BIOS 9131 – Advanced Statistical Theory for Biostatistics I

This course provides an advanced study of theoretical statistics. Topics include: an introduction probability and sample space, conditional probability and Bayes Theorem, probability distribution of a random variable, discrete and continuous random variables, functions of random variables, moments and moment generating functions, order statistics and their distributions, discrete distributions, continuous distributions, bivariate and multivariate normal distribution, modes of convergence, limiting moment generating functions, and the central limit theorems. 3 hour

BIOS 9130—Research Seminar in Biostatistics

This course is designed to provide the student with the current best practices in biostatistical consulting. Topics include: Identifying and constructing appropriate questions to ask clients regarding their consultation request, an overview of appropriate statistical methods and SAS software procedures to use for specific study designs and statistical analysis of collected data, directing a consultation appointment without faculty lead, conducting exploratory data analyses, conducting effective analyses based on appropriate statistical methods, conducting needed simulation (including Monte Carlo methods and Bootstrap methods) and providing oral and written communication of statistical findings. 3 credit house

Daily Walking and Life Expectancy of Elderly People in the Iowa 65+ Rural Health Study

The purpose of this paper is to investigate the hypothesis that outdoor daily walking, as an exercise, has an effect on the rate of mortality among those elderly people in the Iowa 65+ Rural Health Study (RHS). RHS is a prospective longitudinal cohort study of 8 years follow-up from 1981 to 1989. It consists of a random sample of 3,673 individuals (1,420 men and 2,253 women) aged 65 or older living in Washington and Iowa counties of the State of Iowa. Our analysis was conducted only on those non-institutional individuals who could without any help walk across a small room; this reduced the total number of individuals in the study to 2,717. Moreover, a total of 923 individuals died during the period of the study. The life histories of those individuals were obtained and divided into two cohorts; one containing 1,134 who exercise daily by walking and the other containing 1,583 who do not exercise daily by walking. The interviewers asked participants about 17 medical conditions, from which 13 are included in our study. We found that daily walking exercise is related inversely to total mortality before and after adjusting for the other factors in particular for age group and health conditions. We observed that hazard ratio (HR) of death was the highest among those individuals having a history of cancer (HR = 2.971) and history of stroke (HR = 2.127). However, individuals with a history of stroke in the “daily walking group” have HR = 0.856 and their risk of death were reduced by 81% compared to those in no “daily walking group.

Double Median Ranked Set Sample: Comparing To Other Double Ranked Samples For Mean And Ratio Estimators

Double median ranked set sample (DMRSS) and its properties for estimating the population mean, when the underlying distribution is assumed to be symmetric about its mean, are introduced. Also, the performance of DMRSS with respect to other ranked set samples and double ranked set samples, for estimating the population mean and ratio, is considered. Real data that consist of heights and diameters of 399 trees are used to illustrate the procedure. The analysis and simulation indicate that using DMRSS for estimating the population mean is more efficient than using the other ranked samples and double ranked samples schemes except in case of uniform distribution. Also, using double sampling schemes substantially increase the relative efficiency of ratio estimators relative to their counterpart schemes of one stage samples. Moreover, DMRSS is superior to other double sampling schemes for ratio estimation

Regression Estimator Using Double Ranked Set Sampling

The performance of a regression estimator based on the double ranked set sample (DRSS) scheme, introduced by Al-Saleh and Al-Kadiri (2000), is investigated when the mean of the auxiliary variable X is unknown. Our primary analysis and simulation indicates that using the DRSS regression estimator for estimating the population mean substantially increases relative efficiency compared to using regression estimator based on simple random sampling (SRS) or ranked set sampling (RSS) (Yu and Lam, 1997) regression estimator.  Moreover, the regression estimator using DRSS is also more efficient than the naïve estimators of the population mean using SRS, RSS (when the correlation coefficient is at least 0.4) and DRSS for high correlation coefficient (at least 0.91.) The theory is illustrated using a real data set of trees

A Test of Symmetry Based on the Kernel Kullback-Leibler Information with Application to Base Deficit Data

The assumption of the symmetry of the underlying distribution is important to many statistical inference and modeling procedures. This paper provides a test of symmetry using kernel density estimation and the Kullback-Leibler information. Based on simulation studies, the new test procedure outperforms other tests of symmetry found in the literature, including the Runs Test of Symmetry. We illustrate our new procedure using real data

A More Efficient Nonparametric Test of Symmetry Based on Overlapping Coefficient

In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit

Inference on Overlapping Coefficients in Two Exponential Populations

Three measures of overlap, namely Matusita’s measureρ , Morisita’s measure λ and Weitzman’s measure Δ are investigated in this article for two exponential populations with different means. It is well that the estimators of those measures of overlap are biased. The bias is of these estimators depends on the unknown overlap parameters. There are no closed-form, exact formulas, for those estimators variances or their exact sampling distributions. Monte Carlo evaluations are used to study the bias and precision of the proposed overlap measures. Bootstrap method and Taylor series approximation are used to construct confidence intervals for the overlap measures

