Some approaches in dealing with nonresponse in survey operations with applications to the 1991 Marinduque census of agriculture and fisheries data
This study presents some of the more popular approaches in dealing with the problem of nonresponse in survey operations. The problem of nonresponse is endemic in every survey. Ignoring these effects contribute to the added inaccuracy of the results and often lead to the misinterpretation of the data...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
1996
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/16313 |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | This study presents some of the more popular approaches in dealing with the problem of nonresponse in survey operations. The problem of nonresponse is endemic in every survey. Ignoring these effects contribute to the added inaccuracy of the results and often lead to the misinterpretation of the data.The problem os Item Nonresponse can be compensated by the methods of Imputation such as Mean Imputation and Hot Deck Imputation which are the more popular ones because of their computational and statistical simplicity. It has been shown that compensating for nonresponse improves results as opposed to total discarding of observations with missing values. A comparative assessment of the Mean Imputation and Hot Deck Imputation methods was made using the 1991 Marinduque Census of Agriculture and Fisheries data. It was shown that varying the rates of missing observations and sample sizes pose an effect on the variances. Results proved that the Hot Deck Imputation method was more efficient than the Mean Imputation method. |
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