This study investigated the effects of laboratory-induced stress and beta-adrenergic blockade on acoustic and aerodynamic voice measures. In a double-blind, placebo-controlled trial, 12 participants, six males and six females, underwent cold pressor-induced sympathetic activation followed by placebo or treatment with 40 mg propranolol. Aerodynamic and acoustic parameters of voice were collected at baseline, during cold pressor and after treatment with propranolol or placebo. Fundamental frequency, jitter, shimmer, maximum airflow declination rate, voice onset time, speaking rate, and subglottal pressure were measured at baseline, during cold pressor-induced stress, and after treatment with propranolol or placebo. Cardiovascular measures served as indicators of sympathetic nervous system (SNS) activation by cold pressor and antagonism by propranolol, and were collected during all conditions. Cold pressor appeared to adequately agonize the SNS as indicated by significant increases in resting systolic and diastolic blood pressure and heart rate. Propranolol appeared to adequately antagonize the SNS for the participants. Jitter ratio demonstrated a statistically significant increase in the participants treated with propranolol. Speaking rate demonstrated a small but significant increase in the placebo control group during cold pressor. Gender differences were observed in a few measures. Cold pressor adequately agonized and propranolol adequately antagonized the SNS. No statistically significant differences across subjects were observed in the voice parameters during cold pressor-induced stress before treatment. Jitter ratio increased significantly during propranolol treatment and cold pressor. Speaking rate demonstrated a statistically significant increase during cold pressor in the placebo control group. Gender differences were observed, but were few.

OBJECTIVE:To determine if there were differences by demographic variables in response rates to Nutrition Screening Initiative (NSI) Checklist statements reported by over 50% of Oklahoma Older Americans Act Nutrition Program (OAANP) congregate meal participants categorized at high nutritional risk based on cumulative NSI Checklist scores.DESIGN:This study evaluated Oklahoma State Unit on Aging statewide archival demographic and NSI Checklist data from 8892 OAANP congregate participants.ANALYSIS:Data were analyzed using chi-square analyses.RESULTS:Eighteen percent of congregate participants were categorized at high nutritional risk. Over 50% of participants categorized at high nutritional risk reported "yes" to having an illness or condition that affected food eaten; eating alone; taking 3 or more medications; and inability to shop, cook, and feed themselves. Significant differences were observed in participant "yes" response rates to these NSI Checklist statements by demographic variables. Participants responded "yes" more to these statements if they were female, of advanced age, and living alone or in rural areas.CONCLUSIONS AND IMPLICATIONS:The results of this study indicate problem areas and population groups for targeting nutrition education programs and services among Oklahoma OAANP congregate meal participants.

A statewide survey of watermelon production was conducted in 1998 and 1999 in Oklahoma. Data from the survey was used to classify production systems and management intensities among watermelon producers. Cluster analysis was used to identify the most closely associated of 24 abiotic and biotic variables affecting productivity. Five clusters were identified each year, or when data were pooled across years. Cluster I combined factors of grower experience, crop rotation, fertilization, and cultivation (mechanical weed control). Cluster II combined factors of cultivar ploidy, black plastic mulch, irrigation frequency, hoeing frequency, row arrangement, pollination, and planting method. Close distances among components implied that these two clusters had the strongest associations; indicating that two primary production systems exist. To measure management intensity of these production systems, a method was developed by: (1) partitioning four economic categories as machinery, labor, supply, and risk for each survey variable; (2) assigning weight scores of 0 or 1 to each category; and (3) summing the weight scores across economic categories for all factors involved in each production system. The most commonly used production system (>50%) consisted of Cluster I, which was considered of intermediate management intensity with scores ≥12 and ≤36. The production system considered as high management intensity with scores >36 was rarely used, but always combined components within Clusters I and II. This is the first attempt to describe complete production systems for watermelon in terms of analytical methods and measurements of crop management intensity.

Partitioning objects into closely related groups that have different states allows to understand the underlying structure in the data set treated. Different kinds of similarity measure with clustering algorithms are commonly used to find an optimal clustering or closely akin to original clustering. Using shrinkage-based and rank-based correlation coefficients, which are known to be robust, the recovery level of six chosen clustering algorithms is evaluated using Rand's C values. The recovery levels using weighted likelihood estimate of correlation coefficient are obtained and compared to the results from using those correlation coefficients in applying agglomerative clustering algorithms.

