality of services provided by diverse health care organizations have begun to appear. We present a case study examining the performance of 22 geographically defined health care systems, known as Veterans Integrated Service Networks; involving the treatment of more than 37,000 veterans discharged from general psychiatry program beds in fiscal year 1998. We describe multilevel multidimensional latent variable models and fit these to a set of related mixed discrete and continuous outcomes to identify networks providing inadequate care to its patients. We use validation sample to assess model fit by comparing observed statistics to the distribution of the statistics across replicated datasets. We propose using posterior tail probabilities associated with functions of the latent variables to select networks with poor outcomes, and finally compare our results with those from current methods. [ABSTRACT FROM AUTHOR]

Minimum t statistics to test for a unit-root are available when the form of break under the alternative evolves according to the crash, changing growth, and mixed models. It is shown that serious power distortions occur if the form of break is misspecified, and thus the practitioner should use the mixed model as the appropriate alternative in empirical applications. The mixed model may reveal useful information regarding the location and form of break. The maximum F statistic for the joint null of a unit-root and no breaks is shown to have greater and less erratic power compared to the minimum t statistic. Stronger evidence against the unit-root is found for the Nelson-Plosser series and U.S. Postwar quarterly real gross national product. [ABSTRACT FROM AUTHOR]

We analyze the modifications that occur in indirect inference when a nuisance parameter is not identified under the null hypothesis. We develop a testing procedure adapted to this simulation-based estimation method, and detail its use for detecting the threshold effect in threshold moving average models with contemporaneous and lagged asymmetries. In contrast to existing threshold models, these models allow taking into account the presence of asymmetric effects of current and lagged random shocks. We use them to measure the persistence of shocks to U.S. output. [ABSTRACT FROM AUTHOR]

Highlights the 2001 Deming Lecture of the American Statistical Association at the Joint Statistical Meetings in Atlanta, Georgia. Presentation of the proactive statistician; Concept of statistical leader; Development of statistics and statistician.

Presents issues concerning on statistical methods in the U.S. Importance of Bayesian analysis for p value estimation; Usability of likelihood function; Impact of assuming alternative reasonable priors on posterior distribution.

The article focuses on the trends in undergraduate economics degrees in the U.S. from 1991 to 2001. The latest data on undergraduate economics degrees awarded by U.S. colleges and universities indicate that recovery from the severe plunge in the number of degrees experienced in the early 1990s continues unabated. Although the sample is not random, it is large. Essentially all of the nation's lost economics majors since the peak in 1991-92 are accounted for by a 24 percent decline at public universities. In contrast to recent experience, however, the gap between public and private institutions started to close in 2000-01, whereas public university degrees rose by 4.5 percent, the number of economics degrees awarded by private colleges and universities hardly changed last year. The percentage of undergraduate degrees in economics awarded to women is reported. At public universities, it has risen from 26 or 27 percent in the early 1990s to about 30 percent today. Women are least well represented among those earning an undergraduate economics degree at regional state universities that do not offer any advanced degrees in economics.

This article studies forecasting a macroeconomic time series variable using a large number of predictors. The predictors are summarized using a small number of indexes constructed by principal component analysis. An approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts. The method is used to construct 6-, 12-, and 24-month-ahead forecasts for eight monthly U.S. macroeconomic time series using 215 predictors in simulated real time from 1970 through 1998. During this sample period these new forecasts outperformed univariate autoregressions, small vector autoregressions, and leading indicator models. [ABSTRACT FROM AUTHOR]

When subjects are measured twice, once at each of two symmetrical locations or times, stability of responses in the absence of treatment within subjects, together with comparability of untreated responses between subjects, is often viewed as supporting a conclusion that differences between treated and control responses reflect effects actually caused by the treatment. The degree to which this intuitive argument is formally correct is explored is several related models: a multivariate Normal model, a nonparametric model defined by symmetries, an analogues randomized experiment, and sensitivity analysis model for observational studies in which treatments are not randomly assigned to subjects, nor to locations within subjects. Card and Kreuger's study of the employment effects of the minimum wage is used to illustrate the methods. [ABSTRACT FROM AUTHOR]

