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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.
The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
Network sampling is a sampling design in which the simple random sample or strati?ed sample of the sampling units is made and all observational units which are linked to any of th
i have an assignment for experimental design which is must done by SAS program can you help me also i need to hand in the assignment till thursday shall i send it for you ?
Confidence interval : A range of the values, calculated from the sample observations which is believed, with the particular probability, to posses the true parameter value. A 95% c
The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
2 jobs n machines,graphical method,how to determine which job should proceed first on each machine
Hello , I have a business statistic HW that is due after 23 hours exactly for now . I need full and details answers please , plus they must be in a done and typed in a word or exce
Data which occur when failure period is recorded which are dependent. Such type of data can arise in number contexts, for instance, in epidemiological cohort studies in which th
The graphical process most frequently used in the analysis of data from a two-by-two crossover design. For each of the subject the difference between the response variable values o
Cochrane collaboration : An international network of the individuals committed to preparing , maintaining and disseminating the systematic reviews of the effects of the health care
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