Degrees of freedom in HLM models
|
|
|
- Brook Moore
- 8 years ago
- Views:
Transcription
1 Degees o eedom n HLM models The vaous degees o eedom n a HLM2/HLM3 model can be calculated accodng to Table 1 and Table 2. Table 1: Degees o Feedom o HLM2 Models Paamete/Test Statstc Degees o Feedom Gammas - Least Squae tables Beta andom Beta xed T Vaance components K q()* Geneal Hypothess tests Statstcs o cuent covaance components Vaance-Covaance test ** Homogenety o level-1 vaance T (egadless o xng; not an appoxmaton) J q The numbe o contasts speced ( 1)/1 2 o all models; add 1 loats, add MLF. the d.. speced along wth the model speccaton the numbe o unts o OLS esdual vaances (OLSRSVAR n the esdual le) * I the message statng "Note: The ch-squaes epoted above ae based on K o K unts..." s pnted, K s used. ** The degees o eedom o "Statstcs o cuent covaance components"
2 Table 2: Degees o Feedom o HLM3 Models Paamete/Test Statstc Degees o Feedom Gammas - Least Squae T tables (egadless o xng; not an appoxmaton) Gammas - Beta andom K q () 2 Gammas - Beta xed/p andom Gammas - Beta xed/p xed J q() T Vaance components: Level-3 K q ()* Level-1 and level-2 J q () K q ()* Geneal Hypothess tests The numbe o contasts speced Statstcs o cuent covaance components: 1( 1 1) / 2 2( 2 1) / 2 ; add 1 Vaance-Covaance test **: 2 loats the d.. speced along wth the model speccaton * I the message statng "Note: The ch-squaes epoted above ae based on K/J o K/J unts..." s pnted, K/J s used. ** The degees o eedom o "Statstcs o cuent covaance components" whee T = numbe o level-1 ecods n MDM J = numbe o level-2 ecods n HLM3 MDM K = numbe o level-3 ecods n HLM3 (level-2 ecods n HLM2) MDM = numbe o level-2 andom eects n HLM2 1 = numbe o andom eects at -level n HLM3 2 = numbe o andom eects at -level HLM3 = total numbe o xed eects q () n a HLM2 model, a gven s assocated wth a cetan. q ( ) s the the numbe o s assocated wth ths ; n a HLM3 model, a gven and s assocated wth a cetan. q ( ) s the numbe o s assocated wth ths. q () a gven s assocated wth a cetan. 2 q () 2 s the numbe o s assocated wth ths.
3 q () the numbe o andom eects assocated wth a cetan. q () the numbe o xed eects assocated wth a cetan. The calculatons o these degees o eedom ae llustated n the ollowng HLM2 and HLM3 examples. Example 1: A HLM2 model Gven the ollowng andom-ntecept model om the HSB data, MATHACH ( SES) 1 ( SECTOR) ( MEANSES) u ( SECTOR) ( MEANSES) u We have: T = 7185, K = 16, = 1 ( u ), =6 (6 s), and q() q(1) = 3. The degees o eedom n the least-squaes tables ae: T = = The appoxmate degees o eedom o the Gammas ae calculated accodng to the andomness o the beta s they ae assocated wth and ae lsted n Table 3. Table 3: Degees o Feedom o the Gammas Fxed Eect Randomness o Beta q () Fomula o d.. Appox. d.. andom 3 K q() andom 3 K q() andom 3 K q() xed 3 T xed 3 T 7179
4 12 xed 3 T 7179 The degees o eedom o the vaance component u s 16 3 = 157. The degees o eedom o the geneal hypothess tests ae the numbe o contasts speced, whch s 2 n ou case. The degees o eedom o the Statstcs o cuent covaance components model s ( 1)/2 = 2. The degees o eedom o the Test o homogenety o level-1 vaance s 16 1 = 159. Example 2: A HLM3 model The HLM3 model wth x and andom slopes om the EG data s shown below: MATH ( YEAR) e 1 ( BLACK) ( HISPANIC) ( BLACK) ( HISPANIC) ( LOWINC) u ( LOWINC) u In ths example we have the values: T = 723, J = 1721, K = 6, 1 = 2 (, ), 1 2 = 2 (, 1 u u ), =8 (8 s), q() q(1) = 3 (o and 1), q2() q2(1) (o and 1), q () q (1) = 1, and q () q (1) = 2 The degees o eedom n the least-squaes tables ae: T = = 7222.
5 The appoxmate degees o eedom o the Gammas ae calculated accodng to the andomness o the s and s they ae assocated wth, whch ae lsted n Table 4. Table 4. Degees o Feedom o the Gammas Eect Randomness o Beta Randomness o P q () q () omula o d.. d.. 2 andom andom 3 2 K q () 2 58 andom andom 3 2 K q () xed andom 3 1 J q() xed andom 3 1 J q() andom andom 3 2 K q () andom andom 3 2 K q () xed andom 3 1 J q() xed andom 3 1 J q() The degees o eedom o the level-3 vaance components ae K q ( ), whee K can be K when the message Note: The ch-squae epoted above ae based on K o K unts s pnted n the output. In ou case, the degees o eedom o u s 6 2 = 58, and the same wth u 1. The degees o eedom o level-1 and level-2 vaance components ae J q ( ) Kq( ), whee J and K can be J and K as above. The degees o eedom o the vaance components s summazed n Table 5.
6 Table 5: Degees o Feedom o the Random Eects Vaance Component q () q () omula o d.. d J q() Kq() J q() Kq() 1659 u 1 2 K q () 58 u K q () 58
Illustration (and the use of HLM)
Illustration (and the use of HLM) Chapter 4 1 Measurement Incorporated HLM Workshop The Illustration Data Now we cover the example. In doing so we does the use of the software HLM. In addition, we will
The 3-Level HLM Model
James H. Steiger Department of Psychology and Human Development Vanderbilt University Regression Modeling, 2009 1 2 Basic Characteristics of the 3-level Model Level-1 Model Level-2 Model Level-3 Model
Specifications for this HLM2 run
One way ANOVA model 1. How much do U.S. high schools vary in their mean mathematics achievement? 2. What is the reliability of each school s sample mean as an estimate of its true population mean? 3. Do
Construct the MDM file for a HLM2 model using SPSS file input
Construct the MDM file for a HLM2 model using SPSS file input Level-1 file: For HS&B example data (distributed with the program), the level-1 file (hsb1.sav) has 7,185 cases and four variables (not including
LATIN SQUARE DESIGN (LS) -With the Latin Square design you are able to control variation in two directions.
Facts about the LS Design LATIN SQUARE DESIGN (LS) -With the Latin Squae design you ae able to contol vaiation in two diections. -Teatments ae aanged in ows and columns -Each ow contains evey teatment.
Additional File 1 - A model-based circular binary segmentation algorithm for the analysis of array CGH data
1 Addtonal Fle 1 - A model-based ccula bnay segmentaton algothm fo the analyss of aay CGH data Fang-Han Hsu 1, Hung-I H Chen, Mong-Hsun Tsa, Lang-Chuan La 5, Ch-Cheng Huang 1,6, Shh-Hsn Tu 6, Ec Y Chuang*
Semipartial (Part) and Partial Correlation
Semipatial (Pat) and Patial Coelation his discussion boows heavily fom Applied Multiple egession/coelation Analysis fo the Behavioal Sciences, by Jacob and Paticia Cohen (975 edition; thee is also an updated
Electric Potential. otherwise to move the object from initial point i to final point f
PHY2061 Enched Physcs 2 Lectue Notes Electc Potental Electc Potental Dsclame: These lectue notes ae not meant to eplace the couse textbook. The content may be ncomplete. Some topcs may be unclea. These
(Semi)Parametric Models vs Nonparametric Models
buay, 2003 Pobablty Models (Sem)Paametc Models vs Nonpaametc Models I defne paametc, sempaametc, and nonpaametc models n the two sample settng My defnton of sempaametc models s a lttle stonge than some
An Algorithm For Factoring Integers
An Algothm Fo Factong Integes Yngpu Deng and Yanbn Pan Key Laboatoy of Mathematcs Mechanzaton, Academy of Mathematcs and Systems Scence, Chnese Academy of Scences, Bejng 100190, People s Republc of Chna
Introduction to Multilevel Modeling Using HLM 6. By ATS Statistical Consulting Group
Introduction to Multilevel Modeling Using HLM 6 By ATS Statistical Consulting Group Multilevel data structure Students nested within schools Children nested within families Respondents nested within interviewers
