Weighting and estimation
Results
All (8)
All (8) ((8 results))
- Articles and reports: 12-001-X198900214562Description:
This paper presents a technique for developing appropriate confidence intervals around postcensal population estimates using a modification of the ratio-correlation method termed the rank-order procedure. It is shown that the Wilcoxon test can be used to decide if a given ratio-correlation model is stable over time. If stability is indicated, then the confidence intervals associated with the data used in model construction are appropriate for postcensal estimates. If stability is not indicated, the confidence intervals associated with the data used in model construction are not appropriate, and, moreover, likely to overstate the precision of postcensal estimates. Given instability, it is shown that confidence intervals appropriate for postcensal estimates can be derived using the rank-order procedure. An empirical example is provided using county population estimates for Washington state.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214563Description:
This paper examines the adequacy of estimates of emigrants from Canada and interprovincial migration data from the Family Allowance files and Revenue Canada tax files. The application of these data files in estimating total population for Canada, provinces and territories, was evaluated with reference to the 1986 Census counts. It was found that these two administrative files provided consistent and reasonably accurate series of data on emigration and interprovincial migration from 1981 to 1986. Consequently, the population estimates were fairly accurate. The estimate of emigrants derived from the Family Allowance file could be improved by using the ratio of adult to child emigrant rates computed from Employment and Immigration Canada’s immigration file.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214565Description:
Empirical Bayes techniques are applied to the problem of “small area” estimation of proportions. Such methods have been previously used to advantage in a variety of situations, as described, for example, by Morris (1983). The basic idea here consists of incorporating random effects and nested random effects into models which reflect the complex structure of a multi-stage sample design, as was originally proposed by Dempster and Tomberlin (1980). Estimates of proportions can be obtained, together with associated estimates of uncertainty. These techniques are applied to simulated data in a Monte Carlo study which compares several available techniques for small area estimation.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214566Description:
A randomized response model for sampling from dichotomous populations is developed in this paper. The model permits the use of continuous randomization and multiple trials per respondent. The special case of randomization with normal distributions is considered, and a computer simulation of such a sampling procedure is presented as an initial exploration into the effects such a scheme has on the amount of information in the sample. A portable electronic device is discussed which would implement the presented model. The results of a study taken, using the electronic randomizing device, is presented. The results show that randomized response sampling is a superior technique to direct questioning for at least some sensitive questions.
Release date: 1989-12-15 - 5. Logistic regression under complex survey designs ArchivedArticles and reports: 12-001-X198900214567Description:
Estimation procedures for obtaining consistent estimators of the parameters of a generalized logistic function and of its asymptotic covariance matrix under complex survey designs are presented. A correction in the Taylor estimator of the covariance matrix is made to produce a positive definite covariance matrix. The correction also reduces the small sample bias. The estimation procedure is first presented for cluster sampling and then extended to more complex situations. A Monte Carlo study is conducted to examine the small sample properties of F-tests constructed from alternative covariance matrices. The maximum likelihood estimation method where the survey design is completely ignored is compared with the usual Taylor’s series expansion method and with the modified Taylor procedure.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214568Description:
The paper describes a Monte Carlo study of simultaneous confidence interval procedures for k > 2 proportions, under a model of two-stage cluster sampling. The procedures investigated include: (i) standard multinomial intervals; (ii) Scheffé intervals based on sample estimates of the variances of cell proportions; (iii) Quesenberry-Hurst intervals adapted for clustered data using Rao and Scott’s first and second order adjustments to X^2; (iv) simple Bonferroni intervals; (v) Bonferroni intervals based on transformations of the estimated proportions; (vi) Bonferroni intervals computed using the critical points of Student’s t. In several realistic situations, actual coverage rates of the multinomial procedures were found to be seriously depressed compared to the nominal rate. The best performing intervals, from the point of view of coverage rates and coverage symmetry (an extension of an idea due to Jennings), were the t-based Bonferroni intervals derived using log and logit transformations. Of the Scheffé-like procedures, the best performance was provided by Quesenberry-Hurst intervals in combination with first-order Rao-Scott adjustments.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900114580Description:
Estimation of total numbers of hogs and pigs, sows and gilts, and cattle and calves in a state is studied using data obtained in the June Enumerative Survey conducted by the National Agricultural Statistics Service of the U.S. Department of Agriculture. It is possible to construct six different estimators using the June Enumerative Survey data. Three estimators involve data from area samples and three estimators combine data from list-frame and area-frame surveys. A rotation sampling scheme is used for the area frame portion of the June Enumerative Survey. Using data from the five years, 1982 through 1986, covariances among the estimators for different years are estimated. A composite estimator is proposed for the livestock numbers. The composite estimator is obtained by a generalized least-squares regression of the vector of different yearly estimators on an appropriate set of dummy variables. The composite estimator is designed to yield estimates for livestock inventories that are “at the same level” as the official estimates made by the U.S. Department of Agriculture.
Release date: 1989-06-15 - Articles and reports: 12-001-X198900114581Description:
This paper develops a design consistent small domain estimator using a random effects model. The mean squared error of this estimator is then evaluated without assuming the random effect component of the model is correct. Data from a complex sample survey shows how this approach to mean squared error estimation, while perhaps too instable to be used directly, can be employed to determine whether the design consistent small domain estimator proposed here is better than the conventional design-based estimator.
