Statistics and Probability Commons^™

A Statistical Approach To Characterize And Detect Degradation Within The Barabasi-Albert Network, Mohd-Fairul Mohd-Zaid

Theses and Dissertations

Social Network Analysis (SNA) is widely used by the intelligence community when analyzing the relationships between individuals within groups of interest. Hence, any tools that can be quantitatively shown to help improve the analyses are advantageous for the intelligence community. To date, there have been no methods developed to characterize a real world network as a Barabasi-Albert network which is a type of network with properties contained in many real-world networks. In this research, two newly developed statistical tests using the degree distribution and the L-moments of the degree distribution are proposed with application to classifying networks and detecting degradation …

Model Averaged Double Robust Estimation, Matthew Cefalu, Francesca Dominici, Nils D. Arvold Md, Giovanni Parmigiani

Harvard University Biostatistics Working Paper Series

Existing methods in causal inference do not account for the uncertainty in the selection of confounders. We propose a new class of estimators for the average causal effect, the model averaged double robust estimators, that formally account for model uncertainty in both the propensity score and outcome model through the use of Bayesian model averaging. These estimators build on the desirable double robustness property by only requiring the true propensity score model or the true outcome model be within a specified class of models to maintain consistency. We provide asymptotic results and conduct a large scale simulation study that indicates …

Optimal Design Of Low-Density Snp Arrays For Genomic Prediction: Algorithm And Applications, Xiao-Lin Wu, Jiaqi Xu, Guofei Feng, George R. Wiggans, Jeremy F. Taylor, Jun He, Changsong Qian, Jiansheng Qiu, Barry Simpson, Jeremy Walker, Stewart Bauck

Department of Statistics: Faculty Publications

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. …

The Subject Librarian Newsletter, Statistics, Fall 2016, Patti Mccall

Libraries' Newsletters

No abstract provided.

Another Generalized Transmuted Family Of Distributions: Properties And Applications, Faton Merovci, Morad Alizadeh, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

We introduce and study general mathematical properties of a new generator of continuous distributions with two extra parameters called the Another generalized transmuted family of distributions. We present some special models. We investigate the asymptotes and shapes. The new density function can be expressed as a linear combination of exponentiated densities based on the same baseline distribution. We obtain explicit expressions for the ordinary and incomplete moments and generating functions, Bonferroni and Lorenz curves, asymptotic distribution of the extreme values, Shannon and Renyi entropies and order statistics, which hold for any baseline model, certain characterisations are presented. Further, we …

Ultracoproduct Continua And Their Regular Subcontinua, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

We continue our study of ultracoproduct continua, focusing on the role played by the regular subcontinua—those subcontinua which are themselves ultracoproducts. Regular subcontinua help us in the analysis of intervals, composants, and noncut points of ultracoproduct continua. Also, by identifying two points when they are contained in the same regular subcontinua, we naturally generalize the partition of a standard subcontinuum of ℍ * into its layers.

Probabilistic Methods In Information Theory, Erik W. Pachas

Electronic Theses, Projects, and Dissertations

Given a probability space, we analyze the uncertainty, that is, the amount of information of a finite system, by studying the entropy of the system. We also extend the concept of entropy to a dynamical system by introducing a measure preserving transformation on a probability space. After showing some theorems and applications of entropy theory, we study the concept of ergodicity, which helps us to further analyze the information of the system.

Variation Of Driving Skill Among Elderly Drivers Compared To Young Drivers In Japan, Indri Hapsari Susilowati, Akira Yasukouchi

Kesmas

Penelitian ini menganalisis kemampuan mengemudi pada pengemudi lanjut usia (lansia) dibandingkan dengan usia muda di Jepang dan melihat keterampilan mengemudi yang kurang sehingga dapat memengaruhi risiko kecelakaan di jalan raya. Subjek penelitian adalah pengemudi usia muda dan lansia, terdiri dari 10 mahasiswa (20 - 24 tahun) dan 25 pengemudi lansia (14 laki-laki dan 11 perempuan) berasal dari The Silver Menpower Center, organisasi bagi lansia > 60 tahun. Pengemudi lansia dibagi menjadi dua kelompok, yaitu lansia 1 berusia 60 - 65 tahun (10 orang) dan lansia 2 berusia > 65 tahun (15 orang). Kemampuan mengemudi dievaluasi dengan simulator permainan mengemudi dalam laboratorium. Analisis …

Rural-Based Health Promotion Model For Pregnant Women In Banyumas District, Elviera Gamelia, Dian Anandari, Dyah Umiyarni Purnamasari

