Abstract
The problem of data recovery found in a wide variety of statistical analysis applications. For example, it related to the survey in various sectors of the economy. When filling out a questionnaire specialist specific subject area sometimes there is a situation where he cannot answer all the questions for technical reasons (failure of the communication channel) or for personal reasons (he may not prefer one criterion to another). Survey data in many cases are formed in the form of rectangular binary tables, where columns (rows) are the studied variables that correspond to binary numbers (1, 0) or signs ( + , -). This article is devoted to the analysis and recovery of binary data in cases when the table of values of variables for the above reasons is absent. The solution of this problem proposed to carried out by the method of homogeneous groups. The essence of this method is to find in the General population of binary data of homogeneous groups of subjects of the survey and determine the affiliation of the subject of the survey, in the response of which for one of the above reasons there was a transition to one of the selected homogeneous groups. This method works well for large amounts of binary data with relatively few spaces. Otherwise, stricter methods, such as simulation methods using maximum likelihood functions or Bayesian strategies, are used. Ref. 8, tabl. 2
Highlights
The problem of processing data gaps has to be faced in a wide variety of statistical analysis applications [1,4,5]
If one question not answered by the majority of experts, it is a lack of questionnaire and you need to adjust this question and repeat the survey
This article devoted to the analysis and recovery of binary data in cases where the table of the values of variables is missing
Summary
Annotation. An approach to solving the problem of converting a table with incomplete source data or containing values that do not correspond to the expected measurement result into a representative sample considered. The existing methods of missing data recovery are analyzed, the method of homogeneous groups for missing data recovery in the original binary data table presented. Keywords: method of questionnaire, questionnaire table of binary data, homogeneous data groups, the method of homogeneous groups, restoration of missing data
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
