CONTACT DETAILS. Cape Town BIOSTATISTICIANS. Esmé Jordaan Specialist Statistician Tel:
|
|
|
- Neal Griffith
- 6 years ago
- Views:
Transcription
1 CONTACT DETAILS Cape Town Esmé Jordaan Specialist Tel: Interest areas: Finite Mixture models with a focus on Latent Class Models; Growth mixture modelling with normal and non-normal data; (Pragmatic) Randomised controlled trials; Structural Equations modelling including Measurement models such as the Rasch model; Agreement for categorical data and loglinear modeling in contingency tables; Clinical research areas include sport science and psychiatric research. Ria Laubscher Senior ria.laubscher@mrc.ac.za Tel: Interest areas: Mortality Profiles; Database Management; Nutritional Data Analyses Graphical display of data Sonja Swanevelder Senior sonja.swanevelder@mrc.ac.za Tel: Interest areas: Medical & Sport Biostatistics with special interest in Randomised Controlled Trials, Correlated data, Regression analyses and Survival Analyses. Nomonde Gwebushe nomonde.gwebushe@mrc.ac.za Tel: Interest areas: Clinical and cluster randomised controlled trials; Application of general linear models and linear mixed models; Logistic Regression Mikateko Cynthia Mazinu Junior mikateko.mazinu@mrc.ac.za Tel: Interest areas: Logistic regression modelling, clinical and randomised controlled trails.
2 Prof Carl Lombard Consultant Tel: Interest areas: Analysis and design of clinical trials especially cluster randomized trials. Statistical aspects of data and safety monitoring of clinical trials. Analysis of correlated data with respect to recurrent events, longitudinal design and the joint modeling of responses and survey analysis. Dr Averalda Van Graan Manager of SAFOODS and dietary intake assessment Tel: Joelaine Chetty Research Dietitian, Food Compilation RD (SA) MPH Tel: Interested Areas: Food composition database management and maintenance; food compilation software development; food composition website maintenance; recipe calculation methodology; networking with food industry and food labelling assistance; public health nutrition in lifecycle; nutrition advocacy and food composition training. Malory Jumat Chief Research Technologist - Food Compilation (MSc Nutrition) malory.links@mrc.ac.za Tel: Interest areas: Food composition database management and maintenance; food compilation software development; food composition training, food quantity estimations, chemical analysis of food, analytical methodology, photochemistry and health, application development
3 ADMINISTRATION Jessica Petersen Senior Officer (Secretary) P O Box 19070, Tygerberg, 7505, South Africa Tel: Fax: Jessica.petersen@mrc.ac.za Amanda Fourie Senior Encoder amanda.fourie@mrc.ac.za Tel:
4 Pretoria Prof Samuel OM Manda Acting Director Tel: Interest areas: Methodological research: Bayesian and nonparametric statistics; joint modelling of longitudinal and recurrent-events data and multivariate spatial statistics. Application research: Maternal and child health outcomes in Africa; TB, HIV/AIDS and vascular disease outcomes; and mortality data in South Africa and the sub-saharan Africa. Dr Steve Olorunju Specialist Tel: Interest areas: Experimental Designs: Clinical and Cluster Randomized Trials; Analysis of Complex Surveys; Environmental Health; Drug trials, Family Health, Drug Use and abuse; Lecturing and Supervision of students. Charl Janse Van Rensburg Tel: Interest areas: Utilising Big Data in healthcare; Bayesian and nonparametric statistics; bioinformatics; multilevel modelling. Tshifhiwa M Nkwenika Junior Tshifhiwa.nkwenika@mrc.ac.za Tel: Interest areas: Logistic regression and Discriminant analysis modelling, clinical randomized trails. ADMINISTRATION Emily Gomes Chief Officer emily.gomes@mrc.ac.za Tel:
5 Durban Tarylee Reddy Senior Tel: Interest areas: HIV/AIDS Surveys; multistate Markov models, joint modelling of longitudinal and time to event data, missing data analysis Natashia Morris Research Support Manager: GIS Tel: Interest areas: Spatial analysis, mapping, spatial statistics, surveillance, decision support, monitoring and evaluation of public health interventions, health systems optimisation using geospatial tools and techniques, free and open source software for geospatial application, socio-demographic analysis, mobile device technologies. Yusentha Balakrishna Tel: Interest areas: Nutritional data analysis, meta-analysis and systematic reviews, multivariate analysis, incidence estimation. Nada Abdelatif Tel: ADMINISTRATION Thabisile Mvuyana Data Encoder Tel:
Prerequisite: STATS 7 or STATS 8 or AP90 or (STATS 120A and STATS 120B and STATS 120C). AP90 with a minimum score of 3
University of California, Irvine 2017-2018 1 Statistics (STATS) Courses STATS 5. Seminar in Data Science. 1 Unit. An introduction to the field of Data Science; intended for entering freshman and transfers.
