NARA Discovery
Article Details
← Back to Search Results
Journal Article

Regression Estimation Following the Square-Root Transformation of the Response

Timothy G. Gregoire; Qi Feng Lin; Johnathan Boudreau; Ross Nelson
Forest Science · Vol. 54, Issue 6 · pp. 597-606 · 2008

Abstract

In a variety of regression situations, there is interest in predicting the value of Y2, yet it is useful to model it using a square root transformation, such that Y rather than Y2 is regressed on one or more covariates. The back-transformation bias of the square root transformation of the response variable of interest is presented in detail. An unbiased estimator is presented: . Its performance is compared against that of two biased estimators: and . The first two moments of these estimators are derived analytically and verified by means of a simulation study. Both biased estimators have lower mean square errors than the unbiased estimator. An example wherein aboveground biomass is the response variable is presented for illustration.

Bibliographic Information

JournalForest Science
PublisherSpringer
Publication Date2008-10-01
Publication Year2008
Volume54
Issue6
Pages597-606
Document TypeJournal Article
Print ISSN0015-749X
eISSN1938-3738
DOI10.1093/forestscience/54.6.597

Access Information

NARA Access Coverage1955-01-01~Current
Journal Homepagehttps://www.springer.com/journal/44391
Publisher PageOpen Publisher Page
Full-text access depends on NARA's subscribed coverage and institutional access.