Orbit dynamics and kinematics with full quaternions
bt dynamcs and knematcs wth full quatenons Davde Andes and Enco S. Canuto, Membe, IEEE Abstact Full quatenons consttute a compact notaton fo descbng the genec moton of a body n the space. ne of the most
A New replenishment Policy in a Two-echelon Inventory System with Stochastic Demand
A ew eplenshment Polcy n a wo-echelon Inventoy System wth Stochastc Demand Rasoul Haj, Mohammadal Payesh eghab 2, Amand Babol 3,2 Industal Engneeng Dept, Shaf Unvesty of echnology, ehan, Ian (haj@shaf.edu,
AREA COVERAGE SIMULATIONS FOR MILLIMETER POINT-TO-MULTIPOINT SYSTEMS USING STATISTICAL MODEL OF BUILDING BLOCKAGE
Radoengneeng Aea Coveage Smulatons fo Mllmete Pont-to-Multpont Systems Usng Buldng Blockage 43 Vol. 11, No. 4, Decembe AREA COVERAGE SIMULATIONS FOR MILLIMETER POINT-TO-MULTIPOINT SYSTEMS USING STATISTICAL
PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12
14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed
Portfolio Loss Distribution
Portfolo Loss Dstrbuton Rsky assets n loan ortfolo hghly llqud assets hold-to-maturty n the bank s balance sheet Outstandngs The orton of the bank asset that has already been extended to borrowers. Commtment
Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting
Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of
Estimating Multilevel Models using SPSS, Stata, SAS, and R. JeremyJ.Albright and Dani M. Marinova. July 14, 2010
Estimating Multilevel Models using SPSS, Stata, SAS, and R JeremyJ.Albright and Dani M. Marinova July 14, 2010 1 Multilevel data are pervasive in the social sciences. 1 Students may be nested within schools,
UNIT CIRCLE TRIGONOMETRY
UNIT CIRCLE TRIGONOMETRY The Unit Cicle is the cicle centeed at the oigin with adius unit (hence, the unit cicle. The equation of this cicle is + =. A diagam of the unit cicle is shown below: + = - - -
α α λ α = = λ λ α ψ = = α α α λ λ ψ α = + β = > θ θ β > β β θ θ θ β θ β γ θ β = γ θ > β > γ θ β γ = θ β = θ β = θ β = β θ = β β θ = = = β β θ = + α α α α α = = λ λ λ λ λ λ λ = λ λ α α α α λ ψ + α =
LINES ON BRIESKORN-PHAM SURFACES
LIN ON BRIKORN-PHAM URFAC GUANGFNG JIANG, MUTUO OKA, DUC TAI PHO, AND DIRK IRMA Abstact By usng toc modfcatons and a esult of Gonzalez-pnbeg and Lejeune- Jalabet, we answe the followng questons completely
A Coverage Gap Filling Algorithm in Hybrid Sensor Network
A Coveage Ga Fllng Algothm n Hybd Senso Netwok Tan L, Yang Mnghua, Yu Chongchong, L Xuanya, Cheng Bn A Coveage Ga Fllng Algothm n Hybd Senso Netwok 1 Tan L, 2 Yang Mnghua, 3 Yu Chongchong, 4 L Xuanya,
Bending Stresses for Simple Shapes
-6 Bendng Stesses fo Smple Sapes In bendng, te maxmum stess and amount of deflecton can be calculated n eac of te followng stuatons. Addtonal examples ae avalable n an engneeng andbook. Secton Modulus
CRRC-1 Method #1: Standard Practice for Measuring Solar Reflectance of a Flat, Opaque, and Heterogeneous Surface Using a Portable Solar Reflectometer
CRRC- Method #: Standad Pactice fo Measuing Sola Reflectance of a Flat, Opaque, and Heteogeneous Suface Using a Potable Sola Reflectomete Scope This standad pactice coves a technique fo estimating the
Keywords: Transportation network, Hazardous materials, Risk index, Routing, Network optimization.
IUST Intenatonal Jounal of Engneeng Scence, Vol. 19, No.3, 2008, Page 57-65 Chemcal & Cvl Engneeng, Specal Issue A ROUTING METHODOLOGY FOR HAARDOUS MATIALS TRANSPORTATION TO REDUCE THE RISK OF ROAD NETWORK
Documentation about calculation methods used for the electricity supply price index (SPIN 35.1),
STATISTICS SWEDEN Documentaton (6) ES/PR-S 0-- artn Kullendorff arcus rdén Documentaton about calculaton methods used for the electrct suppl prce ndex (SPIN 35.), home sales (HPI) The ndex fgure for electrct
Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.
