Analysis

Description:

This paper will describe the multiple imputation of income in the National Health Interview Survey and discuss the methodological issues involved. In addition, the paper will present empirical summaries of the imputations as well as results of a Monte Carlo evaluation of inferences based on multiply imputed income items.

Analysts of health data are often interested in studying relationships between income and health. The National Health Interview Survey, conducted by the National Center for Health Statistics of the U.S. Centers for Disease Control and Prevention, provides a rich source of data for studying such relationships. However, the nonresponse rates on two key income items, an individual's earned income and a family's total income, are over 20%. Moreover, these nonresponse rates appear to be increasing over time. A project is currently underway to multiply impute individual earnings and family income along with some other covariates for the National Health Interview Survey in 1997 and subsequent years.

There are many challenges in developing appropriate multiple imputations for such large-scale surveys. First, there are many variables of different types, with different skip patterns and logical relationships. Second, it is not known what types of associations will be investigated by the analysts of multiply imputed data. Finally, some variables, such as family income, are collected at the family level and others, such as earned income, are collected at the individual level. To make the imputations for both the family- and individual-level variables conditional on as many predictors as possible, and to simplify modelling, we are using a modified version of the sequential regression imputation method described in Raghunathan et al. ( Survey Methodology, 2001).

Besides issues related to the hierarchical nature of the imputations just described, there are other methodological issues of interest such as the use of transformations of the income variables, the imposition of restrictions on the values of variables, the general validity of sequential regression imputation and, even more generally, the validity of multiple-imputation inferences for surveys with complex sample designs.

Description:

Missing data are a constant problem in large-scale surveys. Such incompleteness is usually dealt with either by restricting the analysis to the cases with complete records or by imputing, for each missing item, an efficiently estimated value. The deficiencies of these approaches will be discussed in this paper, especially in the context of estimating a large number of quantities. The main part of the paper will describe two examples of analyses using multiple imputation.

In the first, the International Labour Organization (ILO) employment status is imputed in the British Labour Force Survey by a Bayesian bootstrap method. It is an adaptation of the hot-deck method, which seeks to fully exploit the auxiliary information. Important auxiliary information is given by the previous ILO status, when available, and the standard demographic variables.

Missing data can be interpreted more generally, as in the framework of the expectation maximization (EM) algorithm. The second example is from the Scottish House Condition Survey, and its focus is on the inconsistency of the surveyors. The surveyors assess the sampled dwelling units on a large number of elements or features of the dwelling, such as internal walls, roof and plumbing, that are scored and converted to a summarizing 'comprehensive repair cost.' The level of inconsistency is estimated from the discrepancies between the pairs of assessments of doubly surveyed dwellings. The principal research questions concern the amount of information that is lost as a result of the inconsistency and whether the naive estimators that ignore the inconsistency are unbiased. The problem is solved by multiple imputation, generating plausible scores for all the dwellings in the survey.

Description:

In the United States, the National Health and Nutrition Examination Survey (NHANES) is linked to the National Health Interview Survey (NHIS) at the primary sampling unit level (the same counties, but not necessarily the same persons, are in both surveys). The NHANES examines about 5,000 persons per year, while the NHIS samples about 100,000 persons per year. In this paper, we present and develop properties of models that allow NHIS and administrative data to be used as auxiliary information for estimating quantities of interest in the NHANES. The methodology, related to Fay-Herriot (1979) small-area models and to calibration estimators in Deville and Sarndal (1992), accounts for the survey designs in the error structure.

Description:

Cancer surveillance research requires accurate estimates of risk factors at the small area level. These risk factors are often obtained from surveys such as the National Health Interview Survey (NHIS) or the Behavioral Risk Factors Surveillance Survey (BRFSS). Unfortunately, no one population-based survey provides ideal prevalence estimates of such risk factors. One strategy is to combine information from multiple surveys, using the complementary strengths of one survey to compensate for the weakness of the other. The NHIS is a nationally representative, face-to-face survey with a high response rate; however, it cannot produce state or substate estimates of risk factor prevalence because sample sizes are too small. The BRFSS is a state-level telephone survey that excludes non-telephone households and has a lower response rate, but does provide reasonable sample sizes in all states and many counties. Several methods are available for constructing small-area estimators that combine information from both the NHIS and the BRFSS, including direct estimators, estimators under hierarchical Bayes models and model-assisted estimators. In this paper, we focus on the latter, constructing generalized regression (GREG) and 'minimum-distance' estimators and using existing and newly developed small-area smoothing techniques to smooth the resulting estimators.

Description:

This study takes a look at the modelling methods used for public health data. Public health has a renewed interest in the impact of the environment on health. Ecological or contextual studies ideally investigate these relationships using public health data augmented with environmental characteristics in multilevel or hierarchical models. In these models, individual respondents in health data are the first level and community data are the second level. Most public health data use complex sample survey designs, which require analyses accounting for the clustering, nonresponse, and poststratification to obtain representative estimates of prevalence of health risk behaviours.