Core Courses for Students Who Enrolled Prior to Fall 2018
Biostatistics and Applied Data Analysis Students must take one of the following two sequences: Sequence 1 Biostatistics and Data Analysis I (PHP 2507) This course, the first in a year long, two-course
2018 PAA Short Course on Bayesian Small Area Estimation using Complex Data Introduction and Overview
2018 PAA Short Course on Bayesian Small Area Estimation using Complex Data Introduction and Overview Sam Clark 1, Zehang Richard Li 2, Jon Wakefield 2,3 1 Department of Sociology, Ohio State University,
GRADUATE CERTIFICATE PROGRAM
GRADUATE CERTIFICATE PROGRAM GEOGRAPHIC INFORMATION SCIENCES Department of Geography University of North Carolina Chapel Hill Conghe Song, Director csong @email.unc.edu 919-843-4764 (voice) 919-962-1537
WHO lunchtime seminar Mapping child growth failure in Africa between 2000 and Professor Simon I. Hay March 12, 2018
WHO lunchtime seminar Mapping child growth failure in Africa between 2000 and 2015 Professor Simon I. Hay March 12, 2018 Outline Local Burden of Disease (LBD) at IHME Child growth failure From global to
STATISTICS FACULTY COURSES UNDERGRADUATE GRADUATE. Explanation of Course Numbers. Bachelor's program. Minor. Master's programs.
STATISTICS Statistics is one of the natural, mathematical, and biomedical sciences programs in the Columbian College of Arts and Sciences. The curriculum emphasizes the important role of statistics as
GeoHealth Applications Platform ESRI Health GIS Conference 2013
GeoHealth Applications Platform ESRI Health GIS Conference 2013 Authors Thomas A. Horan, Ph.D. Professor, CISAT Director April Moreno Health GeoInformatics Ph.D. Student Brian N. Hilton, Ph.D. Clinical
Estimating Optimal Dynamic Treatment Regimes from Clustered Data
Estimating Optimal Dynamic Treatment Regimes from Clustered Data Bibhas Chakraborty Department of Biostatistics, Columbia University bc2425@columbia.edu Society for Clinical Trials Annual Meetings Boston,
Richard N. Jones, Sc.D. HSPH Kresge G2 October 5, 2011
Harvard Catalyst Biostatistical Seminar Neuropsychological Proles in Alzheimer's Disease and Cerebral Infarction: A Longitudinal MIMIC Model An Overview of Structural Equation Modeling using Mplus Richard
ECLT 5810 Linear Regression and Logistic Regression for Classification. Prof. Wai Lam
ECLT 5810 Linear Regression and Logistic Regression for Classification Prof. Wai Lam Linear Regression Models Least Squares Input vectors is an attribute / feature / predictor (independent variable) The
Advising on Research Methods: A consultant's companion. Herman J. Ader Gideon J. Mellenbergh with contributions by David J. Hand
Advising on Research Methods: A consultant's companion Herman J. Ader Gideon J. Mellenbergh with contributions by David J. Hand Contents Preface 13 I Preliminaries 19 1 Giving advice on research methods
Division of Pharmacoepidemiology And Pharmacoeconomics Technical Report Series
Division of Pharmacoepidemiology And Pharmacoeconomics Technical Report Series Year: 2013 #006 The Expected Value of Information in Prospective Drug Safety Monitoring Jessica M. Franklin a, Amanda R. Patrick
Contents. Part I: Fundamentals of Bayesian Inference 1
Contents Preface xiii Part I: Fundamentals of Bayesian Inference 1 1 Probability and inference 3 1.1 The three steps of Bayesian data analysis 3 1.2 General notation for statistical inference 4 1.3 Bayesian
OUTBREAK INVESTIGATION AND SPATIAL ANALYSIS OF SURVEILLANCE DATA: CLUSTER DATA ANALYSIS. Preliminary Programme / Draft_2. Serbia, Mai 2013
OUTBREAK INVESTIGATION AND SPATIAL ANALYSIS OF SURVEILLANCE DATA: CLUSTER DATA ANALYSIS Preliminary Programme / Draft_2 Serbia, 20-24 Mai 2013 1. Course presentation Outbreak investigation is one of the
STATISTICS-STAT (STAT)
Statistics-STAT (STAT) 1 STATISTICS-STAT (STAT) Courses STAT 158 Introduction to R Programming Credit: 1 (1-0-0) Programming using the R Project for the Statistical Computing. Data objects, for loops,
THE DATA REVOLUTION HAS BEGUN On the front lines with geospatial data and tools
