Simulations
Filter results by
Search HelpKeyword(s)
Type
Survey or statistical program
Results
All (27)
All (27) (10 to 20 of 27 results)
- 11. Modelling complex households and communities—Example of Demo4: Demographic module of the SustainCity project ArchivedArticles and reports: 11-522-X201300014279Description:
As part of the European SustainCity project, a microsimulation model of individuals and households was created to simulate the population of various European cities. The aim of the project was to combine several transportation and land-use microsimulation models (land-use modelling), add on a dynamic population module and apply these microsimulation approaches to three geographic areas of Europe (the Île-de-France region and the Brussels and Zurich agglomerations
Release date: 2014-10-31 - Articles and reports: 11-522-X201300014289Description:
This paper provides an overview of the main new features that will be added to the forthcoming version of the Demosim microsimulation projection model based on microdata from the 2011 National Household Survey. The paper first describes the additions to the base population, namely new variables, some of which are added to the National Household Survey data by means of data linkage. This is followed by a brief description of the methods being considered for the projection of language variables, citizenship and religion as examples of the new features for events simulated by the model.
Release date: 2014-10-31 - 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 - Articles and reports: 82-003-X201301011873Geography: CanadaDescription:
A computer simulation model of physical activity was developed for the Canadian adult population using longitudinal data from the National Population Health Survey and cross-sectional data from the Canadian Community Health Survey. The model is based on the Population Health Model (POHEM) platform developed by Statistics Canada. This article presents an overview of POHEM and describes the additions that were made to create the physical activity module (POHEM-PA). These additions include changes in physical activity over time, and the relationship between physical activity levels and health-adjusted life expectancy, life expectancy and the onset of selected chronic conditions. Estimates from simulation projections are compared with nationally representative survey data to provide an indication of the validity of POHEM-PA.
Release date: 2013-10-16 - Articles and reports: 11-522-X200600110445Description:
When Chiang's "standard" method is used, calculating life expectancy for (small) census agglomerations in Canada can produce estimates whose confidence intervals are too wide to be useful. However, we have been able to show that by combining small area estimation methods and simulation methods, we can obtain narrower confidence intervals.
Release date: 2008-03-17 - Articles and reports: 11-522-X20020016722Geography: CanadaDescription:
Colorectal cancer (CRC) is the second cause of cancer deaths in Canada. Randomized controlled trials (RCT) have shown the efficacy of screening using faecal occult blood tests (FOBT). A comprehensive evaluation of the costs and consequences of CRC screening for the Canadian population is required before implementing such a program. This paper evaluates whether or not the CRC screening is cost-effective. The results of these simulations will be provided to the Canadian National Committee on Colorectal Cancer Screening to help formulate national policy recommendations for CRC screening.
Statistics Canada's Population Health Microsimulation Model was updated to incorporate a comprehensive CRC screening module based on Canadian data and RCT efficacy results. The module incorporated sensitivity and specificity of FOBT and colonoscopy, participation rates, incidence, staging, diagnostic and therapeutic options, disease progression, mortality and direct health care costs for different screening scenarios. Reproducing the mortality reduction observed in the Funen screening trial validated the model.
Release date: 2004-09-13 - 17. Modeling the burden of cancer in Canada ArchivedArticles and reports: 82-005-X20020016479Geography: CanadaDescription:
The Population Health Model (POHEM) is a policy analysis tool that helps answer "what-if" questions about the health and economic burden of specific diseases and the cost-effectiveness of administering new diagnostic and therapeutic interventions. This simulation model is particularly pertinent in an era of fiscal restraint, when new therapies are generally expensive and difficult policy decisions are being made. More important, it provides a base for a broader framework to inform policy decisions using comprehensive disease data and risk factors. Our "base case" models comprehensively estimate the lifetime costs of treating breast, lung and colorectal cancer in Canada. Our cancer models have shown the large financial burden of diagnostic work-up and initial therapy, as well as the high costs of hospitalizing those dying of cancer. Our core cancer models (lung, breast and colorectal cancer) have been used to evaluate the impact of new practice patterns. We have used these models to evaluate new chemotherapy regimens as therapeutic options for advanced lung cancer; the health and financial impact of reducing the hospital length of stay for initial breast cancer surgery; and the potential impact of population-based screening for colorectal cancer. To date, the most interesting intervention we have studied has been the use of tamoxifen to prevent breast cancer among high risk women.