Principal coordinate analysis is a more powerful technique than principal component analysis to ensure identification on groups of objects if some conditions are satisfied. The results of using principal coordinates prior to cluster analysis were investigated. Three different methods of standardization were examined and compared with no standardization using both principal coordinates and principal components. The retrieval abilities of the known agglomerative clustering algorithms were improved by using principal coordinates. The results of applying principal coordinates based on the correlation coefficient instead of Euclidean distance prior to clustering algorithms were less sensitive to changes in noise.

Oklahoma Older Americans Act Nutrition Program participants' (n = 859) ability to shop, cook, and feed themselves was evaluated using factor analysis and logistic regression. Congregate participants who reported they were not able to shop, cook, and feed themselves had significantly lower "mobility," "financial management," and "financial security" factor scores; home-delivered participants had significantly lower "mobility," "living arrangement" and "financial security," and higher "social interaction" factor scores. For congregate meal participants the factors "mobility" and "financial management" and for home-delivered meal participants, the factors "mobility" and "social interaction" were significantly associated with reported ability to shop, cook, and feed themselves.

Clustering algorithms with different similarity measures are commonly used to find an optimal clustering or close to original clustering. The recovery level of using Euclidean distance and distances transformed from correlation coefficients is evaluated and compared using Rand's (1971) C statistic. The C values present how the resultant clustering is close to the original clustering. In simulation study, the recovery level is improved by applying the correlation coefficients between objects. Using the data set from Spellman et al. (1998), the recovery levels with different similarity measures are also presented. In general, the recovery level of true clusters was increased by using the correlation coefficients.

Two different formulations on the moments of Rand's C appear incompatible. The mean and variance of Rand's C statistic given by Fowlkes and Mallows (J. Amer Statist. Assoc. 78 (1983) 553) are special cases of the mean and variance of C given by DuBien and Warde (ASA proceedings of the social statistics section (1981) 309).

We present a multistage approach for estimating the abundance of stream fishes using geographic information systems (GIS) technology. Stream habitat types (i.e., channel units), classified in terms of their quality (optimal, suitable, or unsuitable) for a fish species, were used to stratify the stream for population sampling. Population abundance estimates and habitat quality were then used with the GIS to predict abundances in areas that were not sampled and to calculate an abundance estimate for the entire stream or stream segment. We present the basic method and illustrate its use with a case study of the leopard darter Percina pantherina from Big Eagle Creek in southeastern Oklahoma. Our method is flexible, accounts for variation in habitat quality and its influence on fish abundance, and incorporates GIS technology as an aid for quantitatively sampling large areas that are logistically difficult to sample.

AbstractThis article presents an algebraic analysis of agglomerative clustering method algorithms, which results in a graphic portrayal of these algorithms and a classification scheme for these algorithms based on the degree of distortion perpetrated on the object space by the algorithms in each group.

The randomized response technique is an effective survey method designed to elicit sensitive information while ensuring the privacy of the respondents. In this article, we present some new results on the randomization response model in situations wherein one or two response variables are assumed to follow a multinomial distribution. For a single sensitive question, we use the well-known Hopkins randomization device to derive estimates, both under the assumption of truthful and untruthful responses, and present a technique for making pairwise comparisons. When there are two sensitive questions of interest, we derive a Pearson product moment correlation estimator based on the multinomial model assumption. This estimator may be used to quantify the linear relationship between two variables when multinomial response data are observed according to a randomized-response protocol.

A new quantitative randomized response technique is presented in this paper. The proposed technique will use a Hopkins' randomizing device to derive a multinomial distribution for sensitive categories. After obtaining the observed estimates for sensitive category proportions which also include the random responses from the Hopkins' randomizing device, we derive the true estimates of the proportions for the sensitive categories in a situation where a model accounting for the respondent to lie is used. For contingency tables, we derive a Pearson product-moment correlation between two different sensitive questions.