Analysis

Description:

In 1997, the US Office of Management and Budget issued revised standards for the collection of race information within the federal statistical system. One revision allows individuals to choose more than one race group when responding to federal surveys and other federal data collections. This change presents challenges for analyses that involve data collected under both the old and new race-reporting systems, since the data on race are not comparable. The following paper discusses the problems encountered by these changes and methods developed to overcome them.

Since most people under both systems report only a single race, a common proposed solution is to try to bridge the transition by assigning a single-race category to each multiple-race reporter under the new system, and to conduct analyses using just the observed and assigned single-race categories. Thus, the problem can be viewed as a missing-data problem, in which single-race responses are missing for multiple-race reporters and needing to be imputed.

The US Office of Management and Budget suggested several simple bridging methods to handle this missing-data problem. Schenker and Parker (Statistics in Medicine, forthcoming) analysed data from the National Health Interview Survey of the US National Center for Health Statistics, which allows multiple-race reporting but also asks multiple-race reporters to specify a primary race, and found that improved bridging methods could result from incorporating individual-level and contextual covariates into the bridging models.

While Schenker and Parker discussed only three large multiple-race groups, the current application requires predicting single-race categories for several small multiple-race groups as well. Thus, problems of sparse data arise in fitting the bridging models. We address these problems by building combined models for several multiple-race groups, thus borrowing strength across them. These and other methodological issues are discussed.

Description:

Although the use of school vouchers is growing in the developing world, the impact of vouchers is an open question. Any sort of long-term assessment of this activity is rare. This paper estimates the long-term effect of Colombia's PACES program, which provided over 125,000 poor children with vouchers that covered half the cost of private secondary school.

The PACES program presents an unusual opportunity to assess the effect of demand-side education financing in a Latin American country where private schools educate a substantial proportion of pupils. The program is of special interest because many vouchers were assigned by lottery, so program effects can be reliably assessed.

We use administrative records to assess the long-term impact of PACES vouchers on high school graduation status and test scores. The principal advantage of administrative records is that there is no loss-to-follow-up and the data are much cheaper than a costly and potentially dangerous survey effort. On the other hand, individual ID numbers may be inaccurate, complicating record linkage, and selection bias contaminates the sample of test-takers. We discuss solutions to these problems. The results suggest that the program increased secondary school completion rates, and that college-entrance test scores were higher for lottery winners than losers.

Description:

The census data are widely used in the distribution and targeting of resources at national, regional and local levels. In the United Kingdom (UK), a population census is conducted every 10 years. As time elapses, the census data become outdated and less relevant, thus making the distribution of resources less equitable. This paper examines alternative methods in rectifying this.

A number of small area methods have been developed for producing postcensal estimates, including the Structural Preserving Estimation technique as a result of Purcell and Kish (1980). This paper develops an alternative approach that is based on a linear mixed modelling approach to producing postcensal estimates. The validity of the methodology is tested on simulated data from the Finnish population register and the technique is applied to producing updated estimates for a number of the 1991 UK census variables.

Description:

Nearly all surveys use complex sampling designs to collect data and these data are frequently used for statistical analyses beyond the estimation of simple descriptive parameters of the target population. Many procedures available in popular statistical software packages are not appropriate for this purpose because the analyses are based on the assumption that the sample has been drawn with simple random sampling. Therefore, the results of the analyses conducted using these software packages would not be valid when the sample design incorporates multistage sampling, stratification, or clustering. Two commonly used methods for analysing data from complex surveys are replication and Taylor linearization techniques. We discuss the use of WESVAR software to compute estimates and replicate variance estimates by properly reflecting complex sampling and estimation procedures. We also illustrate the WESVAR features by using data from two Westat surveys that employ complex survey designs: the Third International Mathematics and Science Study (TIMSS) and the National Health and Nutrition Examination Survey (NHANES).

Description:

For most survey samples, if not all, we have to deal with the problem of missing values. Missing values are usually caused by nonresponse (such as refusal of participant or interviewer was unable to contact respondent) but can also be produced at the editing step of the survey in an attempt to resolve problems of inconsistent or suspect responses. The presence of missing values (nonresponse) generally leads to bias and uncertainty in the estimates. To treat this problem, the appropriate use of all available auxiliary information permits the maximum reduction of nonresponse bias and variance. During this presentation, we will define the problem, describe the methodology that SEVANI is based on and discuss potential uses of the system. We will end the discussion by presenting some examples based on real data to illustrate the theory in practice.

