Analysis

All (4) ((4 results))

• 1. The role of demographic factors in the analysis of survey versus diary purchase reporting accuracy Archived

  Articles and reports: 12-001-X198900114577

  Description:

  In this article the authors evaluate the relative performance of survey and diary data collection methods in the context of the long-distance telephone communication market. Based on an analysis of 1,530 respondents, the results indicate that two demographic variables, sex and income, are important in explaining the difference in survey reporting and diary recording of usage data.

  Release date: 1989-06-15

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• 2. Sample allocation in multivariate surveys Archived

  Articles and reports: 12-001-X198900114578

  Description:

  The optimum allocation to strata for multipurpose surveys is often solved in practice by establishing linear variance constraints and then using convex programming to minimize the survey cost. Using the Kuhn-Tucker theorem, this paper gives an expression for the resulting optimum allocation in terms of Lagrangian multipliers. Using this representation, the partial derivative of the cost function with respect to the k-th variance constraint is found to be -2 \alpha_{k^*} g (x^*) / v_k, where g (x^*) is the cost of the optimum allocation and where \alpha_{k^*} and v_k are, respectively, the k-th normalized Lagrangian multiplier and the upper bound on the precision of the k-th variable. Finally, a simple computing algorithm is presented and its convergence properties are discussed. The use of these results in sample design is demonstrated with data from a survey of commercial establishments.

  Release date: 1989-06-15

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• 3. Modelling and estimation for repeated surveys Archived

  Articles and reports: 12-001-X198900114579

  Description:

  Estimation of the means of a characteristic for a population at different points in time, based on a series of repeated surveys, is briefly reviewed. By imposing a stochastic parametric model on these means, it is possible to estimate the parameters of the model and to obtain alternative estimators of the means themselves. We describe the case where the population means follow an autoregressive-moving average (ARMA) process and the survey errors can also be formulated as an ARMA process. An example using data from the Canadian Travel Survey is presented.

  Release date: 1989-06-15

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• 4. Estimation of livestock inventories using several area- and multiple-frame estimators Archived

  Articles and reports: 12-001-X198900114580

  Description:

  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

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Articles and reports (4) ((4 results))

• 1. The role of demographic factors in the analysis of survey versus diary purchase reporting accuracy Archived

  Articles and reports: 12-001-X198900114577

  Description:

  In this article the authors evaluate the relative performance of survey and diary data collection methods in the context of the long-distance telephone communication market. Based on an analysis of 1,530 respondents, the results indicate that two demographic variables, sex and income, are important in explaining the difference in survey reporting and diary recording of usage data.

  Release date: 1989-06-15

  ---

• 2. Sample allocation in multivariate surveys Archived

  Articles and reports: 12-001-X198900114578

  Description:

  The optimum allocation to strata for multipurpose surveys is often solved in practice by establishing linear variance constraints and then using convex programming to minimize the survey cost. Using the Kuhn-Tucker theorem, this paper gives an expression for the resulting optimum allocation in terms of Lagrangian multipliers. Using this representation, the partial derivative of the cost function with respect to the k-th variance constraint is found to be -2 \alpha_{k^*} g (x^*) / v_k, where g (x^*) is the cost of the optimum allocation and where \alpha_{k^*} and v_k are, respectively, the k-th normalized Lagrangian multiplier and the upper bound on the precision of the k-th variable. Finally, a simple computing algorithm is presented and its convergence properties are discussed. The use of these results in sample design is demonstrated with data from a survey of commercial establishments.

  Release date: 1989-06-15

  ---

• 3. Modelling and estimation for repeated surveys Archived

  Articles and reports: 12-001-X198900114579

  Description:

  Estimation of the means of a characteristic for a population at different points in time, based on a series of repeated surveys, is briefly reviewed. By imposing a stochastic parametric model on these means, it is possible to estimate the parameters of the model and to obtain alternative estimators of the means themselves. We describe the case where the population means follow an autoregressive-moving average (ARMA) process and the survey errors can also be formulated as an ARMA process. An example using data from the Canadian Travel Survey is presented.

  Release date: 1989-06-15

  ---

• 4. Estimation of livestock inventories using several area- and multiple-frame estimators Archived

  Articles and reports: 12-001-X198900114580

  Description:

  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

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