Analysis

Description:

This multivariate statistical analysis, which captures the number of prior police contacts of young people apprehended by the police, uses longitudinally linked records from the Incident-Based Uniform Crime Reporting Survey for 1995 to 2001.

Description:

Linearization (or Taylor series) methods are widely used to estimate standard errors for the co-efficients of linear regression models fit to multi-stage samples. When the number of primary sampling units (PSUs) is large, linearization can produce accurate standard errors under quite general conditions. However, when the number of PSUs is small or a co-efficient depends primarily on data from a small number of PSUs, linearization estimators can have large negative bias.

In this paper, we characterize features of the design matrix that produce large bias in linearization standard errors for linear regression co-efficients. We then propose a new method, bias reduced linearization (BRL), based on residuals adjusted to better approximate the covariance of the true errors. When the errors are independent and identically distributed (i.i.d.), the BRL estimator is unbiased for the variance. Furthermore, a simulation study shows that BRL can greatly reduce the bias, even if the errors are not i.i.d. We also propose using a Satterthwaite approximation to determine the degrees of freedom of the reference distribution for tests and confidence intervals about linear combinations of co-efficients based on the BRL estimator. We demonstrate that the jackknife estimator also tends to be biased in situations where linearization is biased. However, the jackknife's bias tends to be positive. Our bias-reduced linearization estimator can be viewed as a compromise between the traditional linearization and jackknife estimators.

Description:

In this paper, we discuss the analysis of complex health survey data by using multivariate modelling techniques. Main interests are in various design-based and model-based methods that aim at accounting for the design complexities, including clustering, stratification and weighting. Methods covered include generalized linear modelling based on pseudo-likelihood and generalized estimating equations, linear mixed models estimated by restricted maximum likelihood, and hierarchical Bayes techniques using Markov Chain Monte Carlo (MCMC) methods. The methods will be compared empirically, using data from an extensive health interview and examination survey conducted in Finland in 2000 (Health 2000 Study).

The data of the Health 2000 Study were collected using personal interviews, questionnaires and clinical examinations. A stratified two-stage cluster sampling design was used in the survey. The sampling design involved positive intra-cluster correlation for many study variables. For a closer investigation, we selected a small number of study variables from the health interview and health examination phases. In many cases, the different methods produced similar numerical results and supported similar statistical conclusions. Methods that failed to account for the design complexities sometimes led to conflicting conclusions. We also discuss the application of the methods in this paper by using standard statistical software products.

Description:

In this paper, we consider the effect of the interval censoring of cessation time on intensity parameter estimation with regard to smoking cessation and pregnancy. The three waves of the National Population Health Survey allow the methodology of event history analysis to be applied to smoking initiation, cessation and relapse. One issue of interest is the relationship between smoking cessation and pregnancy. If a longitudinal respondent who is a smoker at the first cycle ceases smoking by the second cycle, we know the cessation time to within an interval of length at most a year, since the respondent is asked for the age at which she stopped smoking, and her date of birth is known. We also know whether she is pregnant at the time of the second cycle, and whether she has given birth since the time of the first cycle. For many such subjects, we know the date of conception to within a relatively small interval. If we knew the time of smoking cessation and pregnancy period exactly for each member who experienced one or other of these events between cycles, we could model their temporal relationship through their joint intensities.

Description:

This paper explores the relationship between low income and prevalence of asthma. The genetic and environmental determinants are incompletely understood. It has been observed in a previous study that Canadians with low incomes are at increased risk of asthma. Based on data from 17,605 subjects 12 years of age or older who participated in the first cycle of the National Population Health Survey (NPHS) from 1994 to 1995, males and females with low incomes had 1.44- and 1.33-fold increases, respectively, in the prevalence of asthma compared with their counterparts with high incomes. However, there was no significant difference observed between middle and high income categories. Therefore, it is not clear if there is a more systematic relationship between income adequacy and asthma occurrence. A much larger sample size of the second cycle of the NPHS allowed us to further explore if the prevalence of asthma increases with decreasing income adequacy among Canadians.

Description:

In this highly technical paper, we illustrate the application of the delete-a-group jack-knife variance estimator approach to a particular complex multi-wave longitudinal study, demonstrating its utility for linear regression and other analytic models. The delete-a-group jack-knife variance estimator is proving a very useful tool for measuring variances under complex sampling designs. This technique divides the first-phase sample into mutually exclusive and nearly equal variance groups, deletes one group at a time to create a set of replicates and makes analogous weighting adjustments in each replicate to those done for the sample as a whole. Variance estimation proceeds in the standard (unstratified) jack-knife fashion.

