Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
Longitudinal data: The data arising when each of the number of subjects or patients give rise to the vector of measurements representing same variable observed at the number of different time instants.
This type of data combines elements of the multivariate data and time series data. They differ from the previous, however, in that only a single variable is involved, and from the latter in consisting of a large number of short series, one from the each subject, rather than single long series. This kind of data can be collected either prospectively, following subjects forward in time, or the retrospectively, by extracting measurements on each person from historical records. This kind of data is also often called as repeated measures data, specifically in the social and behavioural sciences, though in these disciplines such data are more likely to occur from observing individuals repeatedly under different experimental conditions rather than from a simple time sequence. Special statistical techniques are often required for the analysis of this type of data because the set of measurements on one subject tend to be intercorrelated. This correlation should be taken into account to draw the valid scientific inferences. The design of most of the studies specifies that all the subjects are to have the same number of the repeated measurements made at the equivalent time intervals. Such data is usually referred to as the balanced longitudinal data. But though the balanced data is generally the target, unbalanced longitudinal data in which subjects might have different numbers of repeated measurements made at the differing time intervals, do arise for the variety of reasons. Sometimes the data are unbalanced or incomplete by the design; an investigator might, for instance, choose in advance to take the measurements every hour on one half of the subjects and every two hours on other half.
In general, though, the major reason for the unbalanced data in a longitudinal study is occurrence of missing values in the sense that the intended measurements are not taken, are lost or are otherwise not available.
Opreation research phase
Suppose the graph G is n-connected, regular of degree n, and has an even number of vertices. Prove that G has a one-factor. Petersen's 2-factor theorem (Theorem 5.40 in the note
Classification and regression tree technique (CART): The alternative to the multiple regression and associated techniques or methods for determining subsets of the explanatory va
Hypergeometric distribution is t he probability distribution related with the sampling without replacement from the population of finite size. If the population comprises of r ele
Oracle property is a name given to techniques for estimating the regression parameters in the models fitted to high-dimensional data which have the property that they can correctl
The distribution free or technique which is the analogue of the analysis of variance for the design with two factors. It can be applied to data sets which do not meet the assumptio
Partial least squares is an alternative to the multiple regressions which, in spite of using the original q explanatory variables directly, constructs the new set of k regressor v
distinguish the historigram and histogram
Latin square is an experimental design targeted at removing from the experimental error the variation from two extraneous sources so that a more sensitive test of the treatment ef
Standardise the following arguments, which involve counter-arguments Some educators have argued that the increasing use of the internet by children and teenagers will have a be
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd