Unobserved data, treatment

The treatment of unobserved data is of necessity different from that given to observed data. For these data there is only a threshold intensity with which to compare the calculated value, and it becomes necessary to define a number, f, such that flQ(m) is the most probable value of the observed intensity, where Io(ki) is now the minimum Intensity which the m observation would have to display in order to be detectable above background scattering (it has been shown that f = 0.33... 

Traditional (ANOVA) analysis of analgesic clinical trials (i.e., testing the null hypothesis when comparing treatment and placebo groups) have dealt inadequately with the complexities of pain relief data collected in these studies (3, 15). When patients have required rescue medication before the end of the study, scores of unobserved subsequent pain and pain relief (PR) scores have historically been imputed according to predetermined rules such as the so-called last observation... 

The program is extremely well suited for the determination of polymer structures in its treatment of unobserved and overlapping data. Standard least squares treatments assume that only one reflection contributes to any given observation due to the cylindrical symmetry of fiber diffraction patterns a great many of the observations are actually superpositions of two or more reflections, Under these circumstances the observed intensity must be compared to the sum of the contributing calculated intensities. Thus, if c[ independent reflections contribute to the m observation, then... 

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