Weighting and estimation

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All (6) ((6 results))

  • Articles and reports: 12-001-X199000214527
    Description:

    The United States’ National Crime Survey is a large-scale, household survey used to provide estimates of victimizations. The National Crime Survey uses a rotating panel design under which sampled housing units are maintained in the sample for three-and-one-half years with residents of the housing units being interviewed every six months. Nonresponse is a serious problem in longitudinal data from the National Crime Survey since as few as 25% of all individuals interviewed for the survey are respondents over an entire three-and-one-half-year period. In addition, the nonresponse typically does not occur at random with respect to victimization status. This paper presents models for gross flows among two types of victimization reporting classifications: number of victimizations and seriousness of victimization. The models allow for random or nonrandom nonresponse mechanisms, and allow the probabilities underlying the gross flows to be either unconstrained or symmetric. The models are fit, using maximum likelihood estimation, to the data from the National Crime Survey.

    Release date: 1990-12-14

  • Articles and reports: 12-001-X199000214530
    Description:

    For a class of linear unbiased estimators in a class of sampling schemes, it is shown that one can forget the weights used for sample selection while estimating a population ratio by a ratio of two unbiased estimators, respectively of the numerator and the denominator defining the population ratio. This class of schemes includes commonly used sampling schemes such as unequal probability sampling with or without replacement, stratified proportional allocation sampling with unequal selection probabilities and without replacement in each stratum, etc.

    Release date: 1990-12-14

  • Articles and reports: 12-001-X199000214537
    Description:

    Repeated surveys in which a portion of the units are observed at more than one time point and some units are not observed at some time points are of primary interest. Least squares estimation for such surveys is reviewed. Included in the discussion are estimation procedures in which existing estimates are not revised when new data become available. Also considered are techniques for the estimation of longitudinal parameters, such as gross change tables. Estimation for a repeated survey of land use conducted by the U.S. Soil Conservation Service is described. The effects of measurement error on gross change estimates is illustrated and it is shown that survey designs constructed to enable estimation of the parameters of the measurement error process can be very efficient.

    Release date: 1990-12-14

  • Articles and reports: 12-001-X199000114549
    Description:

    In many government surveys, respondents are interviewed a set number of times during the life of the survey, a practice referred to as a rotation design or repeated sampling. Often composite estimation - where data from the current and earlier periods of time are combined - is used to measure the level of a characteristic of interest. As other authors have observed, composite estimation can be used in a rotation design to decrease the variance of estimators of change in level. In this paper, simple expressions are derived for the variance of a general class of composite estimators for level, change in level, and average level over time. Considered first are “one-level” rotation designs, where only the current month is referenced in the interview. Results are developed for any sampling pattern of m interviews over a period of M months. Subsequently, “multi-level” plans are addressed. In each month one of p different groups is interviewed. Respondents then answer questions referring to the previous p months. Results from the several sections apply to a wide range of government surveys.

    Release date: 1990-06-15

  • Articles and reports: 12-001-X199000114554
    Description:

    The problem considered is that of estimation of the total of a finite population which is stratified at two levels: a deeper level which has low intrastratum variability but is not known until the first phase of sampling, and a known pre-stratification which is relatively effective, unit by unit, in predicting the deeper post-stratification. As an important example, the post-stratification may define two groups corresponding to responders and non-responders in the situation of two-phase sampling for non-response. The estimators of Vardeman and Meeden (1984) are employed in a variety of situations where different types of prior information are assumed. In a general case, the standard error relative to that of the usual methods is studied via simulation. In the situation where no prior information is available and where proportional sampling is employed, the estimator is unbiased and its variance is approximated. Here, the variance is always lower than that of the usual double sampling for stratification. Also, without prior information, but with non-proportional sampling, using a slight modification of the second phase sampling plan, an unbiased estimator is found along with its variance, an unbiased estimator of its variance, and an optimal allocation scheme for the two phases of sampling. Finally, applications of these methods are discussed.

    Release date: 1990-06-15

  • Articles and reports: 12-001-X199000114555
    Description:

    This paper proposes an unbiased variance estimation formula for a two-phase sampling design used in many agricultural surveys. In this design, geographically defined primary sampling units (PSUs) are first selected via stratified simple random sampling; then secondary sampling units within sampled PSUs are restratified based on their characteristics and subsampled in a second phase of stratified simple random sampling.

    Release date: 1990-06-15
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  • Articles and reports: 12-001-X199000214527
    Description:

    The United States’ National Crime Survey is a large-scale, household survey used to provide estimates of victimizations. The National Crime Survey uses a rotating panel design under which sampled housing units are maintained in the sample for three-and-one-half years with residents of the housing units being interviewed every six months. Nonresponse is a serious problem in longitudinal data from the National Crime Survey since as few as 25% of all individuals interviewed for the survey are respondents over an entire three-and-one-half-year period. In addition, the nonresponse typically does not occur at random with respect to victimization status. This paper presents models for gross flows among two types of victimization reporting classifications: number of victimizations and seriousness of victimization. The models allow for random or nonrandom nonresponse mechanisms, and allow the probabilities underlying the gross flows to be either unconstrained or symmetric. The models are fit, using maximum likelihood estimation, to the data from the National Crime Survey.

    Release date: 1990-12-14

  • Articles and reports: 12-001-X199000214530
    Description:

    For a class of linear unbiased estimators in a class of sampling schemes, it is shown that one can forget the weights used for sample selection while estimating a population ratio by a ratio of two unbiased estimators, respectively of the numerator and the denominator defining the population ratio. This class of schemes includes commonly used sampling schemes such as unequal probability sampling with or without replacement, stratified proportional allocation sampling with unequal selection probabilities and without replacement in each stratum, etc.

    Release date: 1990-12-14

  • Articles and reports: 12-001-X199000214537
    Description:

    Repeated surveys in which a portion of the units are observed at more than one time point and some units are not observed at some time points are of primary interest. Least squares estimation for such surveys is reviewed. Included in the discussion are estimation procedures in which existing estimates are not revised when new data become available. Also considered are techniques for the estimation of longitudinal parameters, such as gross change tables. Estimation for a repeated survey of land use conducted by the U.S. Soil Conservation Service is described. The effects of measurement error on gross change estimates is illustrated and it is shown that survey designs constructed to enable estimation of the parameters of the measurement error process can be very efficient.

    Release date: 1990-12-14

  • Articles and reports: 12-001-X199000114549
    Description:

    In many government surveys, respondents are interviewed a set number of times during the life of the survey, a practice referred to as a rotation design or repeated sampling. Often composite estimation - where data from the current and earlier periods of time are combined - is used to measure the level of a characteristic of interest. As other authors have observed, composite estimation can be used in a rotation design to decrease the variance of estimators of change in level. In this paper, simple expressions are derived for the variance of a general class of composite estimators for level, change in level, and average level over time. Considered first are “one-level” rotation designs, where only the current month is referenced in the interview. Results are developed for any sampling pattern of m interviews over a period of M months. Subsequently, “multi-level” plans are addressed. In each month one of p different groups is interviewed. Respondents then answer questions referring to the previous p months. Results from the several sections apply to a wide range of government surveys.

    Release date: 1990-06-15

  • Articles and reports: 12-001-X199000114554
    Description:

    The problem considered is that of estimation of the total of a finite population which is stratified at two levels: a deeper level which has low intrastratum variability but is not known until the first phase of sampling, and a known pre-stratification which is relatively effective, unit by unit, in predicting the deeper post-stratification. As an important example, the post-stratification may define two groups corresponding to responders and non-responders in the situation of two-phase sampling for non-response. The estimators of Vardeman and Meeden (1984) are employed in a variety of situations where different types of prior information are assumed. In a general case, the standard error relative to that of the usual methods is studied via simulation. In the situation where no prior information is available and where proportional sampling is employed, the estimator is unbiased and its variance is approximated. Here, the variance is always lower than that of the usual double sampling for stratification. Also, without prior information, but with non-proportional sampling, using a slight modification of the second phase sampling plan, an unbiased estimator is found along with its variance, an unbiased estimator of its variance, and an optimal allocation scheme for the two phases of sampling. Finally, applications of these methods are discussed.

    Release date: 1990-06-15

  • Articles and reports: 12-001-X199000114555
    Description:

    This paper proposes an unbiased variance estimation formula for a two-phase sampling design used in many agricultural surveys. In this design, geographically defined primary sampling units (PSUs) are first selected via stratified simple random sampling; then secondary sampling units within sampled PSUs are restratified based on their characteristics and subsampled in a second phase of stratified simple random sampling.

    Release date: 1990-06-15
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