The following three articles are the results of papers presented and discussed at a symposium entitled "Improving the Workforce of the Future: Opportunities in Undergraduate Education," held August 12-13, 2000, in Indianapolis, IN. This symposium was sponsored by the American Statistical Association through its Undergraduate Statistics Education Initiative. The first article was the keynote address at the symposium. The latter two articles are position papers that were developed in part through discussions among representatives from liberal arts colleges, research universities, industry, and government at a May 1999 meeting at the ASA Headquarters and a subsequent April 2000 workshop in Alexandria, VA. This workshop was partially supported by the National Science Foundation. Other position papers based on symposium discussions are being developed and are scheduled to appear in the Journal of Statistical Education. [ABSTRACT FROM AUTHOR]

Deals with a study which discussed the curriculum guidelines for the Bachelor of Science degrees in statistical science in the United States. Historical background of the study; State of undergraduate programs in statistics; Recommendations for the statistics curriculum.

Analyzes the data gathered by the Industrial Research Institute on the spending of companies in research and development (R&D) and their sales revenue for the fiscal year 1998. Growth pattern of R&D expenditures of companies in the United States; How to evaluate the intensity of R&D expenditures of companies.

Focuses on the suggested enactment of a legislation to establish a commission to study the United States Federal Statistical System and make recommendations to solve the social problems of the nation. Details on the creation of the Consumer Price Index (CPI); Background of the Social Security Solvency Act of 1998 and its implication on the tax burden for the young and elderly; Efforts considered to bring back an organized statistical system of the nation.

The Advanced Placement Statistics course, first offered in 1997 after more than 12 years of planning, allows high school students who pass an examination to receive college credit for a statistics course taken at their high school. In its third year 25,240 students took this examination, and 57% "passed." The three-hour exam consists of both multiple choice and free response questions, which cover the four sections of the AP Statistics syllabus: data exploration, study design, probability distributions through simulation, and inference. Although some problems remain, both students and teachers find the course to be challenging and valuable. [ABSTRACT FROM AUTHOR]

Examines the role of statistics and the role of statisticians both in practice and training in the United States. Preparation of practitioners in the 21st century; Relevance in decision-making practices; Importance of the American Statistical Association.

Highlights results of a survey conducted by the Conference Board of the Mathematical Sciences on undergraduate programs in the United States. Enrollment in statistics courses; Number of bachelor's degrees with a major in statistics; Breakdown of full-time and part-time faculty members.

Presents a first-person narrative of a geographer in the United States regarding developments in quantitative geography in the 1950s and 1960s. Arrival in the Department of Geography at the State University of Iowa in the fall of 1957; Appointment of Edwin Thomas to the department's faculty in 1958 which served as a catalyst in the accelerated and formal development of quantitative geography who brought with him his expertise in statistical analysis.

Presents a first-person narrative of a geographer in the United States regarding developments in the discipline of geography from 1957 to 1977. Early graduate days in the fall of 1956 at the Northwestern University; Stagnation of geography for decades because of lack of tools, methodological insight and development; General trend of applying statistics to geographical research; Philosophical issues in geography.

Discusses the role of Fred K. Schaefer in the development of the science of geography. Family background; Graduation at the Kaiser Friedrich Real Gymnasium in 1927; Postgraduate studies at the University of Berlin from 1928 to 1932; Work as a statistician; Political refuge in London when the Nazis came to power; Migration to the United States in 1938; Staff member at the State University of Iowa; Famous article, "Exceptionalism in Geography: A Methodological Examination".