Our application is to the Chicago Health and Aging Project (CHAP), a community-based longitudinal study examining risk factors for chronic health problems of older adults. A major aim of the study is the investigation of risk factors for incident Alzheimer's disease. The current design of CHAP has two components: (1) Every three years, all surviving members of the cohort are interviewed on a variety of health-related topics. These interviews include cognitive and physical function measures. (2) At each of these waves of data collection, a stratified Poisson sample is drawn from among the respondents to the full population interview for detailed clinical evaluation and neuropsychological testing. To investigate risk factors for incident disease, a 'disease-free' cohort is identified at the preceding time point and forms one major stratum in the sampling frame.

We provide proofs of the theoretical applicability of the delete-a-group jack-knife for particular estimators under this Poisson design, paying needed attention to the distinction between finite-population and infinite-population (model) inference. In addition, we examine the issue of determining the 'right number' of variance groups.

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

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

Description: This infographic details the prevalence of vitamin D inadequacy among the Canadian population aged 3 to 79 by focusing on risk factors as well as behaviours that can reduce the likelihood of low vitamin D.

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: This article provides insights into the rates of COVID-19 mortality among First Nations peoples and Métis living in private dwellings and the social determinants of COVID-19 mortality among these populations using data from the 2016 Canadian Census Health and Environment Cohorts linked to the Canadian Vital Statistics – Death Database from 2016 to 2021.

Description: This short video explains how it can be very effective for all levels of governments and organizations that serve communities to use disaggregated data to make evidence-informed public policy decisions. By using disaggregated data, policymakers are able to design more appropriate and effective policies that meet the needs of each diverse and unique Canadian.

Description: This short video explains how the use of disaggregated data can help policymakers to develop more targeted and effective policies by identifying the unique needs and challenges faced by different demographic groups.

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: 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: Over the last several years, recreational screen time has been increasing. During the COVID-19 pandemic, recreational screen time rose among Canadian youth and adults, and those who increased screen time had poorer self-reported mental health. Using data from the 2017, 2018, and 2021 Canadian Community Health Survey, the objective of this study was to compare recreational screen time behaviours before (2018) and during (2021) the pandemic, looking at patterns by sociodemographic subgroups of the Canadian population.

Description: The availability of measures to operationalize allostatic load—the cumulative toll on the body of responding to stressor demands—in population health surveys may differ across years or surveys, hampering analyses on the entire sampled population. In this study, the impacts of variable selection and calculation method were evaluated to generate an allostatic load index applicable across all cycles of the Canadian Health Measures Survey (CHMS). CHMS data were used to compare individual and population-level changes in scores for allostatic load indexes in which other commonly used measures were substituted for waist-to-hip ratio. Associations between the various constructs and indicators of socioeconomic position were then assessed to evaluate whether relationships were maintained across indexes.

Description: This series of regional maps shows the number of school-aged children eligible to primary and secondary instruction in English in Quebec by census subdivision, and the proportion of these children who attend or have attended an English-language school in Canada. All the information provided comes from the 2021 Census of Population and the 2022 Open Database of Educational Facilities.

Description: While many Canadians prefer to live in low-density housing, the supply of these units is linked to urban sprawl and attendant environmental and economic implications. This article examines recent trends of new housing supply and areas of urban sprawl in select Canadian cities. It also analyzes the characteristics of homeowners who live in neighbourhoods which have recently experienced urban sprawl.

Description: This study used Postsecondary Student Information System (PSIS) administrative data within the Education and Labour Market Longitudinal Platform to compare enrolment and persistence in postsecondary education (PSE) among high school graduates in British Columbia with and without special needs across five cohorts from 2010/2011 to 2014/2015 before and after controlling for several sociodemographic characteristics and academic achievement.

Description: This analysis compares the investment efforts of official language minority (OLM) owned businesses depending on whether they are located in a rural or urban area. The study is based on a model that uses a seemingly unrelated regression equation (SURE) system estimator to simultaneously assess the impact of determinants that explain the investment of businesses in rural and urban areas and to statistically test the differences between the two areas.