THE DATA REVOLUTION HAS BEGUN On the front lines with geospatial data and tools Slidedoc of presentation for MEASURE Evaluation End of Project Meeting Washington DC May 22, 2014 John Spencer Geospatial
COMMISSION ON ACCREDITATION 2011 ANNUAL REPORT ONLINE
COMMISSION ON ACCREDITATION 2011 ANNUAL REPORT ONLINE SUMMARY DATA: POSTDOCTORAL PROGRAMS ^Clicking a table title will automatically direct you to that table in this document *Programs that combine two
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (June, 2017)
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (June, 2017) Report Contents: Vacancy Report Summary of Hiring Status (Vacancy rate over 10%) 1) Total hospital vacancies
FLORIDA COLLEGE SYSTEM VOCATIONAL PROGRAMS AGGREGATED OUTCOME DATA
FLORIDA COLLEGE SYSTEM VOCATIONAL PROGRAMS AGGREGATED OUTCOME DATA 2014-15 PSVC Degree Completers FETPIP FOLLOW-UP OUTCOMES TOTAL FREQ = number of individuals reported for follow-up to FETPIP. # FOUND
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (April, 2018)
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (April, 2018) Report Contents: Report Summary of Hiring Status ( rate over 10%) 1) Total hospital vacancy rate continue
Long Island Breast Cancer Study and the GIS-H (Health)
Long Island Breast Cancer Study and the GIS-H (Health) Edward J. Trapido, Sc.D. Associate Director Epidemiology and Genetics Research Program, DCCPS/NCI COMPREHENSIVE APPROACHES TO CANCER CONTROL September,
LEHMAN COLLEGE OF THE CITY UNIVERSITY OF NEW YORK. 1. Type of Change: Change in Degree Requirements
Alpha Number: Hegis Code 1214 Program Code: 30600 1. Type of Change: Change in Degree Requirements 2. From: [The curriculum consists of 45 graduate credits and includes core courses, an area of specialization,
Introduction to Statistical Analysis using IBM SPSS Statistics (v24)
to Statistical Analysis using IBM SPSS Statistics (v24) to Statistical Analysis Using IBM SPSS Statistics is a two day instructor-led classroom course that provides an application-oriented introduction
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (July, 2018)
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (July, 2018) Report Contents: Report Summary of Hiring Status ( rate over 10%) 1) Hospital vacancies have slowly decreased
Statistics in medicine
Statistics in medicine Lecture 3: Bivariate association : Categorical variables Proportion in one group One group is measured one time: z test Use the z distribution as an approximation to the binomial
Big-Geo-Data EHR Infrastructure Development for On-Demand Analytics
Big-Geo-Data EHR Infrastructure Development for On-Demand Analytics Sohayla Pruitt, MA Senior Geospatial Scientist Duke Medicine DUHS DHTS EIM HIRS Page 1 Institute of Medicine, World Health Organization,
Linear Methods for Classification
Linear Methods for Classification Department of Statistics The Pennsylvania State University Email: jiali@stat.psu.edu Classification Supervised learning Training data: {(x 1, g 1 ), (x 2, g 2 ),..., (x
ECLT 5810 Linear Regression and Logistic Regression for Classification. Prof. Wai Lam
ECLT 5810 Linear Regression and Logistic Regression for Classification Prof. Wai Lam Linear Regression Models Least Squares Input vectors is an attribute / feature / predictor (independent variable) The
CONSTRUCTING THE POVERTY AND OPPORTUNITIES/PUBLIC SERVICES MAPS INFORMATION MANAGEMENT. Background: Brazil Without Extreme Poverty Plan
INFORMATION MANAGEMENT CONSTRUCTING THE POVERTY AND OPPORTUNITIES/PUBLIC SERVICES MAPS Background: Brazil Without Extreme Poverty Plan The Brazil Without Extreme Poverty Plan (BSM), designed to overcome
Master of Science in Statistics A Proposal
1 Master of Science in Statistics A Proposal Rationale of the Program In order to cope up with the emerging complexity on the solutions of realistic problems involving several phenomena of nature it is
Fundamentals to Biostatistics. Prof. Chandan Chakraborty Associate Professor School of Medical Science & Technology IIT Kharagpur
