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37 Pages

### v2part1

Course: EPI 521, Fall 2009
School: UPenn
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Word Count: 8274

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521, EP Spring 2007. Vol II, Part 1 1 Statistical Methods in Epidemiologic Research EP 521 Spring 2007 Course Notes Vol II (Part 1 of 9) Multivariable Regression A. Russell Localio*, and Jesse A Berlin (The Great Master) *Department of Biostatistics and Epidemiology Center for Clinical Epidemiology and Biostatistics School of Medicine University of Pennsylvania Philadelphia PA 19104-6021 Statistical Science,...

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UPenn - EPI - 521
EP 521 Spring 2007, Vol II, Part 9 (Under development) 10 Propensity Scores (balancing scores) 10.1 Potential outcomes, confounding, and conditional independence Problem: In randomized studies: when there are two groups, treated and control: We rely
UPenn - EPI - 521
EP 521, Spring 2007, Vol II, Part 719 Survival Analysis 9.1 Survival and hazard functions 9.2 Survival data and censoring 9.3 Estimating survival functions 9.3.1 Life Table method 9.3.2 Kaplan-Meier method 9.4 Competing risks 9.5 Noninformative c
UPenn - EPI - 521
EP 521, Spring 2007 Vol II, Part 517Other generalized linear regression models for epidemiology We have focused on logistic regression and linear regression. But these are special case of generalized linear models: Ordinary least squares reg
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EP 521 Spring 2007 Vol I, part 312.2 Stratified AnalysesMethods and formulae How do we analyze data in the presence of confounding (or effect modification)? This section focuses on Mantel Haenszel methods for stratified analysis of binary outcome
UPenn - EPI - 521
EP 521, Spring 2007, Vol II, Part 819.9 Cox (proportional hazards) multivariable survival methods We have examined the basic and principal methods of handling survival data: life tables, KaplanMeier estimates, and the log-rank test. These methods
UPenn - EPI - 521
EP 521 Spring 2007, Vol II, Part 21Regression Methods for binary outcomes (logistic regression) 4.1 Background 4.2 Logistic regression properties of the model 4.3 Logistic regression Use of the model 4.4 Likelihoods and likelihood ratios 4.5 Li
UPenn - EPI - 521
EP 521 Spring, 2004, Vol I, Part 513.Sample Size Estimation A key to study design are sample size or power calculations. Required of ever grant proposal In this section: (1) we begin with theory behind power calculations and demonstrate how sim
UPenn - BSTA - 790
Noncompliance in randomized trials Frequently in randomized trials, subjects do not comply with their assigned treatment regimen Examples: Health Insurance Plan (HIP) trial of screening for breast cancer (BC) 2 arms: control: no screening screening
UPenn - BSTA - 652
Reference: Agresti, Chapter 16. Categorical data are measured using a limited number of valuesor categories. Categorical variables may have a natural ordering (ordinal) orthe order may be irrelevant (nominal). They are common in biomedical sc
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1. 2.Give an example of a pair of (different) functions that have the same derivative. Find an anti-derivative of each of the following functions: a) f (x) = sin(2x) b) f (x) = x3 x2 c) f (x) = x3.The points A,B,C,D (in some order) are success
UPenn - MATH - 103
UNIVERSITY of PENNSYLVANIA MATHEMATICS DEPARTMENTMathematics 103 Midterm I Fall 2006Your Name:_ Penn ID#_ Your Professor (check one): Crotty Komendarczyk Tapp Your TA: __Instructions: You have 2 hours to complete this examination. Please write
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UNIVERSITY of PENNSYLVANIA MATHEMATICS DEPARTMENTMathematics 103 Midterm II Fall 2006Your Name:_ Penn ID#_ Your Professor (check one): Crotty Komendarczyk Tapp Your TA: __Instructions: You have 2 hours to complete this examination. Please write
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U S I N G T H E S A M E S Y S T E M F O R A N A L Y Z I N G AND S Y N T H E S I Z I N G S E N T E N C E SPhillipeRincel*andPaul Sabatier* Bull S.A., CE1)IAG, 68 Route de Versailles, 78430 Louveciennes, France. * CNRS, Groupe Intelligen
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BENTE MAEGAARD-EBBE S P A N G - H A N S S E NSEGMENTATION OF FRENCH SENTENCES1. This paper describes a programme which, by means of a very limited number of criteria, analyses French sentences into principal clauses and subordinate clauses. W
UPenn - J - 99
Computational LinguisticsVolume 25, Number 3Beyond Grammar: An Experience-based Theory of Language Rens Bod(University of Amsterdam) Stanford: CSLI Publications (Lecture notes number 88), 1998, xiii+168 pp; distributed by Cambridge University Pr
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INTEGRATING WITHWORD BOUNDARY IDENTIFICATION SENTENCE UNDERSTANDINGKok Wee GanDepartment of Information Systems eJ Computer Science National University of SingaporeK e n t R i d g e C r e s c e n t , S i n g a p o r e 0511 Internet: gankw@iscs.
UPenn - J - 93
Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and RetrievalPaul S. Jacobs (editor)(Research and Development Center, General Electric Company) Hillsdale, NJ: Lawrence Erlbaum Associates, 1992, viii + 281 pp.
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RECOGNIZINGADVICE, WARNINGS,PROMISESAND THREATSKevin Donaghy School of Computer Science and Information Technology Rochester Institute of Technology, Rochester, New York 14623 hkd@cs.rit.eduIt is argued here that utterances in the imperative m
UPenn - P - 83
