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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.
Normality - Reasons for Screening Data Prior to analyzing multivariate normality, one should consider univariate normality Histogram, Normal Q-Qplot (values on x axis
Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in
Cause specific death rate : A death rate calculated for the people dying from the specific disease. For instance, the below given are the rates per 1000 people for three disease cl
Reasons for screening data Garbage in-garbage out Missing data a. Amount of missing data is less crucial than the pattern of it. If randomly
Looking for the correct answer.Y=50+.079(149)-.261(214)=
Surveys which use lists related with the vital statistics to sample individuals for the further information. For instance, the 1988 National Mortality Follow back Survey sampled de
#how to analyse data
Over dispersion is the phenomenon which occurs when empirical variance in the data exceeds the nominal variance under some supposed model. Most often encountered when the modeling
Multiple correlation coefficient is the correlation among the observed values of dependent variable in the multiple regression, and the values predicted by estimated regression
I want to get the quotation of my on-line assignment its based on 1000 words. lecturer provide the video links and we have to watch the videos and highlights the key points also de
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