Let Continuous Outcome Variables Remain Continuous
| Autor: | Akbar Biglarian, Brian H. McArdle, Enayatollah Bakhshi, Kazem Mohammad, Behjat Seifi |
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| Rok vydání: | 2012 |
| Předmět: |
Adult
Mathematical optimization Article Subject Biostatistics lcsh:Computer applications to medicine. Medical informatics Logistic regression General Biochemistry Genetics and Molecular Biology Body Mass Index Odds Ratio Econometrics Humans Computer Simulation Obesity Aged Mathematics Likelihood Functions Models Statistical General Immunology and Microbiology Applied Mathematics Estimator Regression analysis General Medicine Middle Aged Models Theoretical Outcome (probability) Sample size determination Modeling and Simulation lcsh:R858-859.7 Regression Analysis Outcome data Algorithms Research Article |
| Zdroj: | Computational and Mathematical Methods in Medicine Computational and Mathematical Methods in Medicine, Vol 2012 (2012) |
| ISSN: | 1748-6718 1748-670X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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