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The type of longitudinal study in which the subjects receive different treatments on the various occasions. Random allocation is required to determine the order in which the treatments are received. The simplest such design includes two groups of the subjects, one of which receives each of the two treatments, A and B, in the order AB, while the other takes them in the reverse order. This is called as a two-by-two crossover design. While the treatment comparison is 'within-subject' rather than the 'between-subject', it is likely to need fewer subjects to achieve the given power. The study of such designs is not necessarily straight- forward because of the possibility of the carryover effects, that is left over effects of the treatment received on the first occasion which remain present into the second occasion. An attempt to minimize this problem is many times made by including the wash-out period between the two treatment occasions. Some of the authorities have suggested that this type of design should only be used if such carryover effects can be ruled out a priori. Crossover designs are only applicable to the chronic conditions for which short-term relief of the symptoms is the goal rather than a cure of it.
Harris and Stevens forecasting is the method of making short term forecasts in the time series which is subject to abrupt changes in pattern and the transient effects. Instances o
Described by the leading proponent as 'the conscientious, explicit, and judicious uses of present best evidence in making the decisions about the care of individual patients, and
Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal br
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Banach's match-box problem : The person carries two boxes of matches, one in his left and one in his right pocket. At first they comprise N number of matches each. When the person
A comprehensive regression analysis of the case study London has been carried out to test the 4 assumptions of regression: 1. Variables are normally distributed 2. Linear rel
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