Kesmas

Penelitian sebelumnya menunjukkan bahwa pengetahuan pelayanan prenatal di wilayah pedesaan masih rendah yang berdampak pada perilaku buruk sehingga mengembangkan model promosi kesehatan dibutuhkan untuk meningkatkan pengetahuan prenatal, sikap dan perilaku. Penelitian ini bertujuan untuk mengembangkan model promosi kesehatan pelayanan prenatal di wilayah pedesaan berdasarkan penilaian kebutuhan. Penelitian dilakukan pada Juni 2015 dengan pendekatan kualitatif melibatkan 16 ibu hamil pertama di trimester ketiga dengan kehamilan berisiko sebagai informan kunci dan 16 anggota keluarga yang tinggal bersama ibu hamil dan mengetahui kehidupan sehari-harinya, 27 bidan dan 3 tokoh agama sebagai informan tambahan. Teknik pengumpulan data adalah wawancara mendalam dan observasi untuk ibu …

Well Water Consumed And Urolithiasis In Gedangsari Subdistrict, Yogyakarta, Sulistyawati Sulistyawati, Fardhiasih Dwi Astuti, Ruri Trisasri, Asep Rustiawan

Kesmas

Tanah di wilayah Kecamatan Gedangsari mengandung batuan kapur. Masyarakat di daerah ini banyak yang mengkonsumsi air minum dari sumur gali yang mengandung kadar kalsium tinggi, dan banyak yang menderita urolithiasis. Penelitian ini bertujuan untuk mendapatkan gambaran distribusi kalsium atau Ca(OH)2 pada air sumur dan menjelaskan hubungannya dengan kejadian urolithiasis. Penelitian dilakukan di Kecamatan Gedangsari, Kabupaten Gunungkidul selama Juli sampai November 2013. Penelitian dilakukan secara potong lintang dengan konfirmasi uji titrasi di laboratorium. Sejumlah 94 sampel sumur dipilih secara acak dari populasi 3.849 sumur. Kriteria pemilihan sampel adalah sumur gali yang telah digunakan untuk minum oleh penduduk berusia lebih dari 30 …

Identification Of Pathogenic Leptospira In Rat And Shrew Populations Using Rpob Gene And Its Spatial Distribution In Boyolali District, Dyah Widiastuti, Zumrotus Sholichah, Agustiningsih Agustiningsih, Nastiti Wijayanti

Kesmas

Leptospirosis merupakan masalah kesehatan di Indonesia. Hingga April 2014, dilaporkan kasus leptospirosis yang ditularkan oleh tikus di Kabupaten Boyolali dengan angka kematian 83,3%. Genus Leptospira terdiri dari ratusan serovar dan tipe genetik yang hidup di pelbagai jenis habitat. Pengelompokan spesies Leptospira berdasarkan gen rpoB dapat digunakan karena tingkat polimorfisme gen tersebut tinggi. Penelitian ini bertujuan untuk mengidentifikasi serovar bakteri Leptospira pada populasi tikus di Kabupaten Boyolali menggunakan analisis hubungan kekerabatan didasarkan pada polimorfisme gen rpoB dan menggambarkan distribusi spasial tikus positif Leptospira di Kabupaten Boyolali. Penelitian potong lintang dilaksanakan pada bulan April 2014 di Desa Sindon Kecamatan Ngemplak dan Desa …

Measles Immunization And Vitamin A For Prevention Of Pneumonia In Indonesia, Ratno Widoyo

Kesmas

Pneumonia merupakan penyebab kematian tertinggi pada anak di Indonesia setelah diare. Pengendalian pneumonia dapat dilakukan dengan peningkatan cakupan imunisasi campak, pertusis, Streptococcus pneumoniae (Spn), dan Haemophilus influenzae b (Hib). Vaksin Spn dan Hib belum masuk ke dalam kategori imunisasi wajib di Indonesia. Vaksin campak lebih memiliki pengaruh langsung terhadap pneumonia dibandingkan dengan vaksin pertusis. Pemberian imunisasi yang disertai pemberian vitamin A akan meningkatkan titer antibodi pada anak. Penelitian ini bertujuan untuk mengetahui pengaruh pemberian imunisasi campak dan vitamin A terhadap kejadian pneumonia. Metode penelitian adalah potong lintang dengan menggunakan 13.062 data anak yang terdapat pada data Survei Demografi dan Kesehatan …

Role Of Hearth Program With Undernutrition Incidence Among Toddlers In Tangerang City, Gizella Gizella, Dany Hilmanto, Dedi Rachmadi

Kesmas

Kelompok yang rentan terhadap gizi kurang adalah balita. World Health Organization (WHO) menyatakan kematian anak bawah lima tahun (balita) akibat gizi kurang sebesar 54% pada tahun 2002. Di Indonesia, prevalensinya mengalami peningkatan dari 17,9% pada tahun 2010 menjadi 19,6% pada tahun 2013. Di Kota Tangerang, terdapat 1,43% balita yang mengalami gizi buruk pada tahun 2013. Penelitian ini bertujuan untuk membuktikan secara valid hubungan antara Program Pos Gizi yang meliputi perilaku pemberian makan, perilaku kebersihan balita, perilaku mencari pelayanan kesehatan dan perilaku pengasuhan balita dengan kejadian gizi kurang pada balita. Penelitian ini merupakan penelitian kuantitatif, potong lintang, menggunakan data primer serta …

Good Corporate Governance Implementation And Performance Of Civil Servant, Muhammad Hasan, Dumilah Ayuningtyas, Misnaniarti Misnaniarti

Kesmas

Dalam rangka mencapai visi dan misi, setiap rumah sakit harus menjalankan tata kelola perusahaan yang baik (Good Corporate Governance/GCG). Penerapan GCG sendiri bertujuan untuk meningkatkan kinerja pegawai secara optimal, yang akhirnya akan meningkatkan kinerja organisasi. Penelitian ini bertujuan untuk menganalisis hubungan penerapan prinsip-prinsip GCG terhadap kinerja pegawai negeri sipil (PNS) Rumah Sakit Umum Lapangan Natuna Kabupaten Kepulauan Anambas. Jenis penelitian ini adalah deskriptif analitik dengan desain potong lintang pada 56 PNS. Pengumpulan data dilakukan pada tahun 2012 dengan kuesioner terstruktur. Digunakan analisis dengan uji kai kuadrat dan regresi logistik, dan untuk penyederhanaan model dilakukan eliminasi terhadap faktor perancu dengan menggunakan …

Environmental, Behavioral Factors And Filariasis Incidence In Bintan District, Riau Islands Province, Zainul Ikhwan, Lucky Herawati, Suharti Suharti

Kesmas

Tingkat mikrofilaria filariasis di Kabupaten Bintan masih tinggi, khususnya di Kecamatan Teluk Bintan, Teluk Sebong, dan Sri Kuala Lobam. Penelitian ini bertujuan untuk mengetahui hubungan faktor risiko lingkungan (faktor fisik, biologi, kimia, sosial budaya, ekonomi) dan faktor perilaku dengan kejadian filariasis. Jenis penelitian observasional analitik yang dilakukan pada Mei – September 2015 dengan desain kasus kontrol, yang terdiri dari jumlah kasus 33 orang penderita filariasis dan kontrol 65 orang bukan penderita filariasis dengan teknik cluster sampling. Populasi penelitian adalah masyarakat di Kabupaten Bintan. Data yang diperoleh dianalisis menggunakan uji kai kuadrat dan regresi logistik. Hasil menunjukkan adanya hubungan pengetahuan (nilai …

Bayesian Peer Calibration With Application To Alcohol Use, Miles Q. Ott, Joseph W. Hogan, Krista J. Gile, Crystal Linkletter, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Peers are often able to provide important additional information to supplement self-reported behavioral measures. The study motivating this work collected data on alcohol in a social network formed by college students living in a freshman dormitory. By using two imperfect sources of information (self-reported and peer-reported alcohol consumption), rather than solely self-reports or peer-reports, we are able to gain insight into alcohol consumption on both the population and the individual level, as well as information on the discrepancy of individual peer-reports. We develop a novel Bayesian comparative calibration model for continuous, count and binary outcomes that uses covariate information to …

Distance-Based Analysis Of Variance For Brain Connectivity, Russell T. Shinohara, Haochang Shou, Marco Carone, Robert Schultz, Birkan Tunc, Drew Parker, Ragini Verma

UPenn Biostatistics Working Papers

The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that may …

Diffuse Optical Measurements Of Head And Neck Tumor Hemodynamics For Early Prediction Of Chemoradiation Therapy Outcomes, Lixin Dong, Mahesh Kudrimoti, Daniel Irwin, Li Chen, Sameera Kumar, Yu Shang, Chong Huang, Ellis L. Johnson, Scott D. Stevens, Brent J. Shelton, Guoqiang Yu