Fundamentals to Biostatistics Prof. Chandan Chakraborty Associate Professor School of Medical Science & Technology IIT Kharagpur Statistics collection, analysis, interpretation of data development of new
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (September, 2018)
ZSFG Human Resources Services Report Submitted to the Joint Conference Committee (September, ) Report Contents: Vacancy Report Summary of Hiring Status (Vacancy rate over 10%) Graphs: YTD vacancy rate,
Department of Economic and Social Affairs May 2007
UNITED NATIONS SECRETARIAT ESA/STAT/AC.115/13 Department of Economic and Social Affairs May 2007 Statistics Division English only United Nations Expert Group Meeting on Contemporary Practices in Census
Approach to identifying hot spots for NCDs in South Africa
Approach to identifying hot spots for NCDs in South Africa HST Conference 6 May 2016 Noluthando Ndlovu, 1 Candy Day, 1 Benn Sartorius, 2 Karen Hofman, 3 Jens Aagaard-Hansen 3,4 1 Health Systems Trust,
COMMISSION ON ACCREDITATION 2014 ANNUAL REPORT ONLINE
COMMISSION ON ACCREDITATION 2014 ANNUAL REPORT ONLINE SUMMARY DATA: POSTDOCTORAL PROGRAMS ^Clicking a table title will automatically direct you to that table in this document *Programs that combine two
Sasko Martinovski 1* Abstract. 1. Introduction. Review paper UDC 007:004]:528}:613/614
![Sasko Martinovski 1* Abstract. 1. Introduction. Review paper UDC 007:004]:528}:613/614](/thumbs/90/101776932.jpg "Sasko Martinovski 1* Abstract. 1. Introduction. Review paper UDC 007:004]:528}:613/614")
Review paper UDC 007:004]:528}:613/614 DEVELOPING SYSTEMS FOR STRATEGIC PLANNING IN THE HEALTH AND NUTRITION SECTOR BY USING THE GEOGRAPHIC INFORMATION SYSTEM AND ITS APPLICATION IN THE REPUBLIC OF MACEDONIA
COMMISSION ON ACCREDITATION 2012 ANNUAL REPORT ONLINE
COMMISSION ON ACCREDITATION 2012 ANNUAL REPORT ONLINE SUMMARY DATA: POSTDOCTORAL PROGRAMS ^Clicking a table title will automatically direct you to that table in this document *Programs that combine two
Power and Sample Size for the Most Common Hypotheses in Mixed Models
Power and Sample Size for the Most Common Hypotheses in Mixed Models Anna E. Barón Sarah M. Kreidler Deborah H. Glueck, University of Colorado and Keith E. Muller, University of Florida UNIVERSITY OF COLORADO
AN EMPIRICAL INVESTIGATION OF THE IMPACT OF DIFFERENT METHODS FOR SYNTHESISING EVIDENCE IN A NETWORK META- ANALYSIS
AN EMPIRICAL INVESTIGATION OF THE IMPACT OF DIFFERENT METHODS FOR SYNTHESISING EVIDENCE IN A NETWORK META- ANALYSIS Project team Amalia (Emily) Karahalios - School of Public Health and Preventive Medicine,
INTRODUCTION. In March 1998, the tender for project CT.98.EP.04 was awarded to the Department of Medicines Management, Keele University, UK.
INTRODUCTION In many areas of Europe patterns of drug use are changing. The mechanisms of diffusion are diverse: introduction of new practices by new users, tourism and migration, cross-border contact,
9/12/17. Types of learning. Modeling data. Supervised learning: Classification. Supervised learning: Regression. Unsupervised learning: Clustering
Types of learning Modeling data Supervised: we know input and targets Goal is to learn a model that, given input data, accurately predicts target data Unsupervised: we know the input only and want to make
Machine Learning (CS 567) Lecture 5
Machine Learning (CS 567) Lecture 5 Time: T-Th 5:00pm - 6:20pm Location: GFS 118 Instructor: Sofus A. Macskassy (macskass@usc.edu) Office: SAL 216 Office hours: by appointment Teaching assistant: Cheol
GEOSPATIAL ONLINE WEB-TOOLS CapeFarmMapper & CAMIS
GEOSPATIAL ONLINE WEB-TOOLS CapeFarmMapper & CAMIS F.C. Basson 14 March 2017 Overview Spatial information and technology has become more important and relevant Applications Mapping of Agricultural footprint
Machine Learning (CS 567) Lecture 2
Machine Learning (CS 567) Lecture 2 Time: T-Th 5:00pm - 6:20pm Location: GFS118 Instructor: Sofus A. Macskassy (macskass@usc.edu) Office: SAL 216 Office hours: by appointment Teaching assistant: Cheol
Purpose Study conducted to determine the needs of the health care workforce related to GIS use, incorporation and training.