In practice, it is very difficult to estimate the nonresponse bias. However, it is possible to estimate the nonresponse variance by assuming that the bias is negligible. In the last decade, many methods were indeed proposed to estimate this variance, and some of these have been implemented in the System for Estimation of Variance due to Nonresponse and Imputation (SEVANI).

The methodology used to develop SEVANI is based on the theory of two-phase sampling where we assume that the second phase of selection is nonresponse. However, contrary to two-phase sampling, an imputation or nonresponse model is required for variance estimation. SEVANI also assumes that nonresponse is treated by reweighting respondent units or by imputing their missing values. Three imputation methods are considered: the imputation of an auxiliary variable, regression imputation (deterministic or random) and nearest-neighbour imputation.

Description:

A wide class of models of interest in social and economic research can be represented by specifying a parametric structure for the covariances of observed variables. The availability of software, such as LISREL (Jöreskog and Sörbom 1988) and EQS (Bentler 1995), has enabled these models to be fitted to survey data in many applications. In this paper, we consider approaches to inference about such models using survey data derived by complex sampling schemes. We consider evidence of finite sample biases in parameter estimation and ways to reduce such biases (Altonji and Segal 1996) and associated issues of efficiency of estimation, standard error estimation and testing. We use longitudinal data from the British Household Panel Survey for illustration. As these data are subject to attrition, we also consider the issue of how to use nonresponse weights in the modelling.

Description:

Behavioural researchers use a variety of techniques to predict respondent scores on constructs that are not directly observable. Examples of such constructs include job satisfaction, work stress, aptitude for graduate study, children's mathematical ability, etc. The techniques commonly used for modelling and predicting scores on such constructs include factor analysis, classical psychometric scaling and item response theory (IRT), and for each technique there are often several different strategies that can be used to generate individual scores. However, researchers are seldom satisfied with simply measuring these constructs. They typically use the derived scores in multiple regression, analysis of variance and numerous multivariate procedures. Though using predicted scores in this way can result in biased estimates of model parameters, not all researchers are aware of this difficulty. The paper will review the literature on this issue, with particular emphasis on IRT methods. Problems will be illustrated, some remedies suggested, and areas for further research will be identified.

Description:

Analysis of dose-response relationships has long been important in toxicology. More recently, this type of analysis has been employed to evaluate public education campaigns. The data that are collected in such evaluations are likely to come from standard household survey designs with all the usual complexities of multiple stages, stratification and variable selection probabilities. On a recent evaluation, a system was developed with the following features: categorization of doses into three or four levels, propensity scoring of dose selection and a new jack-knifed Jonckheere-Terpstra test for a monotone dose-response relationship. This system allows rapid production of tests for monotone dose-response relationships that are corrected both for sample design and for confounding. The focus of this paper will be the results of a Monte-Carlo simulation of the properties of the jack-knifed Jonckheere-Terpstra.

Moreover, there is no experimental control over dosages and the possibility of confounding variables must be considered. Standard regressions in WESVAR and SUDAAN could be used to determine if there is a linear dose-response relationship while controlling on confounders, but such an approach obviously has low power to detect nonlinear but monotone dose-response relationships and is time-consuming to implement if there are a large number of possible outcomes of interest.

Description:

While censuses and surveys are often said to measure populations as they are, most reflect information about individuals as they were at the time of measurement, or even at some prior time point. Inferences from such data therefore should take into account change over time at both the population and individual levels. In this paper, we provide a unifying framework for such inference problems, illustrating it through a diverse series of examples including: (1) estimating residency status on Census Day using multiple administrative records, (2) combining administrative records for estimating the size of the US population, (3) using rolling averages from the American Community Survey, and (4) estimating the prevalence of human rights abuses.

Specifically, at the population level, the estimands of interest, such as the size or mean characteristics of a population, might be changing. At the same time, individual subjects might be moving in and out of the frame of the study or changing their characteristics. Such changes over time can affect statistical studies of government data that combine information from multiple data sources, including censuses, surveys and administrative records, an increasingly common practice. Inferences from the resulting merged databases often depend heavily on specific choices made in combining, editing and analysing the data that reflect assumptions about how populations of interest change or remain stable over time.

