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Likert scales is often used in the studies of attitudes in which the raw scores are based on the graded alternative responses to each of a series of queries. For instance, the subject might be asked to indicate his/her degree of agreement with each of the series of statements relevant to the attitude. The number is attached to each possible response, for example
1:strongly approve; 2:approve; 3:undecided; 4:disapprove; 5:strongly disapprove; and the total of these used as the compo- site score. A generally used Likert-type scale in the medicine is the Apgar score used to appraise status of the newborn infants. This is the total of the points (0,1 or 2) allotted for each of the ?ve items:
* heart rate (is over 100 beats per minute 2 points, slower 1 point, no beat 0);
* the respiratory effort;
* the muscle tone;
* the response to simulation by the catheter in the nostril;
*the colour of skin.
The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte
A name sometimes given to the type of diagram generally used in meta-analysis, in which point estimates and confidence intervals are displayed for all the studies included in the a
The procedure in which the prior distribution is required in the application of Bayesian inference, it is determined from empirical evidence, namely same data for which the posteri
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Information theory: This is the branch of applied probability theory applicable to various communication and signal processing problems in the field of engineering and biology. In
It is the survey which is carried out in Great Britain on a continuous basis since 1971. About 100 000 households are included in this sample every year. The main goal of the surve
An approach of using the likelihood as the basis of estimation without the requirement to specify a parametric family for data. Empirical likelihood can be viewed as the example of
This is an approach to the modelling of time-frequency surfaces which consists of a Bayesian regularization scheme in which the prior distributions over the time-frequency coeffici
An approach to decrease the size of very large data sets in which the data are first 'binned' and then statistics such as the mean and variance/covariance are calculated on each bi
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