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PC program for assessing the effect of a treatment when subjects are growing: comparative studies
We describe, illustrate, and make available a menu-driven PC program which can be used to assess the effect of a treatment on growth when random allocation of subjects to the treatment and control groups is not feasible. Three different estimators of, and confidence intervals for, this effect are co...
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Published in: | International journal of bio-medical computing 1995-03, Vol.38 (3), p.217-224 |
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container_end_page | 224 |
container_issue | 3 |
container_start_page | 217 |
container_title | International journal of bio-medical computing |
container_volume | 38 |
creator | Kowalskia, Charles J. Schneiderman, Emet D. Willis, Stephen M. |
description | We describe, illustrate, and make available a menu-driven PC program which can be used to assess the effect of a treatment on growth when random allocation of subjects to the treatment and control groups is not feasible. Three different estimators of, and confidence intervals for, this effect are computed, namely, the simple gains, standardized gains, and covariance adjusted estimators. It is shown by means of several examples that these estimators can differ substantially, and some guidelines for choosing between them in specific circumstances are provided. |
doi_str_mv | 10.1016/S0020-7101(05)80003-0 |
format | article |
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ispartof | International journal of bio-medical computing, 1995-03, Vol.38 (3), p.217-224 |
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language | eng |
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source | ScienceDirect Journals |
subjects | Analysis of Variance Animals Bias reduction Biological and medical sciences Body Weight - drug effects Child Computer Simulation Computerized, statistical medical data processing and models in biomedicine Confidence Intervals Growth Growth - drug effects Humans Jackknife Linear Models Mathematical Computing Medical sciences Medical statistics Microcomputers Rats Regression to mean Software Thyroxine - pharmacology Treatment effects Treatment Outcome User-Computer Interface |
title | PC program for assessing the effect of a treatment when subjects are growing: comparative studies |
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