Biomedical Engineering Faculty Publications

This study used a hybrid near-infrared diffuse optical instrument to monitor tumor hemodynamic responses to chemoradiation therapy for early prediction of treatment outcomes in patients with head and neck cancer. Forty-seven patients were measured once per week to evaluate the hemodynamic status of clinically involved cervical lymph nodes as surrogates for the primary tumor response. Patients were classified into two groups: complete response (CR) (n = 29) and incomplete response (IR) (n = 18). Tumor hemodynamic responses were found to be associated with clinical outcomes (CR/IR), wherein the associations differed depending on human papillomavirus (HPV-16) status. In HPV-16 …

The Use Of Permutation Tests For The Analysis Of Parallel And Stepped-Wedge Cluster Randomized Trials, Rui Wang, Victor Degruttola

Harvard University Biostatistics Working Paper Series

We investigate the use of permutation tests for the analysis of parallel and stepped-wedge cluster randomized trials. Permutation tests for parallel designs with exponential family endpoints have been extensively studied. The optimal permutation tests developed for exponential family alternatives require information on intraclass correlation, a quantity not yet defined for time-to-event endpoints. Therefore, it is unclear how efficient permutation tests can be constructed for cluster-randomized trials with such endpoints. We consider a class of test statistics formed by a weighted average of pair-specific treatment effect estimates and offer practical guidance on the choice of weights to improve efficiency. We apply …

Improving Precision By Adjusting For Baseline Variables In Randomized Trials With Binary Outcomes, Without Regression Model Assumptions, Jon Arni Steingrimsson, Daniel F. Hanley, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

In randomized clinical trials with baseline variables that are prognostic for the primary outcome, there is potential to improve precision and reduce sample size by appropriately adjusting for these variables. A major challenge is that there are multiple statistical methods to adjust for baseline variables, but little guidance on which is best to use in a given context. The choice of method can have important consequences. For example, one commonly used method leads to uninterpretable estimates if there is any treatment effect heterogeneity, which would jeopardize the validity of trial conclusions. We give practical guidance on how to avoid this …

Left And Right Ventricular Dyssynchrony And Strains From Cardiovascular Magnetic Resonance Feature Tracking Do Not Predict Deterioration Of Ventricular Function In Patients With Repaired Tetralogy Of Fallot, Linyuan Jing, Gregory J. Wehner, Jonathan D. Suever, Richard Charnigo, Sudad Alhadad, Evan Stearns, Dimitri Mojsejenko, Christopher M. Haggerty, Kelsey Hickey, Anne Marie Valente, Tal Geva, Andrew J. Powell, Brandon K. Fornwalt

Saha Cardiovascular Research Center Faculty Publications

Background: Patients with repaired tetralogy of Fallot (rTOF) suffer from progressive ventricular dysfunction decades after their surgical repair. We hypothesized that measures of ventricular strain and dyssynchrony would predict deterioration of ventricular function in patients with rTOF.

Methods: A database search identified all patients at a single institution with rTOF who underwent cardiovascular magnetic resonance (CMR) at least twice, > 6 months apart, without intervening surgical or catheter procedures. Seven primary predictors were derived from the first CMR using a custom feature tracking algorithm: left (LV), right (RV) and inter-ventricular dyssynchrony, LV and RV peak global circumferential strains, and LV and …

A Bayesian Framework For The Classification Of Microbial Gene Activity States, Craig Disselkoen, Brian Greco, Kaitlyn Cook, Kristin Koch, Reginald Lerebours, Chase Viss, Joshua Cape, Elizabeth Held, Yonatan Ashenafi, Karen Fischer, Allyson Acosta, Mark Cunningham, Aaron A. Best, Matthew Dejongh, Nathan Tintle

Statistical and Data Sciences: Faculty Publications

Numerous methods for classifying gene activity states based on gene expression data have been proposed for use in downstream applications, such as incorporating transcriptomics data into metabolic models in order to improve resulting flux predictions. These methods often attempt to classify gene activity for each gene in each experimental condition as belonging to one of two states: active (the gene product is part of an active cellular mechanism) or inactive (the cellular mechanism is not active). These existing methods of classifying gene activity states suffer from multiple limitations, including enforcing unrealistic constraints on the overall proportions of active and inactive …

Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae

The Summer Undergraduate Research Fellowship (SURF) Symposium

Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …

Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis

The Summer Undergraduate Research Fellowship (SURF) Symposium

Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …

Mediation Analysis For A Survival Outcome With Time-Varying Exposures, Mediators, And Confounders, Sheng-Hsuan Lin, Jessica G. Young, Roger Logan, Tyler J. Vanderweele

