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Matching is the method of making a study group and a comparison group comparable with respect to the extraneous factors. Generally used in the retrospective studies when selecting cases and controls to control variation in a response variable due to sources other than those which are taken immediately under investigation. Numerous kinds of matching can be recognized, the most common of which is when each case is individually matched with the control subject on the matching variables, for instance sex, age, occupation, etc. When the variable on which the matching takes place is continuous it is generally transformed into a series of categories (such as age), but the second process is to say that two values of the variable match if their difference lies between the defined limits.
This technique is known as caliper matching. Also significant is group matching in which distributions of the extraneous factors are made similar in the groups to be compared.
Group visible design is an arrangement of the v mn treatments in b blocks such that: * Each block comprises k distinct treatments k5v; * Each treatment is replicated r number
Obuchowski and Rockette method is an alternative to the Dorfman-Berbaum-Metz technique for analyzing multiple reader receiver operating curve data. Instead of the modelling the ja
Demographic data: Age: continuous variable Gender: categorical variable with males coded 1, females coded 2. Relationship status: categorical variable 1 to 5. Rational
Clinical vs. statistical significance : The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. Wi
The theorem relating structure of the likelihood to the concept of the sufficient statistic. Officially the necessary and sufficient condition which a statistic S be sufficient for
Looking for the correct answer.Y=50+.079(149)-.261(214)=
In the network shown below, the rst of the two numbers on each arc indicates the arc capacity and the second (in parentheses) of the two numbers indicates the current flow. Use t
Range is the difference between the largest and smallest observations in the data set. Commonly used as an easy-to-calculate measure of the dispersion in the set of observations b
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
MEANING ,IMPORTANCE AND RELEAVANCE OF SCATTER DIAGRAM
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