Producer Theory Producton ASSUMPTION 2.1 Propertes of the Producton Set The producton set Y satsfes the followng propertes 1. Y s non-empty If Y s empty, we have nothng to talk about 2. Y s closed A set
Making the MDM file. cannot
1 2 Making the MDM file. For any given set of variables, you only need to do this once. But if you need to add a variable, you will need to repeat the process. HLM cannot transform variables (e.g., a square
SIMPLE LINEAR CORRELATION
SIMPLE LINEAR CORRELATION Smple lnear correlaton s a measure of the degree to whch two varables vary together, or a measure of the ntensty of the assocaton between two varables. Correlaton often s abused.
Chapter 4: Matrix Norms
EE448/58 Vesion.0 John Stensby Chate 4: Matix Noms The analysis of matix-based algoithms often equies use of matix noms. These algoithms need a way to quantify the "size" of a matix o the "distance" between
TRUCK ROUTE PLANNING IN NON- STATIONARY STOCHASTIC NETWORKS WITH TIME-WINDOWS AT CUSTOMER LOCATIONS
TRUCK ROUTE PLANNING IN NON- STATIONARY STOCHASTIC NETWORKS WITH TIME-WINDOWS AT CUSTOMER LOCATIONS Hossen Jula α, Maged Dessouky β, and Petos Ioannou γ α School of Scence, Engneeng and Technology, Pennsylvana
Questions & Answers Chapter 10 Software Reliability Prediction, Allocation and Demonstration Testing
M13914 Questions & Answes Chapte 10 Softwae Reliability Pediction, Allocation and Demonstation Testing 1. Homewok: How to deive the fomula of failue ate estimate. λ = χ α,+ t When the failue times follow
Can Auto Liability Insurance Purchases Signal Risk Attitude?
Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang
Uniform Rectilinear Motion
Engineeing Mechanics : Dynamics Unifom Rectilinea Motion Fo paticle in unifom ectilinea motion, the acceleation is zeo and the elocity is constant. d d t constant t t 11-1 Engineeing Mechanics : Dynamics
PRACTICE 1: MUTUAL FUNDS EVALUATION USING MATLAB.
PRACTICE 1: MUTUAL FUNDS EVALUATION USING MATLAB. INDEX 1. Load data usng the Edtor wndow and m-fle 2. Learnng to save results from the Edtor wndow. 3. Computng the Sharpe Rato 4. Obtanng the Treynor Rato
FAIR VALUATION OF VARIOUS PARTICIPATION SCHEMES IN LIFE INSURANCE ABSTRACT
FAIR VALUAION OF VARIOUS PARIIPAION SHEMES IN LIFE INSURANE PIERRE DEVOLDER AND INMAULADA DOMÍNGUEZ-FABIÁN BY Insttut des Scences Actuaelles, Unvesté atholque de Louvan, 6 ue des Wallons, 348 Louvan la
Symmetric polynomials and partitions Eugene Mukhin
Symmetic polynomials and patitions Eugene Mukhin. Symmetic polynomials.. Definition. We will conside polynomials in n vaiables x,..., x n and use the shotcut p(x) instead of p(x,..., x n ). A pemutation
4a 4ab b 4 2 4 2 5 5 16 40 25. 5.6 10 6 (count number of places from first non-zero digit to
. Simplify: 0 4 ( 8) 0 64 ( 8) 0 ( 8) = (Ode of opeations fom left to ight: Paenthesis, Exponents, Multiplication, Division, Addition Subtaction). Simplify: (a 4) + (a ) (a+) = a 4 + a 0 a = a 7. Evaluate
Administrative Council July 28, 2010 Presented by Nancy McNerney Institutional Effectiveness Planning and Research
Administrative Council July 28, 2010 Presented by Nancy McNerney Institutional Effectiveness Planning and Research Developmental Students Today I will talk about 1. Who are they? 2. What are some facts
The force between electric charges. Comparing gravity and the interaction between charges. Coulomb s Law. Forces between two charges
The foce between electic chages Coulomb s Law Two chaged objects, of chage q and Q, sepaated by a distance, exet a foce on one anothe. The magnitude of this foce is given by: kqq Coulomb s Law: F whee
Spirotechnics! September 7, 2011. Amanda Zeringue, Michael Spannuth and Amanda Zeringue Dierential Geometry Project
Spiotechnics! Septembe 7, 2011 Amanda Zeingue, Michael Spannuth and Amanda Zeingue Dieential Geomety Poject 1 The Beginning The geneal consensus of ou goup began with one thought: Spiogaphs ae awesome.
