Proportionate Reduction Of Error
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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
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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
of making observations which are possibly subject to errors of all types. Such measures quantify how much having the observations available has reduced the loss proportionate reduction in error can be symbolized by (cost) of the uncertainty about the intended quantity compared with not having
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those observations. Proportional reduction in error is a more restrictive framework widely used in statistics, in which regression to the mean occurs because extreme scores tend to become: the general loss function is replaced by a more direct measure of error such as the mean square error. Examples are the coefficient of determination and Goodman and Kruskal's https://learn.bu.edu/bbcswebdav/pid-826908-dt-content-rid-2073693_1/courses/13sprgmetcj702_ol/week05/metcj702_W05S03T02_proportional.html lambda.[1] The concept of proportional reduction in loss was proposed by Bruce Cooil and Roland T. Rust in their 1994 paper. Many commonly used reliability measures for quantitative data (such as continuous data in an experimental design) are PRL measures, including Cronbach's alpha and measures proposed by Ben J. Winer (1971). It also provides a general way of https://en.wikipedia.org/wiki/Proportional_reduction_in_loss developing measures for the reliability of qualitative data. For example, this framework provides several possible measures that are applicable when a researcher wants to assess the consensus between judges who are asked to code a number of items into mutually exclusive qualitative categories (Cooil and Rust, 1995). Measures of this latter type have been proposed by several researchers, including Perrault and Leigh (1989). References[edit] ^ Upton G., Cook, I. (2006) Oxford Dictionary of Statistics, OUP. ISBN 978-0-19-954145-4 Cooil, B., and Rust, R. T. (1994), "Reliability and Expected Loss: A Unifying Principle," Psychometrika, 59, 203-216. (available here) Cooil, B., and Rust, R. T. (1995), "General Estimators for the Reliability of Qualitative Data," Psychometrika, 60, 199-220. (available here) Rust, R. T., and Cooil, B. (1994), "Reliability Measures for Qualitative Data: Theory and Implications," Journal of Marketing Research, 31(1), 1-14. (available here) Winer, B.J. (1971), Statistical Principles in Experimental Design. New York: McGraw-Hill. Perreault, W.D. and Leigh, L.E. (1989), “Reliability of Nominal Data Based on Qualitative Judgments,” Journal of Marketing Research, 26, 135-148 Retrieved from "https://en.wikipedia.org
Login Help Contact Us About Access You are not currently logged in. Access your personal account or get JSTOR access through your library or other institution: login Log in to your personal https://www.jstor.org/stable/4106125 account or through your institution. The Sociological Quarterly Vol. 22, No. 3, Summer, 1981 Interpreting Proport... Interpreting Proportional Reduction in Error Measures as Percentage of Variation Explained Frederick J. Kviz The Sociological Quarterly Vol. 22, No. 3 (Summer, 1981), pp. 413-420 Published by: Wiley on behalf of the Midwest Sociological Society Stable URL: http://www.jstor.org/stable/4106125 Page Count: 8 Download ($14.00) Subscribe ($19.50) Cite this Item Cite This Item Copy Citation Export reduction in Citation Export to RefWorks Export a RIS file (For EndNote, ProCite, Reference Manager, Zotero…) Export a Text file (For BibTex) Note: Always review your references and make any necessary corrections before using. Pay attention to names, capitalization, and dates. × Close Overlay Journal Info The Sociological Quarterly Description: The Sociological Quarterly is devoted to publishing cutting-edge research and theory in all areas of sociological inquiry. Our focus is on publishing the reduction in error best in sociological research and writing to advance the discipline and reach the widest possible audience. Since 1960, the contributors and readers of The Sociological Quarterly have made it one of the leading generalist journals in the field. Each issue is designed for efficient browsing and reading and the articles are helpful for teaching and classroom use. Coverage: 1960-2010 (Vol. 1, No. 1 - Vol. 51, No. 4) Moving Wall Moving Wall: 5 years (What is the moving wall?) Moving Wall The "moving wall" represents the time period between the last issue available in JSTOR and the most recently published issue of a journal. Moving walls are generally represented in years. In rare instances, a publisher has elected to have a "zero" moving wall, so their current issues are available in JSTOR shortly after publication. Note: In calculating the moving wall, the current year is not counted. For example, if the current year is 2008 and a journal has a 5 year moving wall, articles from the year 2002 are available. Terms Related to the Moving Wall Fixed walls: Journals with no new volumes being added to the archive. Absorbed: Journals that are combined with another title. Complete: Journals that are no longer published or that have been combined wit