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  • 1. Perfoming logistic regression on survey data with the new surveylogistic procedure Archived
    Articles and reports: 11-522-X20020016723
    Description:

    Categorical outcomes, such as binary, ordinal and nominal responses, occur often in survey research. Logistic regression investigates the relationship between such categorical responses variables and a set of explanatory variables. The LOGISTIC procedure can be used to perform a logistic analysis on data from a random sample. However, this approach is not valid if the data come from other sample designs, such as complex survey designs with stratification, clustering and/or unequal weighting. In these cases, specialized techniques must be applied in order to produce the appropriate estimates and standard errors.

    The SURVEYLOGISTIC procedure, experimental in Version 9, brings logistic regression for survey data to the SAS System and delivers much of the functionality of the LOGISTIC procedure. This paper describes the methodological approach and applications for this new software.

    Release date: 2004-09-13
  • 2. Coverage error in population censuses: The case of Turkey Archived
    Articles and reports: 12-001-X20030026780
    Description:

    Coverage errors and other coverage issues related to the population censuses are examined in the light of the recent literature. Especially, when the actual population census count of persons are matched with their corresponding post enumeration survey counts, the aggregated results in a dual record system setting can provide some coverage error statistics.

    In this paper, the coverage error issues are evaluated and alternative solutions are discussed in the light of the results from the latest Population Census of Turkey. By using the Census and post enumeration survey data, regional comparison of census coverage was also made and has shown greater variability among regions. Some methodological remarks are also made on the possible improvements on the current enumeration procedures.

    Release date: 2004-01-27
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Articles and reports (2)

Articles and reports (2) ((2 results))

  • 1. Perfoming logistic regression on survey data with the new surveylogistic procedure Archived
    Articles and reports: 11-522-X20020016723
    Description:

    Categorical outcomes, such as binary, ordinal and nominal responses, occur often in survey research. Logistic regression investigates the relationship between such categorical responses variables and a set of explanatory variables. The LOGISTIC procedure can be used to perform a logistic analysis on data from a random sample. However, this approach is not valid if the data come from other sample designs, such as complex survey designs with stratification, clustering and/or unequal weighting. In these cases, specialized techniques must be applied in order to produce the appropriate estimates and standard errors.

    The SURVEYLOGISTIC procedure, experimental in Version 9, brings logistic regression for survey data to the SAS System and delivers much of the functionality of the LOGISTIC procedure. This paper describes the methodological approach and applications for this new software.

    Release date: 2004-09-13
  • 2. Coverage error in population censuses: The case of Turkey Archived
    Articles and reports: 12-001-X20030026780
    Description:

    Coverage errors and other coverage issues related to the population censuses are examined in the light of the recent literature. Especially, when the actual population census count of persons are matched with their corresponding post enumeration survey counts, the aggregated results in a dual record system setting can provide some coverage error statistics.

    In this paper, the coverage error issues are evaluated and alternative solutions are discussed in the light of the results from the latest Population Census of Turkey. By using the Census and post enumeration survey data, regional comparison of census coverage was also made and has shown greater variability among regions. Some methodological remarks are also made on the possible improvements on the current enumeration procedures.

    Release date: 2004-01-27
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