Statistical modelling of gambling probabilities
Ttle Statstcal modellng of gamblng pobabltes Autho(s) Lo, Su-yan, Vcto.; 老 瑞 欣 Ctaton Issued Date 992 URL http://hdl.handle.net/0722/3525 Rghts The autho etans all popetay ghts, (such as patent ghts) and
Use of deviance statistics for comparing models
A likelihood-ratio test can be used under full ML. The use of such a test is a quite general principle for statistical testing. In hierarchical linear models, the deviance test is mostly used for multiparameter
NON-CONSTANT SUM RED-AND-BLACK GAMES WITH BET-DEPENDENT WIN PROBABILITY FUNCTION LAURA PONTIGGIA, University of the Sciences in Philadelphia
To appear n Journal o Appled Probablty June 2007 O-COSTAT SUM RED-AD-BLACK GAMES WITH BET-DEPEDET WI PROBABILITY FUCTIO LAURA POTIGGIA, Unversty o the Scences n Phladelpha Abstract In ths paper we nvestgate
INITIAL MARGIN CALCULATION ON DERIVATIVE MARKETS OPTION VALUATION FORMULAS
INITIAL MARGIN CALCULATION ON DERIVATIVE MARKETS OPTION VALUATION FORMULAS Vesion:.0 Date: June 0 Disclaime This document is solely intended as infomation fo cleaing membes and othes who ae inteested in
A New Estimation Model for Small Organic Software Project
8 03 ACADEMY PUBLISHER A New Estmaton Model o Small Oganc Sotwae Poject Wan-Jang Han, Tan-Bo Lu, and Xao-Yan Zhang School O Sotwae Engneeng, Bejng Unvesty o Posts and Telecommuncaton, Bejng, Chna Emal:
Faithful Comptroller s Handbook
Faithful Comptolle s Handbook Faithful Comptolle s Handbook Selection of Faithful Comptolle The Laws govening the Fouth Degee povide that the faithful comptolle be elected, along with the othe offices
The transport performance evaluation system building of logistics enterprises
Jounal of Industial Engineeing and Management JIEM, 213 6(4): 194-114 Online ISSN: 213-953 Pint ISSN: 213-8423 http://dx.doi.og/1.3926/jiem.784 The tanspot pefomance evaluation system building of logistics
Decomposing General Equilibrium Effects of Policy Intervention in Multi-Regional Trade Models
Decomosng Geneal Equlbum Effects of Polcy Inteventon n ult-regonal Tade odels ethod and Samle Alcaton by hstoh Böhnge ente fo Euoean Economc Reseach (ZEW) boehnge@zew.de and Thomas F. Ruthefod Deatment
The OC Curve of Attribute Acceptance Plans
The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4
Order-Degree Curves for Hypergeometric Creative Telescoping
Ode-Degee Cuves fo Hyegeometc Ceatve Telescong ABSTRACT Shaosh Chen Deatment of Mathematcs NCSU Ralegh, NC 7695, USA schen@ncsuedu Ceatve telescong aled to a bvaate oe hyegeometc tem oduces lnea ecuence
Carter-Penrose diagrams and black holes
Cate-Penose diagams and black holes Ewa Felinska The basic intoduction to the method of building Penose diagams has been pesented, stating with obtaining a Penose diagam fom Minkowski space. An example
Voltage ( = Electric Potential )
V-1 Voltage ( = Electic Potential ) An electic chage altes the space aound it. Thoughout the space aound evey chage is a vecto thing called the electic field. Also filling the space aound evey chage is
Statistics Norway Department of Economic Statistics
2004/3 Mach 2004 Documents Statstcs Noway Depatment of Economc Statstcs Jan Henk Wang Non-esponse n the Nowegan Busness Tendency Suvey Peface Ths pape descbes methods fo adjustng fo non-esponse set n the
OPINION DYNAMICS AND BOUNDED CONFIDENCE MODELS, ANALYSIS, AND SIMULATION
Jouna of Atfca Socetes and Soca Smuaton (JASSS) vo.5, no. 3, 02 http://jasss.soc.suey.ac.uk/5/3/2.htm OPINION DYNAMICS AND BOUNDED CONFIDENCE MODELS, ANALYSIS, AND SIMULATION Rane Hegsemann Depatment of
Institut für Halle Institute for Economic Research Wirtschaftsforschung Halle
