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- Table: 89-26-0006Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.Release date: 2024-04-23
- Public use microdata: 89F0002XDescription: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.Release date: 2024-04-12
- Articles and reports: 12-001-X202300200011Description: The article considers sampling designs for populations that can be represented as a N × M matrix. For instance when investigating tourist activities, the rows could be locations visited by tourists and the columns days in the tourist season. The goal is to sample cells (i, j) of the matrix when the number of selections within each row and each column is fixed a priori. The ith row sample size represents the number of selected cells within row i; the jth column sample size is the number of selected cells within column j. A matrix sampling design gives an N × M matrix of sample indicators, with entry 1 at position (i, j) if cell (i, j) is sampled and 0 otherwise. The first matrix sampling design investigated has one level of sampling, row and column sample sizes are set in advance: the row sample sizes can vary while the column sample sizes are all equal. The fixed margins can be seen as balancing constraints and algorithms available for selecting such samples are reviewed. A new estimator for the variance of the Horvitz-Thompson estimator for the mean of survey variable y is then presented. Several levels of sampling might be necessary to account for all the constraints; this involves multi-level matrix sampling designs that are also investigated.Release date: 2024-01-03
- Stats in brief: 11-001-X201800817781Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2018-01-08
- 5. The DYSEM Microsimulation Modelling Platform ArchivedArticles and reports: 11-633-X2017008Description:
The DYSEM microsimulation modelling platform provides a demographic and socioeconomic core that can be readily built upon to develop custom dynamic microsimulation models or applications. This paper describes DYSEM and provides an overview of its intended uses, as well as the methods and data used in its development.
Release date: 2017-07-28 - Articles and reports: 82-003-X201700614829Description:
POHEM-BMI is a microsimulation tool that includes a model of adult body mass index (BMI) and a model of childhood BMI history. This overview describes the development of BMI prediction models for adults and of childhood BMI history, and compares projected BMI estimates with those from nationally representative survey data to establish validity.
Release date: 2017-06-21 - 7. Demosim 2017 ArchivedArticles and reports: 91-621-X2017001Description:
This document briefly describes Demosim, the microsimulation population projection model, how it works as well as its methods and data sources. It is a methodological complement to the analytical products produced using Demosim.
Release date: 2017-01-25 - 8. Demosim: An Overview of Methods and Data Sources ArchivedJournals and periodicals: 91-621-XDescription:
This document briefly describes Demosim, the microsimulation population projection model, how it works as well as its methods and data sources. It is a methodological complement to the analytical products produced using Demosim.
Release date: 2017-01-25 - Articles and reports: 82-003-X201600314338Description:
This paper describes the methods and data used in the development and implementation of the POHEM-Neurological meta-model.
Release date: 2016-03-16 - Articles and reports: 82-003-X201501214293Description:
The University of Wisconsin Cancer Intervention and Surveillance Modeling Network breast cancer microsimulation model was adapted to simulate breast cancer incidence and screening performance in Canada. The model considered effects of breast density on the sensitivity and specificity of screening. The model’s ability to predict age-specific incidence of breast cancer was assessed.
Release date: 2015-12-16
Data (2)
Data (2) ((2 results))
- Table: 89-26-0006Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.Release date: 2024-04-23
- Public use microdata: 89F0002XDescription: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.Release date: 2024-04-12
Analysis (25)
Analysis (25) (20 to 30 of 25 results)
- 21. Empirical comparison of small area estimation methods for the Italian Labour Force Survey ArchivedArticles and reports: 12-001-X199400214419Description:
The study was undertaken to evaluate some alternative small areas estimators to produce level estimates for unplanned domains from the Italian Labour Force Sample Survey. In our study, the small areas are the Health Service Areas, which are unplanned sub-regional territorial domains and were not isolated at the time of sample design and thus cut across boundaries of the design strata. We consider the following estimators: post-stratified ratio, synthetic, composite expressed as linear combination of synthetic and of post-stratified ratio, and sample size dependent. For all the estimators considered in this study, the average percent relative biases and the average relative mean square errors were obtained in a Monte Carlo study in which the sample design was simulated using data from the 1981 Italian Census.