This article presents the first population profile of men and women age 85 and over. It was developed with the 1980 census PUMS sample A, of which nearly 70% were women. Men were better off than women in both socioeconomic and relational characteristics in that they had higher personal incomes from nearly all sources and were far more likely to be married and living independently. They were not found in nursing homes in as great a proportion as were very old women. In a sense, then, the generalizations about the very old have a female bias. [ABSTRACT FROM AUTHOR]

Shows how a standard statistical forecasting model can estimate the probability that a single vote will be decisive in the presidential elections. Factors that determine the probability that a vote is decisive; Theoretical framework for estimating the probability of a decisive vote in the electoral college; Details of the implementation with historical data; Approximate results for the United States congressional elections; Conclusions.

This article highlights the historical events that took place within 50 years since the American Statistical Association was founded in 1839 and the Journal of the American Statistical Association (JASA) was first published in 1888. For the first years, JASA contained almost exclusively nonmathematical papers. Many were mere repositories of extensive data sets, including many compilations from census counts with interpretations of what these data purportedly revealed. Others were from investigations undertaken by sociologists, economists, political scientists and historians. One area that attracted theoretical attention dealt with the concepts of averages, variation and distributions. The second area that received theoretical attention during these years was correlation and related concepts.

Any screening program based on a quantitative risk factor has the objective of identifying individuals at high risk of disease. When the risk factor varies within individuals over time or is subject to measurement error, repeat measurements should aid risk assessment. This ankle presents statistical guidelines for sequential screening based on measurements accumulated over time. The aim for each subject is to decide whether (a) risk is sufficiently low that screening can be stopped, or (b) risk is sufficiently high that intervention is indicated, or (c) further measurements should be Obtained to improve risk assessment. The guidelines presented are optimal in a population, public health sense; that is, they are designed to give the maximal expected risk in the group identified for intervention, subject to constraints on that group's size and on the cost of screening (defined in terms of the average number of measurements per person required). An example concerning screening for cardiovascular disease in middle-aged men using diastolic blood pressure measurements is presented. [ABSTRACT FROM AUTHOR]

In the early 1980s, the U.S. Army opened the National Training Center (NTC) as its main U.S. training venue for battalions and brigades. The NTC's primary purpose was training, but because the simulated combat was fairly realistic, many hoped it would provide a son of laboratory for identifying problems and exploring ways to fix them. This article describes a project that studied tactical reconnaissance at the NTC. The project's substantive purpose was to look for problems in the organization, doctrine, equipment, and training for tactical reconnaissance, and to suggest remedies. Its methodological purpose was to learn how to measure reconnaissance activities and how to use those measurements for analytical purposes, neither of which had been done previously. This article gives background on the NTC and on tactical reconnaissance, and then traces the steps of the reconnaissance project. The two main methodological issues are how to gather measurements in venues like the NTC and what kinds of questions such venues can be used to answer. As it turns out, high-tech measurements are generally of little use low-tech measurements are useful for diagnosis (description) and hypothesis generation, predictions and causal inferences being fraught with hazard. Modest as these uses are, the NTC data are nonetheless highly valuable.

Screening of pooled urine samples was suggested during the Second World War as a method for reducing the cost of detecting syphilis in U.S. soldiers. Recently, pooling has been used in screening for human immunodeficiency virus (HIV) antibody to help curb the further spread of the virus. Pooling reduces the cost but also--and probably more importantly--offers a feasible way to lower the error rates associated with labeling samples when screening low-risk HIV populations. For example given the limited precision of the presently available test kits, when the screened population has a prevalence of 4 per 1,000 (which is roughly the estimated U.S. prevalence), the probability that a sample labeled positive is antibody-free can be reduced from approximately 90% (if each sample is tested individually) to about 2%. Furthermore, screening pooled sera samples can also be used to reduce the probability that a sample labeled negative in fact has antibodies up to 40-fold in such a population--an important consideration when attempting to preserve the integrity of the blood supply. In this article we generalize some commonly used pooling procedures and introduce some new ones. We discuss and compare these procedures' relative merits and weaknesses under practical situations in the context of HIV screening. The proposed procedures can also be used and generalized to other medical and quality control applications.

Describes a statistical study of hitting streaks in Major League baseball. Probability of occurrence of streaks; Examination of the records of Major League players; Exhibition of streakiness in certain years.