Insttut fü Halle Insttute fo Economc Reseach Wtschaftsfoschung Halle A Smple Repesentaton of the Bea-Jaque-Lee Test fo Pobt Models Joachm Wlde Dezembe 2007 No. 13 IWH-Dskussonspapee IWH-Dscusson Papes
Reporting Forms ARF 113.0A, ARF 113.0B, ARF 113.0C and ARF 113.0D FIRB Corporate (including SME Corporate), Sovereign and Bank Instruction Guide
Reportng Forms ARF 113.0A, ARF 113.0B, ARF 113.0C and ARF 113.0D FIRB Corporate (ncludng SME Corporate), Soveregn and Bank Instructon Gude Ths nstructon gude s desgned to assst n the completon of the FIRB
AN EQUILIBRIUM ANALYSIS OF THE INSURANCE MARKET WITH VERTICAL DIFFERENTIATION
QUIIRIUM YI OF T IUR MRKT WIT VRTI IFFRTITIO Mahto Okua Faculty of conomcs, agasak Unvesty, 4-- Katafuch, agasak, 8508506, Japan okua@net.nagasak-u.ac.p TRT ach nsuance poduct pe se s dentcal but the nsuance
Solutions to Problems: Chapter 7
Solution to Poblem: Chapte 7 P7-1. P7-2. P7-3. P7-4. Authoized and available hae LG 2; Baic a. Maximum hae available fo ale Authoized hae 2,000,000 Le: Shae outtanding 1,400,000 Available hae 600,000 b.
Recurrence. 1 Definitions and main statements
Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.
On the Efficiency of Equilibria in Generalized Second Price Auctions
On the Effcency of Equlba n Genealzed Second Pce Auctons Ioanns Caaganns Panagots Kanellopoulos Chstos Kaklamans Maa Kyopoulou Depatment of Compute Engneeng and Infomatcs Unvesty of Patas and RACTI, Geece
Stress test for measuring insurance risks in non-life insurance
PROMEMORIA Datum June 01 Fnansnspektonen Författare Bengt von Bahr, Younes Elonq and Erk Elvers Stress test for measurng nsurance rsks n non-lfe nsurance Summary Ths memo descrbes stress testng of nsurance
Questions for Review. By buying bonds This period you save s, next period you get s(1+r)
MACROECONOMICS 2006 Week 5 Semina Questions Questions fo Review 1. How do consumes save in the two-peiod model? By buying bonds This peiod you save s, next peiod you get s() 2. What is the slope of a consume
Impact on inventory costs with consolidation of distribution centers
IIE Tansactons (2) 33, 99± Imact on nventoy costs wth consoldaton of dstbuton centes CHUNG PIAW TEO, JIHONG OU and MARK GOH Deatment of Decson Scences, Faculty of Busness Admnstaton, Natonal Unvesty of
Calculation of Sampling Weights
Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample
Integrating Net2 with an intruder alarm system
Net AN035 Integating Net with an intude alam system Oveview Net can monito whethe the intude alam is set o uet If the alam is set, Net will limit access to valid uses who ae also authoised to uet the alam
Drag force acting on a bubble in a cloud of compressible spherical bubbles at large Reynolds numbers
Euopean Jounal of Mechancs B/Fluds 24 2005 468 477 Dag foce actng on a bubble n a cloud of compessble sphecal bubbles at lage Reynolds numbes S.L. Gavlyuk a,b,,v.m.teshukov c a Laboatoe de Modélsaton en
Research on Risk Assessment of the Transformer Based on Life Cycle Cost
ntenational Jounal of Smat Gid and lean Enegy eseach on isk Assessment of the Tansfome Based on Life ycle ost Hui Zhou a, Guowei Wu a, Weiwei Pan a, Yunhe Hou b, hong Wang b * a Zhejiang Electic Powe opoation,
Addendum to: Importing Skill-Biased Technology
Addendum to: Importng Skll-Based Technology Arel Bursten UCLA and NBER Javer Cravno UCLA August 202 Jonathan Vogel Columba and NBER Abstract Ths Addendum derves the results dscussed n secton 3.3 of our
High Availability Replication Strategy for Deduplication Storage System
Zhengda Zhou, Jingli Zhou College of Compute Science and Technology, Huazhong Univesity of Science and Technology, *, zhouzd@smail.hust.edu.cn jlzhou@mail.hust.edu.cn Abstact As the amount of digital data