Description: This article examines the association between parents' housing wealth and the values of houses owned by their adult children. It also documents parent and child co-ownership arrangements. The article follows a previous article that examined the role that parents' property ownership played in the likelihood of homeownership for children born in the 1990s. These articles use residential property and ownership information from the Canadian Housing Statistics Program for the 2021 reference year for all provinces and territories, except Quebec and Saskatchewan.

Description: This article uses 12 months of data from the Labour Force Survey (LFS) and LFS supplement for 2022, and the 2016 General Social Survey on Canadians at Work and Home to explore several quality of employment indicators based on Statistics Canada's Statistical Framework on Quality of Employment among the core working age First Nations people living off reserve and Métis (18 to 64 years), in the 10 provinces.

Description: This thematic series groups different statistical products related to Indigenous peoples. It features analytical documents of varying scopes, such as population profiles, reference materials, data products (including tables and factsheets), among other document types.

Description: Every year, Statistics Canada collects data from hundreds of surveys. As the amount of data gathered increases, Statistics Canada has introduced infographics to help people, business owners, academics, and management at all levels, understand key information derived from the data. Infographics can be used to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and to monitor changes in variables over time.

These infographics will provide a quick overview of Statistics Canada survey data.

Description: Statistics Canada's Quality of Employment in Canada publication is intended to provide Canadians and Canadian organizations with a better understanding of quality of employment using an internationally-supported statistical framework. Quality of employment is approached as a multidimensional concept, characterized by different elements, which relate to human needs in various ways. To cover all relevant aspects, the framework identified seven dimensions and twelve sub-dimensions of quality of employment.

Description: Statistics Canada regularly prepares presentations with statistical findings about the country’s economy, society and environment. These presentations may be intended for conferences, meetings with stakeholders, or other events held throughout the year to provide Statistics Canada with an opportunity to promote the role of official statistics and to better understand data users’ needs. This series provides online access to these presentations as well as new presentations created to help communicate research findings on a wide range of subjects to a broad audience.

Description: Economic and Social Reports includes in-depth research, brief analyses, and current economic updates on a variety of topics, such as labour, immigration, education and skills, income mobility, well-being, aging, firm dynamics, productivity, economic transitions, and economic geography. All the papers are institutionally reviewed and the research and analytical papers undergo peer review to ensure that they conform to Statistics Canada's mandate as a governmental statistical agency and adhere to generally accepted standards of good professional practice.

Description: The newsletter offers information aimed at three main groups, businesses (small to medium), communities and ethno-cultural groups/communities. Articles and outreach materials will assist their understanding of national and local data from the many relevant sources found on the Statistics Canada website.

Description:

Health Reports, published by the Health Analysis Division of Statistics Canada, is a peer-reviewed journal of population health and health services research. It is designed for a broad audience that includes health professionals, researchers, policymakers, and the general public. The journal publishes articles of wide interest that contain original and timely analyses of national or provincial/territorial surveys or administrative databases. New articles are published electronically each month.

Health Reports had an impact factor of 5.0 for 2022 and a five-year impact factor of 5.6. All articles are indexed in PubMed. Our online catalogue is free and receives more than 700,000 visits per year. External submissions are welcome.

Description: Statistics Canada is committed to sharing our knowledge and expertise to help all Canadians develop their data literacy skills by developing a series of data literacy training resources. Data literacy is a key skill needed in the 21st century. It is generally described as the ability to derive meaning from data. Data literacy focuses on the competencies or skills involved in working with data, including the ability to read, analyze, interpret, visualize data, as well as to drive good decision-making.

Description: Once every five years, the Census of Population provides a detailed and comprehensive statistical portrait of Canada that is vital to our country. It is the primary source of sociodemographic data for specific population groups such as lone-parent families, Indigenous peoples, immigrants, seniors and language groups.

In order to help users of census products to better understand the various Census of Population concepts, Statistics Canada has developed, in the context of the activities of the 2021 Census and previous censuses, a collection of short videos. These videos are a reference source for users who are new to census concepts or those who have some experience with these concepts, but may need a refresher or would like to expand their knowledge.

Description: The Canadian Survey on Disability (CSD) is a national survey of Canadians aged 15 and over whose everyday activities are limited because of a long-term condition or health-related problem.

Description: This bulletin presents the most up-to-date available information extracted from all of the Aviation Statistics Centre's surveys. Regular features include releases on principal statistics for Canada's major air carriers, airport data, fare basis statistics and traffic data for Canada's most important markets.