GIS and Health Care: Educational Needs Assessment Cindy Gotz, MPH, CHES Janice Frates, Ph.D. Suzanne Wechsler, Ph.D. Departments of Health Care Administration & Geography California State University Long
School of Geography and Geosciences. Head of School Degree Programmes. Programme Requirements. Modules. Geography and Geosciences 5000 Level Modules
School of Geography and Geosciences Head of School Degree Programmes Graduate Diploma: Dr W E Stephens Health Geography Research Environmental History and Policy (see School of History) M.Res.: M.Litt.:
Chapter 4 Multi-factor Treatment Designs with Multiple Error Terms 93
Contents Preface ix Chapter 1 Introduction 1 1.1 Types of Models That Produce Data 1 1.2 Statistical Models 2 1.3 Fixed and Random Effects 4 1.4 Mixed Models 6 1.5 Typical Studies and the Modeling Issues
edrymoni.aspx M.Sc. in Mathematics, University of Rhode Island, May 2009.
Emmanouil (Manos) Drymonis Visiting Assistant Professor of Mathematics Providence College Howley Hall 218 Providence, Rhode Island 02918, USA tel. 401-865-2633 (office) Email: edrymoni@providence.edu http://www.providence.edu/mathematics-computer-science/faculty/pages/
Cluster Analysis using SaTScan
Cluster Analysis using SaTScan Summary 1. Statistical methods for spatial epidemiology 2. Cluster Detection What is a cluster? Few issues 3. Spatial and spatio-temporal Scan Statistic Methods Probability
Mixture modelling of recurrent event times with long-term survivors: Analysis of Hutterite birth intervals. John W. Mac McDonald & Alessandro Rosina
Mixture modelling of recurrent event times with long-term survivors: Analysis of Hutterite birth intervals John W. Mac McDonald & Alessandro Rosina Quantitative Methods in the Social Sciences Seminar -
Biost 518 Applied Biostatistics II. Purpose of Statistics. First Stage of Scientific Investigation. Further Stages of Scientific Investigation
Biost 58 Applied Biostatistics II Scott S. Emerson, M.D., Ph.D. Professor of Biostatistics University of Washington Lecture 5: Review Purpose of Statistics Statistics is about science (Science in the broadest
Finding Common Ground Through GIS
Finding Common Ground Through GIS Matthew Stone, MPH Special Unit for Technical Assistance Chronic Disease and Injury Control California Department of Public Health ESRI Health GIS Conference Scottsdale,
Tutorial 6: Tutorial on Translating between GLIMMPSE Power Analysis and Data Analysis. Acknowledgements:
Tutorial 6: Tutorial on Translating between GLIMMPSE Power Analysis and Data Analysis Anna E. Barón, Keith E. Muller, Sarah M. Kreidler, and Deborah H. Glueck Acknowledgements: The project was supported
PROGRAM ESTIMATES FY
PROGRAM ESTIMATES FY 2017-2018 Programs Course Fees Books Supplies/ Special Needs Total Agriculture, Food And Natural Resources Dairy Science 5,000.00 400.00 0.00 5,400.00 Energy Management Technology
GIS certificate; 24th 28th September and 3rd 7th December University of Venda
;, TARGET Delegates; Town planners. Geologist, Hydrologist, Hydro-Geologists Botanists Conservationists Land Surveyors, Educators, Researchers, Undergraduate and post-graduate students, companies, Local
Using GIS to Brief New York City Public Officials after September 11
Using GIS to Brief New York City Public Officials after September 11 Presented by Zvia Segal Naphtali, Ph.D. and Leonard M. Naphtali, Ph.D. Presented at the ESRI International Health GIS Conference, May
International Development
International Development Office: The Payson Center for International Development and Technology Transfer, 300 Hébert Hall Phone: 504-865-5240 Fax: 504-865-5241 Website: www.payson.tulane.edu/ Program
Applying Health Outcome Data to Improve Health Equity
Applying Health Outcome Data to Improve Health Equity Devon Williford, MPH, Health GIS Specialist Lorraine Dixon-Jones, Policy Analyst CDPHE Health Equity and Environmental Justice Collaborative Mile High