Harvard University Biostatistics Working Paper Series

We propose an approach to conduct mediation analysis for survival data with time-varying exposures, mediators, and confounders. We identify certain interventional direct and indirect effects through a survival mediational g-formula and describe the required assumptions. We also provide a feasible parametric approach along with an algorithm and software to estimate these effects. We apply this method to analyze the Framingham Heart Study data to investigate the causal mechanism of smoking on mortality through coronary artery disease. The risk ratio of smoking 30 cigarettes per day for ten years compared with no smoking on mortality is 2.34 (95 % CI = …

Assessing The Association Between Quantitative Maturity And Student Performance In Simulation-Based And Non-Simulation Based Introductory Statistics, Nathan L. Tintle

Faculty Work Comprehensive List

The recent simulation-based inference movement in algebra-based introductory statistics courses has provided preliminary evidence of improved student conceptual understanding and retention of key statistical concepts. However, little is known about whether these positive effects in courses using simulation-based inference are preferentially distributed across different types of students. Recent studies investigating predictors of student performance in traditional, algebra-based introductory statistics courses (Stat 101) have focused primarily on mathematical achievement or competencies in high school and early college. Little consideration has been given to how prior experience and competency with statistical thinking may be associated with student performance in college-level courses. In …

Oscillation Criteria For Third-Order Functional Differential Equations With Damping, Martin Bohner, Said R. Grace, Irena Jadlovska

Mathematics and Statistics Faculty Research & Creative Works

This paper is a continuation of the recent study by Bohner et al [9] on oscillation properties of nonlinear third order functional differential equation under the assumption that the second order differential equation is nonoscillatory. We consider both the delayed and advanced case of the studied equation. The presented results correct and extend earlier ones. Several illustrative examples are included.

Sensitivity Of Trial Performance To Delay Outcomes, Accrual Rates, And Prognostic Variables Based On A Simulated Randomized Trial With Adaptive Enrichment, Tiachen Qian, Elizabeth Colantuoni, Aaron Fisher, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

Adaptive enrichment designs involve rules for restricting enrollment to a subset of the population during the course of an ongoing trial. This can be used to target those who benefit from the experimental treatment. To leverage prognostic information in baseline variables and short-term outcomes, we use a semiparametric, locally efficient estimator, and investigate its strengths and limitations compared to standard estimators. Through simulation studies, we assess how sensitive the trial performance (Type I error, power, expected sample size, trial duration) is to different design characteristics. Our simulation distributions mimic features of data from the Alzheimer’s Disease Neuroimaging Initiative, and involve …

The Impact Of Patient Navigation On The Delivery Of Diagnostic Breast Cancer Care In The National Patient Navigation Research Program: A Prospective Meta-Analysis., Tracy A Battaglia, Julie S Darnell, Naomi Ko, Fred Snyder, Electra D Paskett, Kristen J Wells, Elizabeth M Whitley, Jennifer J Griggs, Anand Karnad, Heather Young, Victoria Warren-Mears, Melissa A Simon, Elizabeth Calhoun

Epidemiology Faculty Publications

Patient navigation is emerging as a standard in breast cancer care delivery, yet multi-site data on the impact of navigation at reducing delays along the continuum of care are lacking. The purpose of this study was to determine the effect of navigation on reaching diagnostic resolution at specific time points after an abnormal breast cancer screening test among a national sample. A prospective meta-analysis estimated the adjusted odds of achieving timely diagnostic resolution at 60, 180, and 365 days. Exploratory analyses were conducted on the pooled sample to identify which groups had the most benefit from navigation. Clinics from six …

Modeling Internet Traffic Generations Based On Users And Activities For Telecommunication Applications, Sara Stoudt, Pamela Badian-Pessot, Blanche Ngo Mahop, Erika Earley, Jordan Menter, Yadira Flores, Danielle Williams, Weijia Zhang, Liza Maharjan, Yixin Bao, Laura Rosenbauer, Van Nguyen, Veena Mendiratta, Nessy Tania

Mathematics Sciences: Faculty Publications

A traffic generation model is a stochastic model of the data flow in a communication network. These models are useful during the development of telecommunication technologies and for analyzing the performance and capacity of various protocols, algorithms, and network topologies. We present here two modeling approaches for simulating internet traffic. In our models, we simulate the length and interarrival times of individual packets, the discrete unit of data transfer over the internet. Our first modeling approach is based on fitting data to known theoretical distributions. The second method utilizes empirical copulae and is completely data driven. Our models were based …