This study uses the Behavioral Risk Factor Surveillance System (BRFSS), a state-specific US health risk factor surveillance system conducted by the Center for Disease Control and Prevention, which assesses health risk factors in over 200,000 adults annually. BRFSS data are now available at the metropolitan statistical area (MSA) level and provide quality health information for studies of environmental effects. MSA-level analyses combining health and environmental data are further complicated by joint requirements of the survey sample design and the multilevel analyses.

We compare three modelling methods in a study of physical activity and selected environmental factors using BRFSS 2000 data. Each of the methods described here is a valid way to analyse complex sample survey data augmented with environmental information, although each accounts for the survey design and multilevel data structure in a different manner and is thus appropriate for slightly different research questions.

Description:

The objective of this study was to analyse the influence of community on individual health. The new Canadian Community Health Survey (CCHS) was used to derive individual health variables for Canadian residents aged 18 or older while community-level data were obtained from the Canadian 1996 Census of Population. Weighted logistic multilevel models and principal component analysis were used to analyse these data. After controlling for individual variables, there was little variation between communities. However, the influence of the community was more important for people with low family income than those with higher income.

Description:

This paper examines the simulation study that was conducted to assess the sampling scheme designed for the World Health Organization (WHO) Injection Safety Assessment Survey. The objective of this assessment survey is to determine whether facilities in which injections are given meet the necessary safety requirements for injection administration, equipment, supplies and waste disposal. The main parameter of interest is the proportion of health care facilities in a country that have safe injection practices.

The objective of this simulation study was to assess the accuracy and precision of the proposed sampling design. To this end, two artificial populations were created based on the two African countries of Niger and Burkina Faso, in which the pilot survey was tested. To create a wide variety of hypothetical populations, the assignment of whether a health care facility was safe or not was based on the different combinations of the population proportion of safe health care facilities in the country, the homogeneity of the districts in the country with respect to injection safety, and whether the health care facility was located in an urban or rural district.

Using the results of the simulation, a multi-factor analysis of variance was used to determine which factors affect the outcome measures of absolute bias, standard error and mean-squared error.

Description:

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.

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.

Description:

Some of the most commonly used statistical models are fitted using maximum likelihood (ML) or some extension of ML. Stata's ML command provides researchers and data analysts with a tool to develop estimation commands to fit their models using their data. Such models may include multiple equations, clustered observations, sampling weights and other survey design characteristics. These elements are discussed in this paper.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Using data from the Postsecondary Student Information System (PSIS) and the Census of Population, 2021, this infographic provides information on enrolment in Canadian public postsecondary institutions for transgender and non-binary people.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: The infographic uses data from the integrated file of the Postsecondary Student Information System, the 2016 Census, the 2021 Census and the T1 Family File to compare the job quality of Indigenous graduates with a bachelor's degree with that of non-racialized and non-Indigenous graduates two years after graduation. Job quality indicators include employment income, unionization rate, and employer pension plan coverage rate.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: With an increase in the number of international students and a greater need for affordable housing, questions have arisen about international students housing experiences. This article examines international students’ prevalence of living in unsuitable housing across municipalities enumerated in the 2021 Census of Population long-form questionnaire. The report also presents the rates of unsuitable housing for international students from different source countries and provides comparisons with Canadian-born students.

Description: Selecting immigrants with high levels of education increases their chances of economic success. Immigrants with a bachelor’s degree or higher are more adaptable to changes in the labour market and have steeper growth in employment earnings than those with a trades or high school education. However, many immigrants with a bachelor’s degree or higher have occupations that underutilize their skills, which can reduce their employment income, productivity and well-being. This article updates previously documented trends in education–occupation mismatch with census data from 2001 to 2021.

Description: It is well documented that earnings vary considerably by population group (White, Black, Latin American, etc.). One of the possible reasons may be the fact that educational attainment also varies considerably by population group. Currently, there is a lack of information on the educational pathways of individuals from various population groups who began a postsecondary education program. This article fills this gap by documenting various aspects of the postsecondary experience of different population groups with regard to bachelor’s degree programs.

Description: The impact of immigration on the destination country is contingent not only on the number of immigrants admitted but also on how many of them choose to stay and actively engage in the labour market. This article analyzes the active presence of adult immigrants since the 1990s. Active presence refers to the extent to which immigrants who were admitted to Canada during a specific period actively engage in Canadian society within a specific timeframe.

Description: Headline inflation in Canada reached a 40-year high in 2022. Rising prices reduced the purchasing power of people whose incomes were not keeping pace with inflation and the current high inflation in Canada, as well as in many other countries, may be caused by both demand and supply factors. This article examines whether the current high inflation in Canada is demand–pull or supply–push.