Quantity Formula Meaning of variables. 5 C 1 32 F 5 degrees Fahrenheit, 1 bh A 5 area, b 5 base, h 5 height. P 5 2l 1 2w
1.4 Rewite Fomulas and Equations Befoe You solved equations. Now You will ewite and evaluate fomulas and equations. Why? So you can apply geometic fomulas, as in Ex. 36. Key Vocabulay fomula solve fo a
Data Dashboards Using Excel and MS Word. Dr. Rosemarie O Conner Gabriel Hartmann
Data Dashboards Using Excel and MS Word Dr. Rosemarie O Conner Gabriel Hartmann Agenda Introduction to Dashboards Automation Process Demonstration 4 steps: 1. Design a dashboard 2. Create Word Template
Time Value of Money. Types of Interest. Compounding and Discounting Single Sums. Page 1. Ch. 6 - The Time Value of Money. The Time Value of Money
Ch. 6 - The Tme Value of Money Tme Value of Money The Interest Rate Smple Interest Compound Interest Amortzng a Loan FIN21- Ahmed Y, Dasht TIME VALUE OF MONEY OR DISCOUNTED CASH FLOW ANALYSIS Very Important
NURBS Drawing Week 5, Lecture 10
CS 43/585 Compute Gaphics I NURBS Dawing Week 5, Lectue 1 David Been, William Regli and Maim Pesakhov Geometic and Intelligent Computing Laboato Depatment of Compute Science Deel Univesit http://gicl.cs.deel.edu
1240 ev nm 2.5 ev. (4) r 2 or mv 2 = ke2
Chapte 5 Example The helium atom has 2 electonic enegy levels: E 3p = 23.1 ev and E 2s = 20.6 ev whee the gound state is E = 0. If an electon makes a tansition fom 3p to 2s, what is the wavelength of the
AN IMPLEMENTATION OF BINARY AND FLOATING POINT CHROMOSOME REPRESENTATION IN GENETIC ALGORITHM
AN IMPLEMENTATION OF BINARY AND FLOATING POINT CHROMOSOME REPRESENTATION IN GENETIC ALGORITHM Main Golub Faculty of Electical Engineeing and Computing, Univesity of Zageb Depatment of Electonics, Micoelectonics,
DEFINING %COMPLETE IN MICROSOFT PROJECT
CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,
There is considerable variation in health care utilization and spending. Geographic Variation in Health Care: The Role of Private Markets
TOMAS J. PHILIPSON Univesity of Chicago SETH A. SEABUY AND Copoation LEE M. LOCKWOOD Univesity of Chicago DANA P. GOLDMAN Univesity of Southen Califonia DAIUS N. LAKDAWALLA Univesity of Southen Califonia
Chapter 3 Savings, Present Value and Ricardian Equivalence
Chapte 3 Savings, Pesent Value and Ricadian Equivalence Chapte Oveview In the pevious chapte we studied the decision of households to supply hous to the labo maket. This decision was a static decision,
Introduction to Data Analysis in Hierarchical Linear Models
Introduction to Data Analysis in Hierarchical Linear Models April 20, 2007 Noah Shamosh & Frank Farach Social Sciences StatLab Yale University Scope & Prerequisites Strong applied emphasis Focus on HLM
Seshadri constants and surfaces of minimal degree
Seshadi constants and sufaces of minimal degee Wioletta Syzdek and Tomasz Szembeg Septembe 29, 2007 Abstact In [] we showed that if the multiple point Seshadi constants of an ample line bundle on a smooth
AMB111F Financial Maths Notes
AMB111F Financial Maths Notes Compound Inteest and Depeciation Compound Inteest: Inteest computed on the cuent amount that inceases at egula intevals. Simple inteest: Inteest computed on the oiginal fixed
Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
JFET AMPLIFIER CONFIGURATIONS
JFET MPFE CONFGUTON 5 5 5 n G OUT n G OUT n OUT [a] Cn urce plfer [b] Cn ran [urce Fllwer] plfer [c] Cn Gate plfer Cte a: n ce, cure ateral fr 6.0 ntructry nal Electrnc abratry, prn 2007.MT OpenCureWare
Skills Needed for Success in Calculus 1
Skills Needed fo Success in Calculus Thee is much appehension fom students taking Calculus. It seems that fo man people, "Calculus" is snonmous with "difficult." Howeve, an teache of Calculus will tell