DISTRICT ESTIMATES OF HOME DELIVERIES IN GHANA: A SMALL AREA ANALYSIS USING DHS AND CENSUS DATA
DISTRICT ESTIMATES OF HOME DELIVERIES IN GHANA: A SMALL AREA ANALYSIS USING DHS AND CENSUS DATA Fiifi Amoako Johnson, James J. Brown & Sabu S. Padmadas Correspondence: Fiifi Amoako Johnson Division of
Measuring community health outcomes: New approaches for public health services research
Research Brief March 2015 Measuring community health outcomes: New approaches for public health services research P ublic Health agencies are increasingly asked to do more with less. Tough economic times
CHEMICAL ENGINEERING (CHE)
Chemical Engineering (CHE) 1 CHEMICAL ENGINEERING (CHE) CHE 2033 Introduction to Chemical Process Engineering Prerequisites: CHEM 1515 and ENSC 2213 Description: Concurrent enrollment in MATH 2233 or 3263,
GEOGRAPHIC INFORMATION SYSTEMS SPECIALIST 3 DEFINITION:
Hunterdon County Department of Planning and Land Use Vacancy: Geographic Information Systems Specialist 3 Full Time: 40 Hours per Week Compensation: $42,000.00 per year GEOGRAPHIC INFORMATION SYSTEMS SPECIALIST
PROGRAM ESTIMATES FY
PROGRAM ESTIMATES FY 2018-2019 Programs Course Fees Books Agriculture, Food And Natural Resources Agronomy (Crop Science) 4,900.00 600.00 150.00 5,650.00 Dairy Science 5,100.00 1,100.00 150.00 6,350.00
Machine Learning Linear Classification. Prof. Matteo Matteucci
Machine Learning Linear Classification Prof. Matteo Matteucci Recall from the first lecture 2 X R p Regression Y R Continuous Output X R p Y {Ω 0, Ω 1,, Ω K } Classification Discrete Output X R p Y (X)
POPULATION DYNAMICS & SOCIAL CHANGE IN 3RD WORLD
Syllabus POPULATION DYNAMICS & SOCIAL CHANGE IN 3RD WORLD - 53810 Last update 10-11-2013 HU Credits: 2 Degree/Cycle: 2nd degree (Master) Responsible Department: Sociology and Anthropology Academic year:
Richard D Riley was supported by funding from a multivariate meta-analysis grant from
Bayesian bivariate meta-analysis of correlated effects: impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences Author affiliations Danielle L Burke
GIS as a Management Tool in Nepal Earthquake Response
GIS as a Management Tool in Nepal Earthquake Response Presenter: Charlie Charping GIS Manager Samaritan s Purse A CASE STUDY & LESSONS LEARNED Presentation Agenda Samaritan s Purse Background The Case
Machine Learning (CS 567) Lecture 3
Machine Learning (CS 567) Lecture 3 Time: T-Th 5:00pm - 6:20pm Location: GFS 118 Instructor: Sofus A. Macskassy (macskass@usc.edu) Office: SAL 216 Office hours: by appointment Teaching assistant: Cheol
FLORIDA COLLEGE SYSTEM VOCATIONAL PROGRAMS AGGREGATED OUTCOME DATA
FLORIDA COLLEGE SYSTEM VOCATIONAL PROGRAMS AGGREGATED OUTCOME DATA 2015-16 PSVC Degree Completers FETPIP FOLLOW-UP OUTCOMES TOTAL FREQ = number of individuals reported for follow-up to FETPIP. FOUND EMPLOYED
An Overview of Methods for Applying Semi-Markov Processes in Biostatistics.
An Overview of Methods for Applying Semi-Markov Processes in Biostatistics. Charles J. Mode Department of Mathematics and Computer Science Drexel University Philadelphia, PA 19104 Overview of Topics. I.
Overview. DS GA 1002 Probability and Statistics for Data Science. Carlos Fernandez-Granda
Overview DS GA 1002 Probability and Statistics for Data Science http://www.cims.nyu.edu/~cfgranda/pages/dsga1002_fall17 Carlos Fernandez-Granda Probability and statistics Probability: Framework for dealing
STAC51: Categorical data Analysis
STAC51: Categorical data Analysis Mahinda Samarakoon January 26, 2016 Mahinda Samarakoon STAC51: Categorical data Analysis 1 / 32 Table of contents Contingency Tables 1 Contingency Tables Mahinda Samarakoon
CS 6375 Machine Learning
CS 6375 Machine Learning Nicholas Ruozzi University of Texas at Dallas Slides adapted from David Sontag and Vibhav Gogate Course Info. Instructor: Nicholas Ruozzi Office: ECSS 3.409 Office hours: Tues.
