Proportionate Reduction In Error
Contents |
PRE proportional reduction in error lambda measures. Proportional Reduction of Error (PRE) The
The Proportionate Reduction In Error Is A Measure Of The Quizlet
concept that underlies the definition and interpretation of several measures proportionate reduction in error symbol of association, PRE measures are derived by comparing the errors made in predicting the dependent while ignoring the
Proportional Reduction Calculator
independent variable with errors made when making predictions that use information about the independent variable. E1 = errors of prediction made when the independent variable is ignored E2 = errors of prediction made when the prediction proportional reduction in error stata is based on the independent variable "All PRE measures are based on comparing predictive error levels that result from each of two methods of prediction" (Frankfort-Nachmias and Leon-Guerrero 2011:366). Table 12.1 on page 366 of the textbook helps us to understand this. The independent variable is number of children; the dependent variable is support for abortion. Content on this page requires a newer version of Adobe Flash Player. Two of the most commonly used PRE measures of association are lambda (λ) and gamma (γ). Two PRE Measures: Lambda and Gamma Lambda λ Appropriate for: Nominal Variables Gamma γ Appropriate for: Ordinal and Dichotomous Nominal Variables
or Create About News Subscriber Services Contact Us Help
Proportionate Reduction In Error Can Be Symbolized By
For Authors: A Community of Experts Oxford Reference Publications
Proportional Reduction In Error Spss
Pages Publications Pages Help Search within my subject specializations: Select ... regression to the mean occurs because extreme scores tend to become: Select your specializations: Select All / Clear Selections Archaeology Art & Architecture Bilingual dictionaries Classical studies Encyclopedias Geographical reference https://learn.bu.edu/bbcswebdav/pid-826908-dt-content-rid-2073693_1/courses/13sprgmetcj702_ol/week05/metcj702_W05S03T02_proportional.html English Dictionaries and Thesauri History Ancient history (non-classical to 500 CE) Early history (500 CE to 1500) Early Modern History (1500 to 1700) modern history (1700 to 1945) Contemporary History (post 1945) Military History Regional and National History Local and http://www.oxfordreference.com/view/10.1093/oi/authority.20110803100349896 Family History Language reference History of English Usage and Grammar Guides Writing and Editing Guides Law History of Law Human Rights and Immigration International Law Linguistics Literature Bibliography Children's literature studies Literary studies (early and medieval) Literary studies (19th century) Literary studies (20th century onwards) Literary studies - fiction, novelists, and prose writers Literary studies - plays and playwrights Literary studies - poetry and poets Literary theory and cultural studies Shakespeare studies and criticism Media studies Medicine and health Clinical Medicine Dentistry Public Health and Epidemiology Surgery Psychiatry Music Opera Names studies Performing arts Dance Theatre Philosophy Quotations Religion Science and technology Astronomy and Cosmology Chemistry Earth Scien
Login Username Password Remember me? Forgot your login information? Reset your password Other Login Options OpenAthens Shibboleth Can't login? Find out http://methods.sagepub.com/reference/the-sage-encyclopedia-of-social-science-research-methods/n765.xml how to access the site Search form Advanced Back Browse Browse Content Type BooksLittle Green BooksLittle Blue BooksReferenceJournal ArticlesDatasetsCasesVideo Browse Topic Key concepts in researchPhilosophy of researchResearch http://faculty.washington.edu/ddbrewer/s231/s231regr.htm ethicsPlanning researchResearch designData collectionData quality and data managementQualitative data analysisQuantitative data analysisWriting and disseminating research Browse Discipline AnthropologyBusiness and ManagementCriminology and Criminal JusticeCommunication and Media StudiesCounseling and PsychotherapyEconomicsEducationGeographyHealthHistoryMarketingNursingPolitical reduction in Science