Valuation of Floating Rate Bonds 1
Valuation of Floating Rate onds 1 Joge uz Lopez us 316: Deivative Secuities his note explains how to value plain vanilla floating ate bonds. he pupose of this note is to link the concepts that you leaned
Derivation of Humidty and NOx Humidty Correction Factors
(Ths document follows the presentatons n "Vapor Pressure Equaton for Water n the Range 0 to 00 C", by Arnold Wexler and Lews Greenspan, February 9, 97 JOURNAL OF RESEARCH of the Natonal Bureau of Standards
21 Vectors: The Cross Product & Torque
21 Vectors: The Cross Product & Torque Do not use our left hand when applng ether the rght-hand rule for the cross product of two vectors dscussed n ths chapter or the rght-hand rule for somethng curl
Concept and Experiences on using a Wiki-based System for Software-related Seminar Papers
Concept and Expeiences on using a Wiki-based System fo Softwae-elated Semina Papes Dominik Fanke and Stefan Kowalewski RWTH Aachen Univesity, 52074 Aachen, Gemany, {fanke, kowalewski}@embedded.wth-aachen.de,
Explicit, analytical solution of scaling quantum graphs. Abstract
Explicit, analytical solution of scaling quantum gaphs Yu. Dabaghian and R. Blümel Depatment of Physics, Wesleyan Univesity, Middletown, CT 06459-0155, USA E-mail: ydabaghian@wesleyan.edu (Januay 6, 2003)
The impact of migration on the provision. of UK public services (SRG.10.039.4) Final Report. December 2011
The impact of migation on the povision of UK public sevices (SRG.10.039.4) Final Repot Decembe 2011 The obustness The obustness of the analysis of the is analysis the esponsibility is the esponsibility
Data Mining from the Information Systems: Performance Indicators at Masaryk University in Brno
Data Mnng from the Informaton Systems: Performance Indcators at Masaryk Unversty n Brno Mkuláš Bek EUA Workshop Strasbourg, 1-2 December 2006 1 Locaton of Brno Brno EUA Workshop Strasbourg, 1-2 December
Virtual Parental Involvement: The Role of the Internet in Parent-School Communications
Virtual Parental Involvement: The Role of the Internet in Parent-School Communications Suzanne M. Bouffard Department of Psychology, Duke University & Harvard Family Research Project, Harvard Graduate
Optimal maintenance of a production-inventory system with continuous repair times and idle periods
Proceedngs o the 3 Internatonal Conerence on Aled Mathematcs and Comutatonal Methods Otmal mantenance o a roducton-nventory system wth contnuous rear tmes and dle erods T. D. Dmtrakos* Deartment o Mathematcs
Efficient Evolutionary Data Mining Algorithms Applied to the Insurance Fraud Prediction
Intenatonal Jounal of Machne Leanng and Computng, Vol. 2, No. 3, June 202 Effcent Evolutonay Data Mnng Algothms Appled to the Insuance Faud Pedcton Jenn-Long Lu, Chen-Lang Chen, and Hsng-Hu Yang Abstact
Transmittal 198 Date: DECEMBER 9, 2005. SUBJECT: Termination of the Existing Eligibility-File Based Crossover Process at All Medicare Contractors
anual ystem Depatment of ealth & uman evices (D) entes fo edicae & Pub 100-20 One-Time Notification edicaid evices () Tansmittal 198 Date: DEEBE 9, 2005 hange equest 4231 UBJET: Temination of the Existing
Coordinate Systems L. M. Kalnins, March 2009
Coodinate Sstems L. M. Kalnins, Mach 2009 Pupose of a Coodinate Sstem The pupose of a coodinate sstem is to uniquel detemine the position of an object o data point in space. B space we ma liteall mean
2. TRIGONOMETRIC FUNCTIONS OF GENERAL ANGLES
. TRIGONOMETRIC FUNCTIONS OF GENERAL ANGLES In ode to etend the definitions of the si tigonometic functions to geneal angles, we shall make use of the following ideas: In a Catesian coodinate sstem, an