Proportionate Reduction In Error Regression
Contents |
PRE proportionate reduction in error definition measures. Proportional Reduction of Error (PRE) The proportionate reduction in error symbol concept that underlies the definition and interpretation of several measures regression to the mean occurs because extreme scores tend to become: of association, PRE measures are derived by comparing the errors made in predicting the dependent while ignoring the
Moderately Strong Correlation
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 if the standard error of the estimate is zero, the relation between two variables is: 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
one another? We need a summary measure; we can't just reproduce the table in our articles and reports. General principle of PRE measures: does knowing the value of a case on one variable help you to predict its value on the other, that is, proportionate reduction in error can be symbolized by help you as compared to not knowing its value? General PRE Formula: (error before -
The Standard Error Of The Estimate Indicates:
error after) / (error before) So: each specific PRE formula has three elements: How shall we measure error in prediction for each case,
Proportional Reduction In Error Lambda
or what will count as an error? How shall we predict the dependent variable before knowing the independent variable? In general, we use the prediction method which minimizes our total error (subject perhaps to side constraints). How shall we https://learn.bu.edu/bbcswebdav/pid-826908-dt-content-rid-2073693_1/courses/13sprgmetcj702_ol/week05/metcj702_W05S03T02_proportional.html predict the dependent variable after knowing the independent variable? Notice that this measure always varies between 0 and 1. 0 occurs when error before = error after, in other words, when knowing the independent variable doesn't help us predict. In other words, 0 means no association. 1 occurs when error after = 0, i.e., when knowing the independent variable enables us to make a perfect prediction of the dependent variable. In other words, 1 means perfect association. http://www.d.umn.edu/~schilton/2700/LectureNotes/PREsynopsis.html Can there ever be a negative measure? No, because you can't predict worse than by not knowing anything. Can there ever be a measure greater than 100%? No, because that would mean errors after would have to be negative, and there's no such thing as a negative error. We're going to study three measures: Lambda for nominal, Pearson's r-squared for interval, and gamma for ordinal. LAMBDA: A PRE MEASURE FOR NOMINAL VARIABLES For the specific example of nominal variables, the elements of this formula come out as follows: How shall we measure error in prediction, or what will count as an error? Answer: Having our prediction wrong counts as one error. Having it right counts as no errors. For nominal variables, that's the only possible definition of an error. How shall we predict the dependent variable before knowing the independent variable? Answer: We use the mode, which is the prediction method which minimizes the error. How shall we predict the dependent variable after knowing the independent variable? Answer: We use the mode for each category of the independent variable. This measure is called lambda. There are other (and better) measures of association for nominal variables, but this is the simplest. Let's apply this to the table I showed last time: Parents lean: Democrat Republican Total Children lean Democrat 11 (79%) 7 (26%) 18 (44%) Republican 3 (21% 20 (
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 https://books.google.gr/books?id=G8fhqL9xHOAC&pg=PA101&lpg=PA101&dq=proportionate+reduction+in+error+regression&source=bl&ots=LwmB1XpeAV&sig=jAR6sCEYDfkJf0TIMjrJG12J-rc&hl=en&sa=X&ved=0ahUKEwiR5OvR5ejPAhXiB5oKHfZyCcsQ6A Content Type BooksLittle Green BooksLittle Blue BooksReferenceJournal ArticlesDatasetsCasesVideo Browse Topic Key concepts in researchPhilosophy of researchResearch 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 Science reduction in 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 Download PDF reduction in error 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 ModelAsymmetric MeasuresBiserial CorrelationCanonical Correlation AnalysisCorrelationCor
εμάς.Μάθετε περισσότερα Το κατάλαβαΟ λογαριασμός μουΑναζήτησηΧάρτεςYouTubePlayΕιδήσειςGmailDriveΗμερολόγιοGoogle+ΜετάφρασηΦωτογραφίεςΠερισσότεραΈγγραφαBloggerΕπαφέςHangoutsΑκόμη περισσότερα από την GoogleΕίσοδοςΚρυφά πεδίαΒιβλίαbooks.google.gr - The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information...https://books.google.gr/books/about/Multilevel_Analysis.html?hl=el&id=G8fhqL9xHOAC&utm_source=gb-gplus-shareMultilevel AnalysisΗ βιβλιοθήκη μουΒοήθειαΣύνθετη Αναζήτηση ΒιβλίωνΑποκτήστε το εκτυπωμένο βιβλίοΔεν υπάρχουν διαθέσιμα eBookΕλευθερουδάκηςΠαπασωτηρίουΕύρεση σε κάποια βιβλιοθήκηΌλοι οι πωλητές»Αγορά βιβλίων στο Google PlayΠεριηγηθείτε στο μεγαλύτερο ηλεκτρονικό βιβλιοπωλείο του κόσμου και ξεκινήστε να διαβάζετε σήμερα στον ιστό, το tablet, το τηλέφωνο ή το ereader σας.Άμεση μετάβαση στο Google Play »Multilevel Analysis: An Introduction to Basic and Advanced Multilevel ModelingProfessor Tom A B a B Snijders, Tom A. B. Snijders Roel J. Bosker, Professor Roel J BoskerSAGE, 29 Σεπ 1999 - 272 σελίδες 0 Κριτικέςhttps://books.google.gr/books/about/Multilevel_Analysis.html?hl=el&id=G8fhqL9xHOACThe main methods, techniques and issues for carrying ou