Estimation Using Bivariate Extreme Ranked Set Sampling With Application To The Bivariate Normal Distribution

In this article, the procedure of bivariate extreme ranked set sampling (BVERSS) is introduced and investigated as a procedure of obtaining more accurate samples for estimating the parameters of bivariate populations. This procedure takes its strength from the advantages of bivariate ranked set sampling (BVRSS) over the usual ranked set sampling in dealing with two characteristics simultaneously, and the advantages of extreme ranked set sampling (ERSS) over usual RSS in reducing the ranking errors and hence in being more applicable. The BVERSS procedure will be applied to the case of the parameters of the bivariate normal distributions. Illustration using real data is also provided

Status of Seaweed K. alvarezii Cultivation Sustainability as a Strategic Direction for Seaweed Management in Baubau City, Southeast Sulawesi

This study aims to examine its sustainability status. This study used survey techniques and interviews with seaweed cultivators to collect data. Sustainability data on seaweed cultivation include social, economic, and ecological aspects. The Rapseaweed approach (Rapid Appraisal for Seaweed) has been modified from Rapfish (Rapid Appraisal for Fisheries) to evaluate the sustainability status of seaweed in a multidisciplinary manner. Analysis of the sustainability of K. alvarezii seaweed cultivation using the MDS method. The Rapseaweed analysis reveals that the ecological sustainability index value is 57.76, and the availability of seeds is the most sensitive attribute, with a change in root mean square RMS value of 4.59. Seaweed marketing is the most sensitive attribute, with a change in root mean square RMS value of 12.96, and the economic dimension index value is 65.62. The cultivator's habits have the highest index value of 69.75% for the social dimension, with a root mean square RMS change value of 10.47. All dimensions are considered to be "sufficiently sustainable" by these index values. In the three dimensions, each RMS value indicates that there are sensitive attributes whose existence is suppressed or paid attention to. To obtain a strategic direction for the management of seaweed cultivation in Baubau City based on the RMS value, which has been ranked from highest to lowest, a seaweed management strategy for related stakeholders, namely the local government, the industrial sector, and the cultivating community, namely; strengthening coastal communities' capacity to maximize seaweed cultivation activities, ensuring market availability and price stability, and increasing production at seaweed cultivation centre locationsDimensi ekologi, ekonomi, dan sosial dari pembangunan berkelanjutan diperlukan untuk mengukur status keberlanjutan kegiatan budidaya rumput laut di kota pesisir Baubau untuk arah strategi pengelolaan. Akibatnya, strategi manajemen diperlukan untuk memastikan kelangsungan jangka panjang dari operasi budidaya rumput laut. Sebagai panduan strategi pengelolaan budidaya rumput laut K. alvarezii di pesisir Kota Baubau Provinsi Sulawesi Tenggara, penelitian ini bertujuan untuk mengkaji status kelestariannya. Penelitian ini menggunakan teknik survei dan wawancara dengan pembudidaya rumput laut untuk mengumpulkan data. Data keberlanjutan budidaya rumput laut meliputi aspek sosial, ekonomi, dan ekologi. Pendekatan Rapseaweed (Penilaian Cepat untuk Rumput Laut) telah dimodifikasi dari Rapfish (Penilaian Cepat untuk Perikanan) untuk mengevaluasi status keberlanjutan rumput laut secara multidisiplin. Analisis keberlanjutan budidaya rumput laut K. alvarezii menggunakan metode MDS. Analisis Rapseaweed menunjukkan bahwa nilai indeks keberlanjutan ekologi adalah 57,76, dan ketersediaan benih adalah atribut yang paling sensitif, dengan perubahan nilai RMS root mean square sebesar 4,59. Pemasaran rumput laut merupakan atribut yang paling sensitif, dengan perubahan nilai RMS root mean square sebesar 12,96, dan nilai indeks dimensi ekonomi sebesar 65,62. Kebiasaan pembudidaya memiliki nilai indeks tertinggi sebesar 69,75% untuk dimensi sosial, dengan nilai perubahan RMS root mean square sebesar 10,47. Semua dimensi dianggap "cukup berkelanjutan" dengan nilai indeks ini. Pada ketiga dimensi tersebut, setiap nilai RMS menunjukkan adanya atribut-atribut sensitif yang keberadaannya ditekan atau diperhatikan. Untuk mendapatkan arahan strategis pengelolaan budidaya rumput laut di Kota Baubau berdasarkan nilai RMS yang telah diurutkan dari tertinggi hingga terendah, strategi pengelolaan rumput laut bagi stakeholder terkait yaitu pemerintah daerah, dunia industri, dan masyarakat pembudidaya , yaitu; penguatan kapasitas masyarakat pesisir untuk memaksimalkan kegiatan budidaya rumput laut, memastikan ketersediaan pasar dan stabilitas harga, serta meningkatkan produksi di lokasi sentra budidaya rumput laut. &nbsp