and International RelationsPsychologySocial Policy and Public PolicySocial WorkSociology AnthropologyBusiness and ManagementCriminology and Criminal JusticeCommunication and Media StudiesCounseling and PsychotherapyEconomicsEducationGeographyHealthHistoryMarketingNursingPolitical Science and International RelationsPsychologySocial Policy and Public PolicySocial WorkSociology Research Tools Methods Map Reading Lists Proportional Reduction Of Error (PRE) | The SAGE Encyclopedia of Social Science Research Methods Search form Not Found Show page numbers reduction in error Download PDF Sections Menu Opener Search form icon-arrow-top icon-arrow-top Page Site Advanced 7 of 230 Not Found Opener Sections within this page Sections Proportional Reduction Of Error (PRE) In: The SAGE Encyclopedia of Social Science Research Methods Encyclopedia By: Scott Menard Edited by: Michael S. Lewis-Beck, Alan Bryman & Tim Futing Liao Published: 2004 DOI: http://dx.doi.org/10.4135/9781412950589.n765 +- LessMore information Print ISBN: 9780761923633 | Online ISBN: 9781412950589 Online Publication Date: January 1, 2011 Disciplines: Anthropology, Business and Management, Communication and Media Studies, Criminology and Criminal Justice, Economics, Education, Geography, Health, History, Marketing, Nursing, Political Science and International Relations, Psychology, Social Policy and Public Policy, Social Work, Sociology Buy in print Entry Reader’s Guide Entries A-Z Subject Index Search form Not Found Download PDF Show page numbers Looks like you do not have access to this content. Please login or find out how to gain access. Analysis of VarianceAnalysis of Covariance (ANCOVA)Analysis of Variance (ANOVA)Main EffectModel I ANOVAModel II ANOVAModel III ANOVAOne-Way ANOVATwo-Way ANOVAAssociation and CorrelationAssociationAssociation Model
interval data X-axis = i.v., Y-axis = d.v. direction: positive (up to the right), negative (down to the right) using X to predict Y line summarizes relationship simple linear regression equation: Y = a + bX a = Y-intercept value of Y when line crosses Y-axis (i.e., when X = 0) b = slope change in Y with a unit change in X (rise/run) regression line minimizes squared errors (least squares line) SSE = sum of squared errors MSE = mean squared error errors in prediction = residuals Issues to consider: influence of outliers - outliers can suppress or drive relationships nonlinear relationships - linear regression based on assumption of linearity extrapolation - predicting y based on regression equation and x outside of observed range of x values - be careful! heteroschedasticity - errors in prediction vary over range of values Correlation strength of association - degree of clustering about line r2 as a PRE measure - strength of association Proportional Reduction in Error (PRE) PRE = (E1 - E2) / E1 E1 = errors in predicting d.v. based on distribution of d.v. E2 = errors in predicting d.v. when prediction is based on i.v. ranges between 0 and 1 how much can we reduce errors in predicting d.v. by considering i.v.? 100% reduction (1.0) - perfect prediction 0% reduction (0.0) - i.v. does not help in predicting r2: E1 = predict values of Y based on Y bar (mean) sum of (Y - Y bar)2 E2: predict Y based on X and regression line sum of (Y - Y hat)2 (deviation of observed Y from regression line, squared) Correlation: r Pearson correlation coefficient or product-moment coefficient indicates how closely observed values fall around regression line/clustering about line & direction of association r = square root of r2 and takes sign of slope ranges between -1 and 1 negative r = negative relationship positive r = positive relationship 0 = no relationship strength of r which is stronger: -.2 or +.1? -.5 or +.75? absolute value of r indicates strength general guide for interpreting strength of r (absolute value) 0 - .2 = weak, slight .2 - .4 = mild/modest .4 - .6 = moderate .6 - .8 = moderately strong .8 - 1.0 = strong r standardizes the degree of association, regardless of units of measurement one approach to computing r: standardize each case's value on x and y: (X - X bar) / s.d. on X (Y - Y bar) / s.d. on Y for each case, multiply st