Substantiation of Disease and Health-Related Claims in Advertising. Washington, D.C.
Substantiation of Disease and Health-Related Claims in Advertising Food, Drug, and Law Institute Food Advertising, Labeling, and Litigation Conference September 13-14, 2017 Washington, D.C. Richard L.
FIRE DEPARMENT SANTA CLARA COUNTY
DEFINITION FIRE DEPARMENT SANTA CLARA COUNTY GEOGRAPHIC INFORMATION SYSTEM (GIS) ANALYST Under the direction of the Information Technology Officer, the GIS Analyst provides geo-spatial strategic planning,
A Brief Introduction to Intersection-Union Tests. Jimmy Akira Doi. North Carolina State University Department of Statistics
Introduction A Brief Introduction to Intersection-Union Tests Often, the quality of a product is determined by several parameters. The product is determined to be acceptable if each of the parameters meets
Bayesian Inference on Joint Mixture Models for Survival-Longitudinal Data with Multiple Features. Yangxin Huang
Bayesian Inference on Joint Mixture Models for Survival-Longitudinal Data with Multiple Features Yangxin Huang Department of Epidemiology and Biostatistics, COPH, USF, Tampa, FL yhuang@health.usf.edu January
Geospatial Big Data Analytics for Road Network Safety Management
Proceedings of the 2018 World Transport Convention Beijing, China, June 18-21, 2018 Geospatial Big Data Analytics for Road Network Safety Management ABSTRACT Wei Liu GHD Level 1, 103 Tristram Street, Hamilton,
BOWIE SENIORS COMPUTER CLUB
BOWIE SENIORS COMPUTER CLUB Meeting Minutes for May 5, 2016 Through the efforts of Program Chairman Dan Lee, we had Patrick T. Callahan, GIS Manager of the Prince George's County Office of Information
Medical GIS: New Uses of Mapping Technology in Public Health. Peter Hayward, PhD Department of Geography SUNY College at Oneonta
Medical GIS: New Uses of Mapping Technology in Public Health Peter Hayward, PhD Department of Geography SUNY College at Oneonta Invited research seminar presentation at Bassett Healthcare. Cooperstown,
Factor Analytic Models of Clustered Multivariate Data with Informative Censoring (refer to Dunson and Perreault, 2001, Biometrics 57, )
Factor Analytic Models of Clustered Multivariate Data with Informative Censoring (refer to Dunson and Perreault, 2001, Biometrics 57, 302-308) Consider data in which multiple outcomes are collected for
ALL OF NONPARAMETRIC STATISTICS SOLUTIONS
page 1 / 5 page 2 / 5 all of nonparametric statistics pdf Nonparametric statistics is the branch of statistics that is not based solely on parametrized families of probability distributions (common examples
ENHANCING ROAD SAFETY MANAGEMENT WITH GIS MAPPING AND GEOSPATIAL DATABASE
Abstract ENHANCING ROAD SAFETY MANAGEMENT WITH GIS MAPPING AND GEOSPATIAL DATABASE Dr Wei Liu GHD Reliable and accurate data are needed in each stage of road safety management in order to correctly identify
BAYESIAN METHODS FOR VARIABLE SELECTION WITH APPLICATIONS TO HIGH-DIMENSIONAL DATA
BAYESIAN METHODS FOR VARIABLE SELECTION WITH APPLICATIONS TO HIGH-DIMENSIONAL DATA Intro: Course Outline and Brief Intro to Marina Vannucci Rice University, USA PASI-CIMAT 04/28-30/2010 Marina Vannucci
Anders Skrondal. Norwegian Institute of Public Health London School of Hygiene and Tropical Medicine. Based on joint work with Sophia Rabe-Hesketh
Constructing Latent Variable Models using Composite Links Anders Skrondal Norwegian Institute of Public Health London School of Hygiene and Tropical Medicine Based on joint work with Sophia Rabe-Hesketh
Lecture 1 Introduction to Multi-level Models
Lecture 1 Introduction to Multi-level Models Course Website: http://www.biostat.jhsph.edu/~ejohnson/multilevel.htm All lecture materials extracted and further developed from the Multilevel Model course
STA 4273H: Statistical Machine Learning
