Tests for simple treatment comparisons

CH04 TESTS FOR SIMPLE TREATMENT COMPARISONS Table 4.5 Data for fisher s exact test... 

Note that the testing for trend is seen as a more sensitive way of picking up a possible treatment effect than simple pairwise comparisons of treated and control groups. Attempting to estimate the magnitude of effects at low doses, typically below the lowest positive dose tested in the study, is a much more complex procedure, and is heavily dependent on the assumed functional form of the dose-response relationship. 

Statistical rate theories often are also formulated using variational principles. Like the adiabatic principle, variational principles are intuitive and have to be proven (or disproven) by comparison with true dynamical treatments. As SACM in the previous chapters has been shown to give identical results with trajectory calculations at high temperature for the considered simple reaction system, differences between SACM and VTST would speak against the latter. The charge-dipole system, because of its simplicity, can be used particularly well for a quantitative comparison between SACM and VTST and, hence, for a quantitative test of VTST. 

The proportional hazards model, as the name suggests, assumes that the hazard ratio is a constant. As such it provides a direct extension of the logrank test, which is a simple two treatment group comparison. Indeed if the proportional hazards model is fitted to data without the inclusion of baseline factors then the p-value for the test Hg c = 0 will be essentially the same as the p-value arising out of the logrank test. 

Do simple statistical tests. Average food consumption for the 20-min periods on each day. Use Friedman s two-way analysis of variance for randomized blocks (the days are the blocks, constituting one factor, the treatments are the second factor) followed by pairwise comparisons. Compare two treatments of particular interest, such as lowest MA concentration vs. EtOH only. 

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