Comparative Estimation Systems and the Random Coefficient Regression Approach

2021 ◽  
pp. 67-79
Author(s):  
Robert H. Hornbaker ◽  
Steven T. Sonka ◽  
Bruce L. Dixon
Author(s):  
Giovanni Cerulli

rscore computes unit-specific responsiveness scores using an iterated random-coefficient regression approach. The model fit by rscore considers a regression of a response variable y, that is, outcome, on a series of factors (or regressors) x, that is, varlist, by assuming a different reaction (or “responsiveness”) of each unit to each factor contained in x. rscore allows for i) ranking units according to the obtained level of the responsiveness score; ii) detecting more influential factors in driving unit performance; and iii) studying the distribution (heterogeneity) of factors’ responsiveness scores across units. Also, rscore offers useful graphical representation of results. We provide two illustrative applications of the model: the first is on a cross-section, and the second is on a longitudinal dataset.


BMC Genetics ◽  
2003 ◽  
Vol 4 (Suppl 1) ◽  
pp. S5 ◽  
Author(s):  
Jonathan Corbett ◽  
Aldi Kraja ◽  
Ingrid B Borecki ◽  
Michael A Province

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