Crossed S e r i a l Dependencies: i low-power parseable extension to GPSG Henry Thompson Department of Artificial Intelligence and Program in Cognitive Science U n i v e r s i t y of Edinburgh Hope Park Square, Meadow Lane Edinburgh EH8 9NW SCOTLAND
UPenn - P - 96
Using textual clues to improve metaphor processingSt6phane FerrariLIMSI-CNRS P O B o x 133 F-91403 Orsay cSdex, FRANCE ferrari@limsi.frAbstract In this paper, we propose a textual clue approach to help metaphor detection, in order to improve the
UPenn - C - 88
Vi~tcenza I'~I~}NATARO PaL f. Lingaisfik u.Literattn,viss. Universitht Bielefeld PostfN~h 8640 D-4g0b~ Bielefeld 1 .4~&lt;.x;~&gt;~: The aim of the presenteA rc~:~ffeh is the dt~velop ~:~-~i: ~f a lh~gaisdc mo.del of the function01 cont~pts topic and ~i;,
UPenn - P - 84
SOME L I N G U I S T I CASPECTSFOR A U T O M A T I CTEXTUNDERSTANDINGInstituteYutaka Kusanagi of Literature and Linguistics University of Tsukuba Sakura-mura, Ibarakl 3 0 5 JAPANABSTRACTThis paper proposes a s y s t e m of mapping clas
UPenn - T - 78
The Relation of Grammar to Cognition-a Synopsis Leonard Talmy Program in Cognitive Science / Center for Human Information Processing / UC San DiegoAbstract A sentence (or other portion of discourse) is taken to evoke in the listener a meaning compl
UPenn - P - 84
REPRESENTINGKNOWLEDGE ABOUT KNOWLEDGE AND MUTUAL KNOWLEDGE Sald SoulhiEquipe de Comprehension LSI-du Raisonnement UPSNaturelllg route de Narbonne 31062 Toulouse - FRANCEABSTRACT In order to represent speech acts, in a multi-agent context
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TRANSFER IN A MULTILINGUALMT SYSTEMSteven Krauwer &amp; Louis des Tombe Institute for General Linguistics Utrecht State University Trans 14, 3512 JK Utrecht, The NetherlandsABSTRACT In the context of transferbased MT systems, the nature of the inte
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STRING-TREE CORRESPONDENCE GRAMMAR: A DECLARATIVE GRAMMAR FORMALISM FOR DEFINING THE CORRESPONDENCE BETWEEN STRINGS OF TERMS AND TREE STRUCTURES YUSOFF ZAHARIN Groupe d'Etudes pour la Traduction Automatique B.P. n 68 Universit~ de Grenoble 38402 SAI
UPenn - C - 88
E x p r e s s i n g q u a n t i f i e r s c o p e in F r e n c h g e n e r a t i o nPierre-Joseph G A I L L Y * Computer Science D e p a r t m e n t , U n i v e r s i t y of Liege, B4000 Li~ge~ B e l g i u mAbstractIn this paper we propose a new
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Automatic Refinement of a POS Tagger Using a Reliable Parser and Plain Text CorporaHideki Hirakawa, Kenji Ono, Yulniko Yoshimura Human Interface Laboratory Corporate Research &amp; Development Center Toshiba Corporation Konmkai-Toshiba-cho 1, Saiwai-ku,
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Math 114-001: Hour Exam 2 KeyFeb. 22, 2008Multiple choice questions (10 points each). (1) The curves in R3 dened by r(t) = (t2 , sin(t), t3 ) and h(t) = (sin(t), t, t2 ) intersect at the point (0, 0, 0) when t = 0. What is the angle in radians bet
UPenn - EXAM - 2
Information about the Second Hour exam for Math 114-001 Mechanics of the exam:(1) The exam has been moved to Friday, Feb. 22, in our usual room, DRL A8, at the usual time (11:00 am). It will be 45 minutes long to give us time to collect the exams be
UPenn - EXAM - 3
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Information about the Fourth Hour exam for Math 114-001 Mechanics of the exam:(1) There will be a review session from 8 p.m. to 10 p.m. the evening of Thursday, April 24, in room A5 of DRL labs. (2) The exam will be on Monday, April 28, in our usual
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Math 114-001: Hour Exam 411 a.m., April 24, 2008Your Name: Your T.A. and recitation time: Instructions: This exam is 45 minutes long. You can use one handwritten one-sided page of notes, but no books or calculators. It is important that you show
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Information about the Third Hour exam for Math 114-001 Mechanics of the exam:(1) There will be a review session from 8 p.m. to 10 p.m. the evening of Thursday, May 27, in room A5 of DRL labs. (2) The exam will be on Monday, March 31, in our usual ro
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General Analysis of LARGE Volume Scenarios with String Loop Moduli StabilisationMichele CicoliDepartment of Applied Mathematics and Theoretical Physics University of Cambridge SP08, Upenn, 29 May 2008 Based on: 1) M. Cicoli, J. Conlon, F. Quevedo a
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Solutions to Problem Set #2 (logic and voting systems)Q 1. Negate the sentence: For every vote Senator Specter gets, he has to spend \$10 or one hour of volunteer time. Answer We can let x be a vote that Specter gets, and P (x) = Specter spends \$10
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Eve Mayer March 19, 2003Mathematics 170 Project: Standoff at Fort SumterThe American Civil War, which lasted from 1861 to 1865, began with a standoff at Fort Sumter, South Carolina. The fort, located in the Charleston harbor, was a federal base c
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The Israeli Palestinian ConflictPost Oslo AccordsMeira Levinson Math 170 3/ 19/ 03Historical Background After many years of conflict and war between Israelis and Arabs, hope for peace finally seemed possible with the signing of the Oslo Accor
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I am exploring the possible actions that might take place during the United States second conflict with Iraq. Could there be no bloodshed? Would Iraq ever kick Saddam Hussein out? Come explore the possibilities with me in the wonderful world of confl
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UPenn - MATH - 170
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