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All (4) ((4 results))

  • 1. Condition indexes and variance decompositions for diagnosing collinearity in linear model analysis of survey data Archived
    Articles and reports: 12-001-X201200211757
    Description:

    Collinearities among explanatory variables in linear regression models affect estimates from survey data just as they do in non-survey data. Undesirable effects are unnecessarily inflated standard errors, spuriously low or high t-statistics, and parameter estimates with illogical signs. The available collinearity diagnostics are not generally appropriate for survey data because the variance estimators they incorporate do not properly account for stratification, clustering, and survey weights. In this article, we derive condition indexes and variance decompositions to diagnose collinearity problems in complex survey data. The adapted diagnostics are illustrated with data based on a survey of health characteristics.

    Release date: 2012-12-19
  • 2. Being a Parent in a Stepfamily: A Profile Archived
    Articles and reports: 89-650-X2012002
    Geography: Canada
    Description:

    The article focuses on the situation of parents and stepparents aged 20 to 64, who are members of a stepfamily. It examines the family structure and the parents' conjugal history. It also compares socieconomic characteristics of stepfamily parents with those in intact families, in particular their income, education, labor force participation and the financial difficulties they encounter.

    Release date: 2012-10-18
  • 3. Variance inflation factors in the analysis of complex survey data Archived
    Articles and reports: 12-001-X201200111685
    Description:

    Survey data are often used to fit linear regression models. The values of covariates used in modeling are not controlled as they might be in an experiment. Thus, collinearity among the covariates is an inevitable problem in the analysis of survey data. Although many books and articles have described the collinearity problem and proposed strategies to understand, assess and handle its presence, the survey literature has not provided appropriate diagnostic tools to evaluate its impact on regression estimation when the survey complexities are considered. We have developed variance inflation factors (VIFs) that measure the amount that variances of parameter estimators are increased due to having non-orthogonal predictors. The VIFs are appropriate for survey-weighted regression estimators and account for complex design features, e.g., weights, clusters, and strata. Illustrations of these methods are given using a probability sample from a household survey of health and nutrition.

    Release date: 2012-06-27
  • 4. Volunteering in Canada Archived
    Articles and reports: 11-008-X201200111638
    Geography: Canada
    Description:

    This article examines volunteering in Canada: volunteer rates, number of hours volunteered and types of organizations supported. It describes key socioeconomic characteristics of volunteers, types of volunteer activities, motivations for volunteering and barriers to volunteering. The article also examines "informal volunteering", that is, direct help provided to family, friends and neighbours. Data are from the 2010 Canada Survey on Giving, Volunteering and Participating.

    Release date: 2012-04-16
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Articles and reports (4)

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

  • 1. Condition indexes and variance decompositions for diagnosing collinearity in linear model analysis of survey data Archived
    Articles and reports: 12-001-X201200211757
    Description:

    Collinearities among explanatory variables in linear regression models affect estimates from survey data just as they do in non-survey data. Undesirable effects are unnecessarily inflated standard errors, spuriously low or high t-statistics, and parameter estimates with illogical signs. The available collinearity diagnostics are not generally appropriate for survey data because the variance estimators they incorporate do not properly account for stratification, clustering, and survey weights. In this article, we derive condition indexes and variance decompositions to diagnose collinearity problems in complex survey data. The adapted diagnostics are illustrated with data based on a survey of health characteristics.

    Release date: 2012-12-19
  • 2. Being a Parent in a Stepfamily: A Profile Archived
    Articles and reports: 89-650-X2012002
    Geography: Canada
    Description:

    The article focuses on the situation of parents and stepparents aged 20 to 64, who are members of a stepfamily. It examines the family structure and the parents' conjugal history. It also compares socieconomic characteristics of stepfamily parents with those in intact families, in particular their income, education, labor force participation and the financial difficulties they encounter.

    Release date: 2012-10-18
  • 3. Variance inflation factors in the analysis of complex survey data Archived
    Articles and reports: 12-001-X201200111685
    Description:

    Survey data are often used to fit linear regression models. The values of covariates used in modeling are not controlled as they might be in an experiment. Thus, collinearity among the covariates is an inevitable problem in the analysis of survey data. Although many books and articles have described the collinearity problem and proposed strategies to understand, assess and handle its presence, the survey literature has not provided appropriate diagnostic tools to evaluate its impact on regression estimation when the survey complexities are considered. We have developed variance inflation factors (VIFs) that measure the amount that variances of parameter estimators are increased due to having non-orthogonal predictors. The VIFs are appropriate for survey-weighted regression estimators and account for complex design features, e.g., weights, clusters, and strata. Illustrations of these methods are given using a probability sample from a household survey of health and nutrition.

    Release date: 2012-06-27
  • 4. Volunteering in Canada Archived
    Articles and reports: 11-008-X201200111638
    Geography: Canada
    Description:

    This article examines volunteering in Canada: volunteer rates, number of hours volunteered and types of organizations supported. It describes key socioeconomic characteristics of volunteers, types of volunteer activities, motivations for volunteering and barriers to volunteering. The article also examines "informal volunteering", that is, direct help provided to family, friends and neighbours. Data are from the 2010 Canada Survey on Giving, Volunteering and Participating.

    Release date: 2012-04-16
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