Explain longitudinal data, Advanced Statistics

Assignment Help:

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.


Related Discussions:- Explain longitudinal data

Regression analysis, The regression analysis is used to fit a model descr...

The regression analysis is used to fit a model describing the relationship of a dependent variable with independent variable(s). Here we have fitted three regression models:

Gauss markov theorem, This is the theorem which states that if the error te...

This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p

Play-the-winner rule, Play-the-winner rule is a process sometimes consider...

Play-the-winner rule is a process sometimes considered in the clinical trials in which the response to treatment is positive (a success) or negative (a failure). One of two treatm

Explain maternal mortality, Maternal mortality : The maternal death is the ...

Maternal mortality : The maternal death is the death of a woman while pregnant, delivering a baby or within 42 days of the termination of pregnancy, from any reason related to or a

Binomial distribution with continuity correction, Records on the computer m...

Records on the computer manufacturing process at Pratt-Zungia Limited show that the percentage of defective computers sent to  customers has been 5% over the last few years. Shipme

Uncertainty analysis, Uncertainty analysis is the process for assessing th...

Uncertainty analysis is the process for assessing the variability in the outcome variable that is due to the uncertainty in estimating the values of input parameters. A sensitivit

Continual reassessment method, Continual reassessment method: An approach ...

Continual reassessment method: An approach which applies Bayesian inference for determining the maximum tolerated dose in a phase I trial. The method starts by assuming a logistic

Gabor regression, This is an approach to the modelling of time-frequency su...

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

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

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!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd