Analysis

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:

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: 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: From July 2nd to August 6th, 2024, Statistics Canada conducted the Canadian Survey on Business Conditions. The purpose of this survey is to collect information on businesses in Canada related to emerging issues. This infographic presents key results from this.

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: Optimal oral health is an essential element of healthy aging. Oral health problems such as tooth loss, periodontal disease, and dry mouth accumulate throughout adult life and worsen with increasing age. Using data from the 2019/2020 Canadian Health Survey on Seniors, this study explores the link between dental insurance, income, and oral health care access among seniors (aged 65 and over) in Canada. It contributes to the understanding of oral health care among seniors before the implementation of the Canadian Dental Care Plan.

Description: This paper describes the composition of the Consumer Price Index (CPI) basket and the changes introduced with the 2024 basket update, based on 2023 expenditure weights.

Description: This article examines trends in rates of employment and unemployment, as well as hourly wages and work hours, for the year 2023, and explores how disability intersects with age, sex, educational attainment, and racialized groups to influence labour market outcomes.

Description: With the proportion of small businesses making up nearly all of the employer businesses in Canada, small businesses are an important role in employing Canadians and are a significant driver towards economic recovery. This article provides insights on the expectations of small businesses as well as the unique conditions faced by these businesses in the second quarter of 2024. It involves an examination of the data produced by the Canadian Survey on Business Conditions.

Description: The purpose of this document is to define the concept of peer groups, to give an overview of how they are created and to demonstrate their usefulness. This paper presents the 2023 classification of the peer groups.

Description: This paper investigates the effects of the COVID-19 pandemic on inbound visitors to Canada, and their tourism-related spending, covering the period from 2018 to 2023.

Description: This study examines the economic footprint created by the Canadian research and development pharmaceutical sector on the Canadian economy in 2021, including a focus on the contribution of Innovative Medicines Canada’s members. While the impact of the sector’s medical research is well known, less known are the economic impacts of the sector on the Canadian economy, such as the value generated, the jobs supported and the investments made.

Description: This article takes a closer look into the largest contributors and detractors to growth in each province and territory in 2023. Using data from the May 1, 2024 provincial and territorial GDP by industry release as a starting point, a more comprehensive picture of each jurisdiction’s 2023 economic performance is presented by integrating other economic indicators such as population, prices and labour market measures, and by examining the context in which industries grew or contracted during the reference period.

Description: This fact sheet presents data on icebergs off the coast of Newfoundland and Labrador. The article covers reported iceberg data collected by the International Iceberg Patrol. It also covers how icebergs interact with ocean ecosystems, and the economic and cultural benefits that they provide in Newfoundland and Labrador.

Description: The document focuses on the evolution of Statistics Canada's labour productivity program, tracing its historical background, outlining its structure, as well as detailing the methodology and data sources used. It then discusses the diverse applications of provincial productivity data, identifies key users of productivity statistics, and highlights essential considerations for their interpretation. Finally, the document addresses the review process for quarterly and annual productivity measures and recent program improvements.

Description: Demographic documents is a series of texts intended for scholars and researchers, published occasionally by the Demography Division of Statistics Canada for their methodological, analytical or descriptive interest in the population field.

Description: This article presents results from the first Survey of Sexual Misconduct in the Canadian Armed Forces. Namely, the prevalence of general sexualized behaviour in the workplace; discrimination on the basis of sex, sexual orientation, or gender identity; personal experiences of discrimination or sexualized behaviour; the prevalence of sexual assault; and knowledge of policies on sexual misconduct and perceptions of responses to sexual misconduct are examined. Where possible, results are analyzed by sex, environmental command, type of service, age, rank, and number of years of service.

Description: This publication features short, informative articles focusing on specific justice-related issues. For more in-depth articles on justice in Canada, see also Juristat, Catalogue no. 85-002-X.

Description:

Each issue contains a short article highlighting statistical insights on themes relating to agriculture, food and rural issues.

Description: This publication presents energy balance sheets in natural units and heat equivalents in primary and secondary forms, by province. Each balance sheet shows data on production, trade, interprovincial movements, conversion and consumption by sector. Analytical tables and details on non-energy products are also included. It includes explanatory notes, a historical energy summary table and data analysis. The publication also presents data on natural gas liquids, electricity generated from fossil fuels, solid wood waste and spent pulping liquor.

Description: The Departmental Sustainable Development Strategy (DSDS) outlines departmental actions, with measurable performance indicators, that support the implementation strategies of the 2022-2026 Federal Sustainable Development Strategy. The DSDS further outlines Statistics Canada’s sustainable development vision to produce data to help track whether Canada is moving toward a more sustainable future and highlights projects with links to supporting sustainable development goals.

Description: This series provides detailed documentation on the issues, concepts, methodology, data quality and other relevant research related to household expenditures from the Survey of Household Spending, the Homeowner Repair and Renovation Survey and the Food Expenditure Survey.

Description: This report summarizes the annual achievements of the Methodology Research and Development Program (MRDP) sponsored by the Modern Statistical Methods and Data Science Branch at Statistics Canada. This program covers research and development activities in statistical methods with potentially broad application in the agency’s statistical programs; these activities would otherwise be less likely to be carried out during the provision of regular methodology services to those programs. The MRDP also includes activities that provide support in the application of past successful developments in order to promote the use of the results of research and development work. Selected prospective research activities are also presented.

Description: The series covers environment accounts and indicators, environmental surveys, spatial environmental information and other research related to environmental statistics. The technical paper series is intended to stimulate discussion on a range of environmental topics.

Description: This series of analytical articles provides insights on the socio-economic environment in rural communities in Canada. New articles will be released periodically.