Weighting and estimation

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All (3) ((3 results))

  • 1. On the variances of asymptotically normal estimators from complex surveys Archived
    Articles and reports: 12-001-X198100214321
    Description:

    The problem of specifying and estimating the variance of estimated parameters based on complex sample designs from finite populations is considered. The results of this paper are particularly useful when the parameter estimators cannot be defined explicitly as a function of other statistics from the sample. It is shown how these results can be applied to linear regression, logistic regression and log linear contingency table models.

    Release date: 1981-12-15
  • 2. Models for estimation of sampling errors Archived
    Articles and reports: 12-001-X198100214326
    Description:

    This paper presents results of an empirical study on fitting log-linear models to data on estimates of characteristics and their coefficients of variation (CV) from the Canadian Labour Force Survey. The characteristics were classified into groups on the basis of design effects and models were fitted to data on estimates of characteristic totals and their CVs over twelve month period. The models can be used in situations where estimates of CV are needed for new characteristics, and for providing more precise estimates of reliability of estimates based on past data. The problem of evaluation of fit of the models is considered.

    Release date: 1981-12-15
  • 3. Construction of working probabilities and joint selection probabilities for Fellegi’s PPS sampling scheme Archived
    Articles and reports: 12-001-X198100154935
    Description:

    A FORTRAN Subroutine to obtain the “working probabilities” for Fellegi’s (1963) method of unequal probability sampling is given. The solution is obtained by an iterative procedure where the starting values for the (k+l)th draw “working probabilities” are the solutions for the kth draw “working probabilities” and the iterative procedure is terminated when a prespecified accuracy is achieved. The limitation is that the Subroutine can only be used to obtain up to and including the 5th draw “working probabilities”. It was observed that the convergence occurs very fast in double precision. Therefore all real variables have been declared as double precision. The joint selection probabilities \Pi_{ij}’s i.e. the probability that both the ith and jth units are in the sample are obtained by summing the probabilities of selecting those samples that contain both the ith and jth units. The joint selection probabilities are required for the variance estimation of the Horvitz-Thompson estimator of population total of the characteristic of interest.

    Release date: 1981-06-15
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Analysis (3)

Analysis (3) ((3 results))

  • 1. On the variances of asymptotically normal estimators from complex surveys Archived
    Articles and reports: 12-001-X198100214321
    Description:

    The problem of specifying and estimating the variance of estimated parameters based on complex sample designs from finite populations is considered. The results of this paper are particularly useful when the parameter estimators cannot be defined explicitly as a function of other statistics from the sample. It is shown how these results can be applied to linear regression, logistic regression and log linear contingency table models.

    Release date: 1981-12-15
  • 2. Models for estimation of sampling errors Archived
    Articles and reports: 12-001-X198100214326
    Description:

    This paper presents results of an empirical study on fitting log-linear models to data on estimates of characteristics and their coefficients of variation (CV) from the Canadian Labour Force Survey. The characteristics were classified into groups on the basis of design effects and models were fitted to data on estimates of characteristic totals and their CVs over twelve month period. The models can be used in situations where estimates of CV are needed for new characteristics, and for providing more precise estimates of reliability of estimates based on past data. The problem of evaluation of fit of the models is considered.

    Release date: 1981-12-15
  • 3. Construction of working probabilities and joint selection probabilities for Fellegi’s PPS sampling scheme Archived
    Articles and reports: 12-001-X198100154935
    Description:

    A FORTRAN Subroutine to obtain the “working probabilities” for Fellegi’s (1963) method of unequal probability sampling is given. The solution is obtained by an iterative procedure where the starting values for the (k+l)th draw “working probabilities” are the solutions for the kth draw “working probabilities” and the iterative procedure is terminated when a prespecified accuracy is achieved. The limitation is that the Subroutine can only be used to obtain up to and including the 5th draw “working probabilities”. It was observed that the convergence occurs very fast in double precision. Therefore all real variables have been declared as double precision. The joint selection probabilities \Pi_{ij}’s i.e. the probability that both the ith and jth units are in the sample are obtained by summing the probabilities of selecting those samples that contain both the ith and jth units. The joint selection probabilities are required for the variance estimation of the Horvitz-Thompson estimator of population total of the characteristic of interest.

    Release date: 1981-06-15
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