Explain missing values, Advanced Statistics

Assignment Help:

Missing values: The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the study completely or do not appear for one or other of scheduled visits or because of the equipment failure. The common causes of subjects prematurely ceasing to participate include the recovery, lack of improvement, the unwanted signs or symptoms that might be related to the investigational treatment, unlikeable study procedures and the intercurrent health problems. Such values greatly complicate number of methods of analysis and simply using those individuals for whom data are complete can be unsatisfactory in number of situations. A distinction can be made between the values missing completely at random (MCAR), missing at random (MAR) and the non-ignorable (or informative).

The MCAR variety arise when the individuals drop out of study in a process which is independent of the observed measurements and those that would have been available had they not been missing both; here the observed values effectively constitute the simple random sample of the values for all study subjects. Random drop-out (MAR) happens when the dropout process depends on the outcomes which have been observed in the past, but given this information is conditionally independent of all future (which is unrecorded) values of the outcome variable following the drop-out. At last, in the case of informative drop-out, the drop-out process depends upon the unobserved values of the result variable. It is the latter which cause most the problems for the analysis of data comprising missing values.


Related Discussions:- Explain missing values

Case-control study, Case-control study : The traditional case-control study...

Case-control study : The traditional case-control study is the common research design in the epidemiology where the exposures to risk factors for cases (individuals getting the dis

Zero-inflated poisson regression, Zero-inflated Poisson regression is  the...

Zero-inflated Poisson regression is  the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit

Adjusted r-squared, R-squared is regarded as the coefficient of determinati...

R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also

QUANTITATIVE METHOD., an oil company is considering whether or not to bid f...

an oil company is considering whether or not to bid for an offshore drilling contract. The bid would cost $60 with a 65% chance of gaining the contract. Outcome success Probability

Product-limit estimator, Product-limit estimator is a method for estimatin...

Product-limit estimator is a method for estimating the survival functions for the set of survival times, some of which might be censored observations. The logic behind the procedu

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

Parks test, The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedastici...

The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti

Explain missing values, Missing values : The observations missing from the ...

Missing values : The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the stud

Doane''s rule, A rule for computing the number of classes to use while cons...

A rule for computing the number of classes to use while constructing a histogram and  can be given by   here n is the sample size and ^ γ is the estimate of kurtosis.

Fuzzy set theory, A radically different approach of dealing with the uncert...

A radically different approach of dealing with the uncertainty than the traditional probabilistic and the statistical methods. The necessary feature of the fuzzy set is a membershi

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