Release date: 1989-06-15
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Analysis (8)
Analysis (8) ((8 results))
- Articles and reports: 12-001-X198900214562Description:
This paper presents a technique for developing appropriate confidence intervals around postcensal population estimates using a modification of the ratio-correlation method termed the rank-order procedure. It is shown that the Wilcoxon test can be used to decide if a given ratio-correlation model is stable over time. If stability is indicated, then the confidence intervals associated with the data used in model construction are appropriate for postcensal estimates. If stability is not indicated, the confidence intervals associated with the data used in model construction are not appropriate, and, moreover, likely to overstate the precision of postcensal estimates. Given instability, it is shown that confidence intervals appropriate for postcensal estimates can be derived using the rank-order procedure. An empirical example is provided using county population estimates for Washington state.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214563Description:
This paper examines the adequacy of estimates of emigrants from Canada and interprovincial migration data from the Family Allowance files and Revenue Canada tax files. The application of these data files in estimating total population for Canada, provinces and territories, was evaluated with reference to the 1986 Census counts. It was found that these two administrative files provided consistent and reasonably accurate series of data on emigration and interprovincial migration from 1981 to 1986. Consequently, the population estimates were fairly accurate. The estimate of emigrants derived from the Family Allowance file could be improved by using the ratio of adult to child emigrant rates computed from Employment and Immigration Canada’s immigration file.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214565Description:
Empirical Bayes techniques are applied to the problem of “small area” estimation of proportions. Such methods have been previously used to advantage in a variety of situations, as described, for example, by Morris (1983). The basic idea here consists of incorporating random effects and nested random effects into models which reflect the complex structure of a multi-stage sample design, as was originally proposed by Dempster and Tomberlin (1980). Estimates of proportions can be obtained, together with associated estimates of uncertainty. These techniques are applied to simulated data in a Monte Carlo study which compares several available techniques for small area estimation.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214566Description:
A randomized response model for sampling from dichotomous populations is developed in this paper. The model permits the use of continuous randomization and multiple trials per respondent. The special case of randomization with normal distributions is considered, and a computer simulation of such a sampling procedure is presented as an initial exploration into the effects such a scheme has on the amount of information in the sample. A portable electronic device is discussed which would implement the presented model. The results of a study taken, using the electronic randomizing device, is presented. The results show that randomized response sampling is a superior technique to direct questioning for at least some sensitive questions.
Release date: 1989-12-15 - 5. Logistic regression under complex survey designs ArchivedArticles and reports: 12-001-X198900214567Description:
Estimation procedures for obtaining consistent estimators of the parameters of a generalized logistic function and of its asymptotic covariance matrix under complex survey designs are presented. A correction in the Taylor estimator of the covariance matrix is made to produce a positive definite covariance matrix. The correction also reduces the small sample bias. The estimation procedure is first presented for cluster sampling and then extended to more complex situations. A Monte Carlo study is conducted to examine the small sample properties of F-tests constructed from alternative covariance matrices. The maximum likelihood estimation method where the survey design is completely ignored is compared with the usual Taylor’s series expansion method and with the modified Taylor procedure.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900214568Description:
The paper describes a Monte Carlo study of simultaneous confidence interval procedures for k > 2 proportions, under a model of two-stage cluster sampling. The procedures investigated include: (i) standard multinomial intervals; (ii) Scheffé intervals based on sample estimates of the variances of cell proportions; (iii) Quesenberry-Hurst intervals adapted for clustered data using Rao and Scott’s first and second order adjustments to X^2; (iv) simple Bonferroni intervals; (v) Bonferroni intervals based on transformations of the estimated proportions; (vi) Bonferroni intervals computed using the critical points of Student’s t. In several realistic situations, actual coverage rates of the multinomial procedures were found to be seriously depressed compared to the nominal rate. The best performing intervals, from the point of view of coverage rates and coverage symmetry (an extension of an idea due to Jennings), were the t-based Bonferroni intervals derived using log and logit transformations. Of the Scheffé-like procedures, the best performance was provided by Quesenberry-Hurst intervals in combination with first-order Rao-Scott adjustments.
Release date: 1989-12-15 - Articles and reports: 12-001-X198900114580Description:
Estimation of total numbers of hogs and pigs, sows and gilts, and cattle and calves in a state is studied using data obtained in the June Enumerative Survey conducted by the National Agricultural Statistics Service of the U.S. Department of Agriculture. It is possible to construct six different estimators using the June Enumerative Survey data. Three estimators involve data from area samples and three estimators combine data from list-frame and area-frame surveys. A rotation sampling scheme is used for the area frame portion of the June Enumerative Survey. Using data from the five years, 1982 through 1986, covariances among the estimators for different years are estimated. A composite estimator is proposed for the livestock numbers. The composite estimator is obtained by a generalized least-squares regression of the vector of different yearly estimators on an appropriate set of dummy variables. The composite estimator is designed to yield estimates for livestock inventories that are “at the same level” as the official estimates made by the U.S. Department of Agriculture.
Release date: 1989-06-15 - Articles and reports: 12-001-X198900114581Description:
This paper develops a design consistent small domain estimator using a random effects model. The mean squared error of this estimator is then evaluated without assuming the random effect component of the model is correct. Data from a complex sample survey shows how this approach to mean squared error estimation, while perhaps too instable to be used directly, can be employed to determine whether the design consistent small domain estimator proposed here is better than the conventional design-based estimator.
Release date: 1989-06-15
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