Description:

According to recent literature, the calibration method has gained much popularity on survey sampling and calibration estimators are routinely computed by many survey organizations. The choice of calibration variables for all existing approaches, however, remains ad hoc. In this article, we show that the model-calibration estimator for the finite population mean, which was proposed by Wu and Sitter (2001) through an intuitive argument, is indeed optimal among a class of calibration estimators. We further present optimal calibration estimators for the finite population distribution function, the population variance, variance of a linear estimator and other quadratic finite population functions under a unified framework. A limited simulation study shows that the improvement of these optimal estimators over the conventional ones can be substantial. The question of when and how auxiliary information can be used for both the estimation of the population mean using a generalized regression estimator and the estimation of its variance through calibration is addressed clearly under the proposed general methodology. Constructions of proposed estimators under two-phase sampling and some fundamental issues in using auxiliary information from survey data are also addressed under the context of optimal estimation.

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: 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: The authors used the Splink probabilistic linkage package developed by the UK Ministry of Justice, to link census data from England and Wales to itself to find duplicate census responses. A large gold standard of confirmed census duplicates was available meaning that the results of the Splink implementation could be quality assured. This paper describes the implementation and features of Splink, gives details of the settings and parameters that we used to tune Splink for our particular project, and gives the results that we obtained.

Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.

Description: In accordance with Statistics Canada’s long-term Disaggregated Data Action Plan (DDAP), several initiatives have been implemented into the Labour Force Survey (LFS). One of the more direct initiatives was a targeted increase in the size of the monthly LFS sample. Furthermore, a regular Supplement program was introduced, where an additional series of questions are asked to a subset of LFS respondents and analyzed in a monthly or quarterly production cycle. Finally, the production of modelled estimates based on Small Area Estimation (SAE) methodologies resumed for the LFS and will include a wider scope with more analytical value than what had existed in the past. This paper will give an overview of these three initiatives.

Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.

Description: The Australian Bureau of Statistics (ABS) is committed to improving access to more microdata, while ensuring privacy and confidentiality is maintained, through its virtual DataLab which supports researchers to undertake complex research more efficiently. Currently, the DataLab research outputs need to follow strict rules to minimise disclosure risks for clearance. However, the clerical-review process is not cost effective and has potential to introduce errors. The increasing number of statistical outputs from different projects can potentially introduce differencing risks even though these outputs from different projects have met the strict output rules. The ABS has been exploring the possibility of providing automatic output checking using the ABS cellkey methodology to ensure that all outputs across different projects are protected consistently to minimise differencing risks and reduce costs associated with output checking.

Description: With the availability of larger and more diverse data sources, Statistical Institutes in Europe are inclined to publish statistics on smaller groups than they used to do. Moreover, high impact global events like the Covid crisis and the situation in Ukraine may also ask for statistics on specific subgroups of the population. Publishing on small, targeted groups not only raises questions on statistical quality of the figures, it also raises issues concerning statistical disclosure risk. The principle of statistical disclosure control does not depend on the size of the groups the statistics are based on. However, the risk of disclosure does depend on the group size: the smaller a group, the higher the risk. Traditional ways to deal with statistical disclosure control and small group sizes include suppressing information and coarsening categories. These methods essentially increase the (mean) group sizes. More recent approaches include perturbative methods that have the intention to keep the group sizes small in order to preserve as much information as possible while reducing the disclosure risk sufficiently. In this paper we will mention some European examples of special focus group statistics and discuss the implications on statistical disclosure control. Additionally, we will discuss some issues that the use of perturbative methods brings along: its impact on disclosure risk and utility as well as the challenges in proper communication thereof.

Description: The publication of more disaggregated data can increase transparency and provide important information on underrepresented groups. Developing more readily available access options increases the amount of information available to and produced by researchers. Increasing the breadth and depth of the information released allows for a better representation of the Canadian population, but also puts a greater responsibility on Statistics Canada to do this in a way that preserves confidentiality, and thus it is helpful to develop tools which allow Statistics Canada to quantify the risk from the additional data granularity. In an effort to evaluate the risk of a database reconstruction attack on Statistics Canada’s published Census data, this investigation follows the strategy of the US Census Bureau, who outlined a method to use a Boolean satisfiability (SAT) solver to reconstruct individual attributes of residents of a hypothetical US Census block, based just on a table of summary statistics. The technique is expanded to attempt to reconstruct a small fraction of Statistics Canada’s Census microdata. This paper will discuss the findings of the investigation, the challenges involved in mounting a reconstruction attack, and the effect of an existing confidentiality measure in mitigating these attacks. Furthermore, the existing strategy is compared to other potential methods used to protect data – in particular, releasing tabular data perturbed by some random mechanism, such as those suggested by differential privacy.