STA 4273H: Statistical Machine Learning Russ Salakhutdinov Department of Statistics! rsalakhu@utstat.toronto.edu! http://www.utstat.utoronto.ca/~rsalakhu/ Sidney Smith Hall, Room 6002 Lecture 3 Linear
Joint longitudinal and time-to-event models via Stan
Joint longitudinal and time-to-event models via Stan Sam Brilleman 1,2, Michael J. Crowther 3, Margarita Moreno-Betancur 2,4,5, Jacqueline Buros Novik 6, Rory Wolfe 1,2 StanCon 2018 Pacific Grove, California,
UNIVERSITY OF THE PHILIPPINES LOS BAÑOS INSTITUTE OF STATISTICS BS Statistics - Course Description
UNIVERSITY OF THE PHILIPPINES LOS BAÑOS INSTITUTE OF STATISTICS BS Statistics - Course Description COURSE COURSE TITLE UNITS NO. OF HOURS PREREQUISITES DESCRIPTION Elementary Statistics STATISTICS 3 1,2,s
MAPPING DATA AND INFORMATION SYSTEMS AVAILABILITY AGAINST THE SDGs
MAPPING DATA AND INFORMATION SYSTEMS AVAILABILITY AGAINST THE SDGs Imelda Atai Musana Uganda Bureau of Statistics imelda.atai@ubos.org Date: November 2015 1 Introduction Uganda Lies Astride the Equator
Health utilities' affect you are reported alongside underestimates of uncertainty
Dr. Kelvin Chan, Medical Oncologist, Associate Scientist, Odette Cancer Centre, Sunnybrook Health Sciences Centre and Dr. Eleanor Pullenayegum, Senior Scientist, Hospital for Sick Children Title: Underestimation
Universität Potsdam Institut für Informatik Lehrstuhl Maschinelles Lernen. Linear Classifiers. Blaine Nelson, Tobias Scheffer
Universität Potsdam Institut für Informatik Lehrstuhl Linear Classifiers Blaine Nelson, Tobias Scheffer Contents Classification Problem Bayesian Classifier Decision Linear Classifiers, MAP Models Logistic
Mediation analyses. Advanced Psychometrics Methods in Cognitive Aging Research Workshop. June 6, 2016
Mediation analyses Advanced Psychometrics Methods in Cognitive Aging Research Workshop June 6, 2016 1 / 40 1 2 3 4 5 2 / 40 Goals for today Motivate mediation analysis Survey rapidly developing field in
Optimising Group Sequential Designs. Decision Theory, Dynamic Programming. and Optimal Stopping
: Decision Theory, Dynamic Programming and Optimal Stopping Christopher Jennison Department of Mathematical Sciences, University of Bath, UK http://people.bath.ac.uk/mascj InSPiRe Conference on Methodology
CS 540: Machine Learning Lecture 1: Introduction
CS 540: Machine Learning Lecture 1: Introduction AD January 2008 AD () January 2008 1 / 41 Acknowledgments Thanks to Nando de Freitas Kevin Murphy AD () January 2008 2 / 41 Administrivia & Announcement
Spatial Analysis Unit Carolina Population Center
Spatial Analysis Unit Carolina Population Center scan code to link to website: www.cpc.unc.edu/aboutcpc/services/research/spatial Carolina Population Center University Square East 123 West Franklin Street
By Abdulraheem M.Baabbad. Supervisor: Dr.Bager Al-Ramadan
By Abdulraheem M.Baabbad Supervisor: Dr.Bager Al-Ramadan OUTLINE Health GIS Health GIS Application Emergency Vehicles Allocation: A case study Health GIS Innovative structureto access,integrate,visualize
AP Statistics Homework 11. Logistic Regression
AP Statistics Homework 11 Logistic Regression 1. Anabolic steroid abuse has been increasing despite increased press reports of adverse medical and psychiatric consequences. In a recent study, medical researchers
WHITEPAPER. J u l y V2.01
WHITEPAPER A Natural solution to health, based on blockchain technology. J u l y 2 0 1 8 V2.01 Table of Contents 1 P l a t fo r m S u m m a r y H o l i stic Pro f i l i n g H e a l t h D a t a S t o ra
Probabilistic Methods in Bioinformatics. Pabitra Mitra
Probabilistic Methods in Bioinformatics Pabitra Mitra pabitra@cse.iitkgp.ernet.in Probability in Bioinformatics Classification Categorize a new object into a known class Supervised learning/predictive