An Optimum Multivariate Stratified Sampling Design with Nonresponse: A Lexicographic Goal Programming Approach

2011 ◽  
Vol 10 (4) ◽  
pp. 393-405 ◽  
Author(s):  
Rahul Varshney ◽  
M. J. Ahsan ◽  
M. G. M. Khan
Keyword(s):  
Goal Programming ◽  
Sampling Design ◽  
Stratified Sampling ◽  
Programming Approach ◽  
Multivariate Stratified Sampling ◽  
Lexicographic Goal Programming

scholarly journals The problem of optimum allocation in multivariate stratified sampling

2012 ◽  
Vol 30 (1) ◽  
pp. 65
Author(s):  
Ummatul Fatima ◽  
Shazia Ghufran ◽  
M. J. Ahsan
Keyword(s):  
Sampling Design ◽  
Stratified Sampling ◽  
Optimum Allocation ◽  
Multiple Response ◽  
Sample Surveys ◽  
Multivariate Stratified Sampling ◽  
Highly Correlated

Generally, sample surveys are multivariate in nature where multiple response are obtained on every unit selected in a sample, that is, more than one characteristics are defined on each and every unit of the population. While dealing with a multivariate stratified population, to workout an allocation that is optimum for all characteristics is almost impossible unless the characteristics are highly correlated. Some compromise must be allowed to obtain an allocation that is optimum, in some sense, for all the characteristics. Since such allocations are based on some compromise criteria they are known as compromise allocations. This paper deals with the problem of obtaining an optimum allocation in multivariate stratified sampling design.

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