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Let Continuous Outcome Variables Remain Continuous
Author(s) -
Enayatollah Bakhshi,
Brian H. McArdle,
Kazem Mohammad,
Behjat Seifi,
Akbar Biglarian
Publication year - 2012
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2012/639124
Subject(s) - estimator , outcome (game theory) , sample size determination , mathematics , statistics , continuous variable , computer science , sample (material) , data mining , chemistry , mathematical economics , chromatography
The complementary log-log is an alternative to logistic model. In many areas of research, the outcome data are continuous. We aim to provide a procedure that allows the researcher to estimate the coefficients of the complementary log-log model without dichotomizing and without loss of information. We show that the sample size required for a specific power of the proposed approach is substantially smaller than the dichotomizing method. We find that estimators derived from proposed method are consistently more efficient than dichotomizing method. To illustrate the use of proposed method, we employ the data arising from the NHSI.

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