Description: The pandemic has had an unprecedented impact on the Canadian economy. This impact was uneven across different workers and businesses. However, there is little information available on how businesses were affected by and survived through the pandemic according to the characteristics of their owners, especially those owned by certain groups such as women and immigrants. This article uses a linkage of the monthly business openings and closures with the Canadian Employer-Employee Dynamics Database and the Canada Emergency Wage Subsidy to study the survival rate and employment growth of businesses by gender, and immigrant status of owners.

Description: This article explores trends in patent applications made by Canadian-resident businesses for advanced technologies from 2001 to 2019, drawing on Eurostat's aggregation of high-tech patents. Approximately one-third of applications fall under high-tech categories, the bulk of which were associated with Communication, Computer, and Automated business equipment technologies. While these fields saw growth until 2012, a subsequent decline occurred, notably in Computer and Electronic Product Manufacturing. Biotechnology, Semiconductors, and Lasers showed limited dynamism, while aviation technology applications surged by nearly twentyfold over the period.

Description: Digital Insights brings together a variety of data from across Statistics Canada and other sources to provide insights and analysis on the digital economy and society in Canada. The topics covered include: e-commerce, digital trade, cyber security and cybercrime, and the impacts of Internet and other technology use on the Canadian economy and society.

Description: This technical paper describes the collection of food price data and the methodologies that are used to provide Canadians with accurate and timely food inflation data in both the CPI and the monthly average retail prices table.

Description: This study compares the Government of Canada’s direct and indirect measures to support R&D, as captured by business innovation and growth support (BIGS) programs and the Scientific Research and Experimental Development (SR&ED) tax incentive program. BIGS and SR&ED are two central instruments that the Canadian government uses to stimulate R&D expenditures in the business sector.

Description:

Each issue of Health at a Glance consists of a short non-technical article on topics that feature statistics from health-related surveys and administrative data.

Description:

The National Apprenticeship Survey (NAS) looks at factors affecting the completion, certification and transition of apprentices to the labour market. The survey was a collaborative effort on the part of Employment and Social Development Canada (ESDC) and Statistics Canada. It is hoped that the findings will contribute to the ongoing dialogue by governments, industry and unions to ensure that the apprenticeship systems in Canada continue to respond to the demands of the 21st Century.

Description:

This series of analytical reports provides an overview of the labour market conditions among the Aboriginal off-reserve populations, based on estimates from the Labour Force Survey. These reports examine the Aboriginal labour force characteristics by Aboriginal identity, as well as diverse socio-economic and employment characteristics.

Description:

These analytical products present projections of the diversity of the Canadian population. The purpose of these projections is to paint a potential portrait of the composition of Canada’s population according to different ethnocultural and language characteristics, if certain population growth scenarios were to become reality in the future. Produced using Demosim, a microsimulation model, these projections cover characteristics such as place of birth, generation status, visible minority group, religion and mother tongue.

Description:

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.

Description:

The software is a free and user-friendly application which enables exporters and their agents (including service providers) to electronically report their goods directly to the Government of Canada thus eliminating the manual reporting process form (B13A). The CAED software features a Harmonized system commodity classification search, built-in encryption software, memorisable screens, extensive on-line help and Internet transmission capabilities.

Description:

This publication is a catalogue of strategies and mechanisms that a statistical organization should consider adopting, according to its particular context. This compendium is based on lessons learned and best practices of leadership and management of statistical agencies within the scope of Statistics Canada’s International Statistical Fellowship Program (ISFP). It contains four broad sections including, characteristics of an effective national statistical system; core management practices; improving, modernizing and finding efficiencies; and, strategies to better inform and engage key stakeholders.

Description:

This product is a series of geographic profiles that include provinces and territories as well as the four Inuit regions of Inuit Nunangat. This series presents a summary of characteristics about the Aboriginal population living in these areas. Demographic data and information on living arrangements of children, education, employment, income, housing, health and language are highlighted. Data for each Aboriginal group, as well as data for the non-Aboriginal population, are provided separately for select variables. Findings are based on the 2011 National Household Survey, the 2012 Canadian Community Health Survey, and the 2012 Aboriginal Peoples Survey.

Description:

The objective of this document is to present a proposed Statistical Framework for Energy in Canada, which will help guide data providers and users in the development of a strategic plan for addressing priority elements of the proposed framework.

The framework is intended to apply to energy statistics in Canada in general, with application across a broad range of stakeholders involved in the collection, dissemination and use of energy statistics, including provincial and territorial administrative and statistical agencies.

Description:

Aboriginal Statistics at a Glance provides data users with a thematic guide to Aboriginal data at Statistics Canada. It includes data for the First Nations (North American Indian), Métis, and Inuit populations. Each theme is illustrated with a chart presenting key indicators, a plain language definition of the indicator and links to related data tables and published articles to further assist users in meeting their data needs. Data sources include the 1996, 2001 and 2006 censuses of population, the 2006 Aboriginal Peoples Survey, the 2005 Canadian Community Health Survey, and the 2007/2008 Adult Correctional Services Survey.