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

Classification and regression tree technique (cart), Classification and reg...

Classification and regression tree technique (CART): The alternative to the multiple regression and associated techniques or methods for determining subsets of the explanatory va

Z-tests, Hello! I am currently in graduate school earning a masters in ment...

Hello! I am currently in graduate school earning a masters in mental health counseling. I am in a stats course at current and we are reviewing z-scores. I am a little lost because

Rational –experiential inventory, Demographic data: Age: continuous vari...

Demographic data: Age: continuous variable Gender: categorical variable with males coded 1, females coded 2. Relationship status: categorical variable 1 to 5. Rational

Graphics., how to calculate the semi average method when 8 observations are...

how to calculate the semi average method when 8 observations are given?

Implementation of huffman coding, Input to the compress is a text le with a...

Input to the compress is a text le with arbitrary size, but for this assignment we will assume that the data structure of the file fits in the main memory of a computer. Output of

Tests for heteroscedasticity, Lagrange Multiplier (LM) test The Null Hy...

Lagrange Multiplier (LM) test The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1

Degenerate distributions, The special cases of the probability distribution...

The special cases of the probability distributions in which the random variable's distribution is concentrated at one point only. For instance, a discrete uniform distribution when

Cellular proliferation models, Cellular proliferation models : Models are u...

Cellular proliferation models : Models are used to describe the growth of the  cell populations. One of the example is the deterministic model   where N(t) is the number of cel

EDUC 606, The GRE has a combined verbal and quantitative mean of 1000 and a...

The GRE has a combined verbal and quantitative mean of 1000 and a standard deviation of 200.

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