Release date: 1994-12-15 - 22. Bias corrections for survey estimates from data with ratio imputed values for confounded nonresponse ArchivedArticles and reports: 12-001-X199400214423Description:
Most surveys suffer from the problem of missing data caused by nonresponse. To deal with this problem, imputation is often used to create a “completed data set”, that is, a data set composed of actual observations (for the respondents) and imputations (for the nonrespondents). Usually, imputation is carried out under the assumption of unconfounded response mechanism. When this assumption does not hold, a bias is introduced in the standard estimator of the population mean calculated from the completed data set. In this paper, we pursue the idea of using simple correction factors for the bias problem in the case that ratio imputation is used. The effectiveness of the correction factors is studied by Monte Carlo simulation using artificially generated data sets representing various super-populations, nonresponse rates, nonresponse mechanisms, and correlations between the variable of interest and the auxiliary variable. These correction factors are found to be effective especially when the population follows the model underlying ratio imputation. An option for estimating the variance of the corrected point estimates is also discussed.
Release date: 1994-12-15 - 23. Statistical matching: Use of auxiliary information as an alternative to the conditional independence assumption ArchivedArticles and reports: 12-001-X199300114475Description:
In the creation of micro-simulation databases which are frequently used by policy analysts and planners, several datafiles are combined by statistical matching techniques for enriching the host datafile. This process requires the conditional independence assumption (CIA) which could lead to serious bias in the resulting joint relationships among variables. Appropriate auxiliary information could be used to avoid the CIA. In this report, methods of statistical matching corresponding to three methods of imputation, namely, regression, hot deck, and log linear, with and without auxiliary information are considered. The log linear methods consist of adding categorical constraints to either the regression or hot deck methods. Based on an extensive simulation study with synthetic data, sensitivity analyses for departures from the CIA are performed and gains from using auxiliary information are discussed. Different scenarios for the underlying distribution and relationships, such as symmetric versus skewed data and proxy versus nonproxy auxiliary data, are created using synthetic data. Some recommendations on the use of statistical matching methods are also made. Specifically, it was confirmed that the CIA could be a serious limitation which could be overcome by the use of appropriate auxiliary information. Hot deck methods were found to be generally preferable to regression methods. Also, when auxiliary information is available, log linear categorical constraints can improve performance of hot deck methods. This study was motivated by concerns about the use of the CIA in the construction of the Social Policy Simulation Database at Statistics Canada.
Release date: 1993-06-15 - 24. County estimates of wheat production ArchivedArticles and reports: 12-001-X199100214501Description:
Although farm surveys carried out by the USDA are used to estimate crop production at the state and national levels, small area estimates at the county level are more useful for local economic decision making. County estimates are also in demand by companies selling fertilizers, pesticides, crop insurance, and farm equipment. Individual states often conduct their own surveys to provide data for county estimates of farm production. Typically, these state surveys are not carried out using probability sampling methods. An additional complication is that states impose the constraint that the sum of county estimates of crop production for all counties in a state be equal to the USDA estimate for that state. Thus, standard small area estimation procedures are not directly applicable to this problem. In this paper, we consider using regression models for obtaining county estimates of wheat production in Kansas. We describe a simulation study comparing the resulting estimates to those obtained using two standard small area estimators: the synthetic and direct estimators. We also compare several strategies for scaling the initial estimates so that they agree with the USDA estimate of the state production total.
Release date: 1991-12-16 - Articles and reports: 12-001-X197800254834Description: Frames designed for continuous surveys are sometimes used for ad hoc surveys which require selection of sampling units separate from those selected for the continuous survey. This paper presents an unbiased extension of Keyfitz’s (1951) sample updating method to the case where a portion of the frame has been reserved for surveys other than the main continuous survey. A simple although biased alternative is presented. The scope under Platek and Singh’s (1975) design strategy for an area based continuous survey requiring updating is then expanded to encompass rotation of first stage units, establishment of a separate special survey sub-frame, and procedures to prevent re-selection of ultimate sampling units. The methods are evaluated in a Monte Carlo study using Census data to simulate the design for the Canadian Labour Force Survey.Release date: 1978-12-15
Reference (1)
Reference (1) ((1 result))
- Surveys and statistical programs – Documentation: 11-522-X201300014290Description:
This paper describes a new module that will project families and households by Aboriginal status using the Demosim microsimulation model. The methodology being considered would assign a household/family headship status annually to each individual and would use the headship rate method to calculate the number of annual families and households by various characteristics and geographies associated with Aboriginal populations.
Release date: 2014-10-31
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