Alternative medicine and herbal use among university students

In this study, the authors investigated the predictors of complementary and alternative medicine (CAM) and herbal supplement use among university students. They investigated demographic factors, trait affectivity, symptom reports, and individuals' worries about modernity as potential contributors to use of CAM and herbals. The authors surveyed 506 undergraduates at a large southeastern state universityand administered the following questionnaires to participants in a group setting: a CAM survey, an herbal use survey, a negative affect (NA) and positive affect (PA) scale, Modern Health Worries scale, and the Subjective Health Complaint scale. Overall, 58 % of the participants had used at least one type of CAM, and 79 % of the students had used at least one herbal substance in the past 12 months. A hierarchical regression determined that increased age, female gender, flu-like symptoms, musculoskeletal symptoms, pseudoneurological symptoms, and modern health worries were significantly related to students' CAM use. Herbal use was related to increased age, musculoskeletal, pseudoneurological, and gastrointestinal symptoms.     

An omnibus test of goodness-of-fit for conditional distributions with applications to regression models

We introduce an omnibus goodness-of-fit test for statistical models for the conditional distribution of a random variable. In particular, this test is useful for assessing whether a regression model fits a data set on all its assumptions. The test is based on a generalization of the Cramér–von Mises statistic and involves a local polynomial estimator of the conditional distribution function. First, the uniform almost sure consistency of this estimator is established. Then, the asymptotic distribution of the test statistic is derived under the null hypothesis and under contiguous alternatives. The extension to the case where unknown parameters appear in the model is developed. A simulation study shows that the test has good power against some common departures encountered in regression models. Moreover, its power is comparable to that of other nonparametric tests designed to examine only specific departures.     

Differences in Audiotaped Versus Videotaped Physician-Patient Interactions

Most medical interaction studies have been conducted on audiotaped recordings of physician-patient encounters. Empirical studies have not previously demonstrated whether coders' scores differ on audio-only versus videotaped data. Data from a convenience sample of forty-seven physician-patient interactions were analyzed using the same coding systems to judge audio-only versus video-based data formats. All coding conditions demonstrated acceptable reliability, using intraclass correlation coefficients. However, MANOVA analyses show that ratings of audiotaped physician-patient interactions are not equivalent to ratings of videotaped encounters. Exploratory factor analyses show differences in the underlying structures of the data derived from the audio-only versus the video information. The differences in the video-based factor solutions account for more total variance and are more consistent with theoretical expectations.     

Developing nation models for American Indian nation building-Educating the young leaders of our internal developing nations

American Indian Nations share many common issues with nations in the non-Western world which are developing contemporary economic and political systems after a period of colonialization by Western European countries. Native American students can gain greater understanding of the historical process of nation building in which they are engaged and insight into strategies for integrating the contemporary economics and technology with traditional values and practices from the experiences of some of these non-Western nations. College level courses on American Indian government should utilize nation building examples from the non-Western world in addition to examples from contemporary native nations in North America to broaden students' understanding of tribal government development as part of the process of national regeneration being undertaken by formerly colonized peoples throughout the world.     

Quasi Most Powerful Invariant Goodness-of-fit Tests

ABSTRACT.  In this paper, we develop an approximation for the most powerful invariant test of one location-scale family against another one. The approach is based on the Laplace method for integrals and yields a very accurate approximation of the density of a maximal invariant. Moreover, it can be applied to a much wider set of pairs of densities than previously possible. Many examples are worked out. The resulting test is easy to compute and its power is shown to be very close to that of the best test. By using versions of the Laplace method, the approach is extended to goodness-of-fit tests for residuals in regression and to some multivariate distributions. A small simulation study confirms the theoretical results. An example concludes the paper.     

Uniqueness of the least-distances estimator in regression models with multivariate response

In a regression model with univariate response, the quantities derived from the least-absolute-deviations method need not be unique. In this note, we show that, contrary to the univariate case, in a regression model with multivariate response, the least-distances method typically yields quantities that exhibit uniqueness properties that are similar to those obtained by the least-squares method.     

Analysis of band‐recovery data in a multistate capture‐recapture framework

Dead recoveries of marked animals are commonly used to estimate survival probabilities. Band‐recovery models can be parameterized either by r (the probability of recovering a band conditional on death of the animal) or by f (the probability that an animal will be killed, retrieved, and have its band reported). The T parametrization can be implemented in a capture‐recapture framework with two states (alive and newly dead), mortality being the transition probability between the two states. The authors show here that the f parametrization can also be implemented in a multistate framework by imposing simple constraints on some parameters. They illustrate it using data on the mallard and the snow goose. However, they mention that because it does not entirely separate the individual survival and encounter processes, the f parametrization must be used with care on reduced models, or in the presence of estimates at the boundary of the parameter space. As they show, a multistate framework allows the use of powerful software for model fitting or testing the goodness‐of‐fit of models; it also affords the implementation of complex models such as those based on mixture of information or uncertain states     

Comparison of Kernel Density Estimators with Assumption on Number of Modes

A data-driven bandwidth choice for a kernel density estimator called critical bandwidth is investigated. This procedure allows the estimation to have as many modes as assumed for the density to estimate. Both Gaussian and uniform kernels are considered. For the Gaussian kernel, asymptotic results are given. For the uniform kernel, an argument against these properties is mentioned. These theoretical results are illustrated with a simulation study that compares the kernel estimators that rely on critical bandwidth with another one that uses a plug-in method to select its bandwidth. An estimator that consists in estimates of density contour clusters and takes assumptions on number of modes into account is also considered. Finally, the methodology is illustrated using environment monitoring data.     

Mortality due to External Causes in Three Rural Areas of Senegal

Mortality due to external causes was measured over the period 1985–2004 in three rural areas of Senegal—Bandafassi, Niakhar and Mlomp – whose populations have been under continuous demographic surveillance for many years. The standardized annual rate of deaths due to external causes is 31 deaths per 100,000 inhabitants in Niakhar, 56 in Bandafassi and 102 in Mlomp. The causes of injury-related deaths generally reflect the rural living environment, with relatively few deaths due to road accidents (1.9 deaths per 100,000 inhabitants in Niakhar, 3.0 in Bandafassi and 2.0 in Mlomp), but many deaths due to falls (8.6 deaths per 100,000 inhabitants in Niakhar, 15.1 in Bandafassi and 23.3 in Mlomp). For certain causes, mortality varies considerably. Snake bites, for example, cause 0.1 deaths per 100,000 inhabitants in Niakhar, 13.4 in Bandafassi and 3.0 in Mlomp. The differences between sites are linked in this case to the relative concentrations of wildlife, in turn linked to differences in the local environment and in population densities (144 inhabitants per sq.km in Niakhar versus 19 in Bandafassi and 114 in Mlomp). Although the study areas are still largely unaffected by causes of death associated with development, such as traffic accidents, mortality due to external causes is high.     

Farm Structure and Economic Well-Being: A Look at Three Methodological Sins

Abstract Sociologists have increasingly turned to secondary data sources to study social and economic change. As our experience in this area increases, so should our methodological rigor. Three common methodological sins—model mis-specification, inattention to regional influences, and fuzzy operationalizations—are illustrated through a critique of Barnes and Blevins' (1992) study of farm structure and economic well-being in nonmetropolitan areas. This paper argues, and demonstrates empirically, that many of Barnes and Blevins' conclusions are suspect because they did not include ethnic and regional variables in their regression studies.