Release date: 2002-10-08 - Articles and reports: 12-001-X20020016424Description:
A variety of estimators for the variance of the General Regression (GREG) estimator of a mean have been proposed in the sampling literature, mainly with the goal of estimating the design-based variance. Under certain conditions, estimators can be easily constructed that are approximately unbiased for both the design-variance and the model-variance. Several dual-purpose estimators are studied here in single-stage sampling. These choices are robust estimators of a model-variance even if the model that motivates the GREG has an incorrect variance parameter.
A key feature of the robust estimators is the adjustment of squared residuals by factors analogous to the leverages used in standard regression analysis. We also show that the delete-one jackknife estimator implicitly includes the leverage adjustments and is a good choice from either the design-based or model-based perspective. In a set of simulations, these variance estimators have small bias and produce confidence intervals with near-nominal coverage rates for several sampling methods, sample sizes and populations in single-stage sampling.
We also present simulation results for a skewed population where all variance estimators perform poorly. Samples that do not adequately represent the units with large values lead to estimated means that are too small, variance estimates that are too small and confidence intervals that cover at far less than the nominal rate. These defects can be avoided at the design stage by selecting samples that cover the extreme units well. However, in populations with inadequate design information this will not be feasible.
Release date: 2002-07-05 - Articles and reports: 11F0019M1997099Geography: CanadaDescription:
Context : Lung cancer has been the leading cause of cancer deaths in Canadian males for many years, and since 1994, this has been the case for Canadian femalesas well. It is therefore important to evaluate the resources required for its diagnosis and treatment. This article presents an estimate of the direct medical costsassociated with the diagnosis and treatment of lung cancer calculated through the use of a micro-simulation model. For disease incidence, 1992 was chosen as thereference year, whereas costs are evaluated according to the rates that prevailed in 1993.Methods : A model for lung cancer has been incorporated into the Population Health Model (POHEM). The parameters of the model were drawn in part fromStatistics Canada's Canadian Cancer Registry (CCR), which provides information on the incidence and histological classification of lung cancer cases in Canada.The distribution of cancer stage at diagnosis was estimated by using information from two provincial cancer registries. A team of oncologists derived "typical" treatment approaches reflective of current practice, and the associated direct costs were calculated for these approaches. Once this information and the appropriatesurvival curves were incorporated into the POHEM model, overall costs of treatment were estimated by means of a Monte Carlo simulation.Results: It is estimated that overall, the direct medical costs of lung cancer diagnosis and treatment were just over $528 million. The cost per year of life gained as aresult of treatment of the disease was approximately $19,450. For the first time in Canada, it was possible to estimate the five year costs following diagnosis, bystage of the disease at the time of diagnosis. It was possible to estimate the cost per year of additional life gained for three alternative treatments of non small-cell lungcancer (NSCLC). Sensitivity analyses showed that these costs varied between $1,870 and $6,860 per year of additional life gained, which compares favourablywith the costs that the treatment of other diseases may involve.Conclusions: Contrary to widespread perceptions, it appears that the treatment of lung cancer is effective from an economic standpoint. In addition, the use of amicro-simulation model such as POHEM not only makes it possible to incorporate information from various sources in a coherent manner but also offers thepossibility of estimating the effect of alternative medical procedures from the standpoint of financial pressures on the health care system.
Release date: 1997-04-22 - Articles and reports: 75F0002M1993018Description:
This paper evaluates alternatives for weighting persons who join households after a respondent panel has been selected.
Release date: 1995-12-30
Data (1)
Data (1) ((1 result))
- 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) (0 to 10 of 25 results)
- 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
- 3. 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 - 5. 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 - 6. 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 - 9. Demosim 2015 ArchivedArticles and reports: 91-621-X2015001Description:
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: 2015-09-17 - 10. Modelling complex households and communities—Example of Demo4: Demographic module of the SustainCity project ArchivedArticles and reports: 11-522-X201300014279Description:
As part of the European SustainCity project, a microsimulation model of individuals and households was created to simulate the population of various European cities. The aim of the project was to combine several transportation and land-use microsimulation models (land-use modelling), add on a dynamic population module and apply these microsimulation approaches to three geographic areas of Europe (the Île-de-France region and the Brussels and Zurich agglomerations
Release date: 2014-10-31
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
- Date modified: