Editing and imputation
Results
All (9)
All (9) ((9 results))
- Articles and reports: 12-001-X198600214449Description:
Nearly all surveys and censuses are subject to two types of nonresponse: unit (total) and item (partial). Several methods of compensating for nonresponse have been developed in an attempt to reduce the bias associated with nonresponse. This paper summarizes the nonresponse adjustment procedures used at the U.S. Census Bureau, focusing on unit nonresponse. Some discussion of current and future research in this area is also included.
Release date: 1986-12-15 - Articles and reports: 12-001-X198600214450Description:
From an annual sample of U.S. corporate tax returns, the U.S. Internal Revenue Service provides estimates of population and subpopulation totals for several hundred financial items. The basic sample design is highly stratified and fairly complex. Starting with the 1981 and 1982 samples, the design was altered to include a double sampling procedure. This was motivated by the need for better allocation of resources, in an environment of shrinking budgets. Items not observed in the subsample are predicted, using a modified hot deck imputation procedure. The present paper describes the design, estimation, and evaluation of the effects of the new procedure.
Release date: 1986-12-15 - Articles and reports: 12-001-X198600214451Description:
The Canadian Census of Construction (COC) uses a complex plan for sampling small businesses (those having a gross income of less than $750,000). Stratified samples are drawn from overlapping frames. Two subsamples are selected independently from one of the samples, and more detailed information is collected on the businesses in the subsamples. There are two possible methods of estimating totals for the variables collected in the subsamples. The first approach is to determine weights based on sampling rates. A number of different weights must be used. The second approach is to impute values to the businesses included in the sample but not in the subsamples. This approach creates a complete “rectangular” sample file, and a single weight may then be used to produce estimates for the population. This “large-scale imputation” technique is presently applied for the Census of Construction. The purpose of the study is to compare the figures obtained using various estimation techniques with the estimates produced by means of large-scale imputation.
Release date: 1986-12-15 - 4. The treatment of missing survey data ArchivedArticles and reports: 12-001-X198600114404Description:
Missing survey data occur because of total nonresponse and item nonresponse. The standard way to attempt to compensate for total nonresponse is by some form of weighting adjustment, whereas item nonresponses are handled by some form of imputation. This paper reviews methods of weighting adjustment and imputation and discusses their properties.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114439Description:
Multiple imputation is a technique for handling survey nonresponse that replaces each missing value created by nonresponse by a vector of possible values that reflect uncertainty about which values to impute. A simple example and brief overview of the underlying theory are used to introduce the general procedure.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114440Description:
Statistics Canada has undertaken a project to develop a generalized edit and imputation system, the intent of which is to meet the processing requirements of most of its surveys. The various approaches to imputation for item non-response, which have been proposed, will be discussed. Important issues related to the implementation of these proposals into a generalized setting will also be addressed.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114441Description:
The analysis of survey data becomes difficult in the presence of incomplete responses. By the use of the maximum likelihood method, estimators for the parameters of interest and test statistics can be generated. In this paper the maximum likelihood estimators are given for the case where the data is considered missing at random. A method for imputing the missing values is considered along with the problem of estimating the change points in the mean. Possible extensions of the results to structured covariances and to non-randomly incomplete data are also proposed.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114442Description:
For periodic business surveys which are conducted on a monthly, quarterly or annual basis, the data for responding units must be edited and the data for non-responding units must be imputed. This paper reports on methods which can be used for editing and imputing data. The editing is comprised of consistency and statistical edits. The imputation is done for both total non-response and partial non-response.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114444Description:
A new processing system using the nearest neighbour (N-N) imputation method is being implemented for the National Farm Survey (NFS). An empirical study was conducted to determine if the NFS estimates would be affected by using imputation groups based on type of farm. For the specific imputation rule examined, the study showed evidence that the effect might be small.
Release date: 1986-06-16
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Analysis (9)
Analysis (9) ((9 results))
- Articles and reports: 12-001-X198600214449Description:
Nearly all surveys and censuses are subject to two types of nonresponse: unit (total) and item (partial). Several methods of compensating for nonresponse have been developed in an attempt to reduce the bias associated with nonresponse. This paper summarizes the nonresponse adjustment procedures used at the U.S. Census Bureau, focusing on unit nonresponse. Some discussion of current and future research in this area is also included.
Release date: 1986-12-15 - Articles and reports: 12-001-X198600214450Description:
From an annual sample of U.S. corporate tax returns, the U.S. Internal Revenue Service provides estimates of population and subpopulation totals for several hundred financial items. The basic sample design is highly stratified and fairly complex. Starting with the 1981 and 1982 samples, the design was altered to include a double sampling procedure. This was motivated by the need for better allocation of resources, in an environment of shrinking budgets. Items not observed in the subsample are predicted, using a modified hot deck imputation procedure. The present paper describes the design, estimation, and evaluation of the effects of the new procedure.
Release date: 1986-12-15 - Articles and reports: 12-001-X198600214451Description:
The Canadian Census of Construction (COC) uses a complex plan for sampling small businesses (those having a gross income of less than $750,000). Stratified samples are drawn from overlapping frames. Two subsamples are selected independently from one of the samples, and more detailed information is collected on the businesses in the subsamples. There are two possible methods of estimating totals for the variables collected in the subsamples. The first approach is to determine weights based on sampling rates. A number of different weights must be used. The second approach is to impute values to the businesses included in the sample but not in the subsamples. This approach creates a complete “rectangular” sample file, and a single weight may then be used to produce estimates for the population. This “large-scale imputation” technique is presently applied for the Census of Construction. The purpose of the study is to compare the figures obtained using various estimation techniques with the estimates produced by means of large-scale imputation.
Release date: 1986-12-15 - 4. The treatment of missing survey data ArchivedArticles and reports: 12-001-X198600114404Description:
Missing survey data occur because of total nonresponse and item nonresponse. The standard way to attempt to compensate for total nonresponse is by some form of weighting adjustment, whereas item nonresponses are handled by some form of imputation. This paper reviews methods of weighting adjustment and imputation and discusses their properties.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114439Description:
Multiple imputation is a technique for handling survey nonresponse that replaces each missing value created by nonresponse by a vector of possible values that reflect uncertainty about which values to impute. A simple example and brief overview of the underlying theory are used to introduce the general procedure.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114440Description:
Statistics Canada has undertaken a project to develop a generalized edit and imputation system, the intent of which is to meet the processing requirements of most of its surveys. The various approaches to imputation for item non-response, which have been proposed, will be discussed. Important issues related to the implementation of these proposals into a generalized setting will also be addressed.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114441Description:
The analysis of survey data becomes difficult in the presence of incomplete responses. By the use of the maximum likelihood method, estimators for the parameters of interest and test statistics can be generated. In this paper the maximum likelihood estimators are given for the case where the data is considered missing at random. A method for imputing the missing values is considered along with the problem of estimating the change points in the mean. Possible extensions of the results to structured covariances and to non-randomly incomplete data are also proposed.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114442Description:
For periodic business surveys which are conducted on a monthly, quarterly or annual basis, the data for responding units must be edited and the data for non-responding units must be imputed. This paper reports on methods which can be used for editing and imputing data. The editing is comprised of consistency and statistical edits. The imputation is done for both total non-response and partial non-response.
Release date: 1986-06-16 - Articles and reports: 12-001-X198600114444Description:
A new processing system using the nearest neighbour (N-N) imputation method is being implemented for the National Farm Survey (NFS). An empirical study was conducted to determine if the NFS estimates would be affected by using imputation groups based on type of farm. For the specific imputation rule examined, the study showed evidence that the effect might be small.
Release date: 1986-06-16
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