Description: Education and training is acknowledged as fundamental for the development of a society. It is a complex multidimensional phenomenon, which determinants are ascribable to several interrelated familiar and socio-economic conditions. To respond to the demand of supporting statistical information for policymaking and its monitoring and evaluation process, the Italian National Statistical Institute (Istat) is renewing the education and training statistical production system, implementing a new thematic statistical register. It will be part of the Istat Integrated System of Registers, thus allowing relating the education and training phenomenon to other relevant phenomena, e.g. transition to work.

Description: Growing Up in Québec is a longitudinal population survey that began in the spring of 2021 at the Institut de la statistique du Québec. Among the children targeted by this longitudinal follow-up, some will experience developmental difficulties at some point in their lives. Those same children often have characteristics associated with higher sample attrition (low-income family, parents with a low level of education). This article describes the two main challenges we encountered when trying to ensure sufficient representativeness of these children, in both the overall results and the subpopulation analyses.

Description: In 2021, Statistics Canada initiated the Disaggregated Data Action Plan, a multi-year initiative to support more representative data collection methods, enhance statistics on diverse populations to allow for intersectional analyses, and support government and societal efforts to address known inequalities and bring considerations of fairness and inclusion into decision making. As part of this initiative, we are building the Survey Series on People and their Communities, a new probabilistic panel specifically designed to collect data that can be disaggregated according to racialized group. This new tool will allow us to address data gaps and emerging questions related to diversity. This paper will give an overview of the design of the Survey Series on People and their Communities.

Description: The Aboriginal Peoples Survey (APS) is a national survey on the social and economic conditions of First Nations people living off reserve, Métis and Inuit. The objectives of the APS are to identify the needs of these Aboriginal groups and to inform policy and programs aimed at improving the well-being of Aboriginal peoples. The APS aims to provide current and relevant data for a variety of stakeholders, including Aboriginal organizations, communities, service providers, researchers, governments, and the general public.

The 2012 APS represents the fourth cycle of the survey and focuses on issues of education, employment and health of First Nations people living off reserve, Métis and Inuit aged 6 years and over.

The 2017 APS represents the fifth cycle of the survey and focuses on participation in the Canadian economy, transferable skills, practical training, use of information technology and Aboriginal language attainment of First Nations people living off reserve, Métis and Inuit aged 15 years and over.

Description:

The Geography working paper series is intended to stimulate discussion on a variety of topics covering conceptual, methodological or technical work to support the development and dissemination of the division's data, products and services. Readers of the series are encouraged to contact the Geography Division with comments and suggestions.

Description:

As Statistics Canada celebrates a significant milestone in 2018, it is time to take a look back at our history to see where we have been and what we have done over the past century. At the same time, it is a chance to reflect on where the agency is headed in the future. This series of articles shows how our work has evolved since 1918: where we started, how we have evolved and what we do now.

Description:

This series of analytical reports provides an overview of the Canadian labour market experiences of immigrants to Canada, based on data from the Labour Force Survey. These reports examine the labour force characteristics of immigrants, by reporting on employment and unemployment at the Canada level, for the provinces and large metropolitan areas. They also provide more detailed analysis by region of birth, as well as in-depth analysis of other specific aspects of the immigrant labour market.

Description:

Historical works allow readers to peer into the past, not only to satisfy our curiosity about “the way things were,” but also to see how far we’ve come, and to learn from the past. For Statistics Canada, such works are also opportunities to commemorate the agency’s contributions to Canada and its people, and serve as a reminder that an institution such as this continues to evolve each and every day.

On the occasion of Statistics Canada’s 100th anniversary in 2018, Standing on the shoulders of giants: History of Statistics Canada: 1970 to 2008, builds on the work of two significant publications on the history of the agency, picking up the story in 1970 and carrying it through the next 36 years, until 2008. To that end, when enough time has passed to allow for sufficient objectivity, it will again be time to document the agency’s next chapter as it continues to tell Canada’s story in numbers.

Description: This publication presents an overview of recent economic developments in the provinces and territories. The overview covers several broad areas: 1) gross domestic product (GDP) by income and by expenditure, 2) GDP by industry, 3) labour productivity and other related variables.

The publication examines trends in the major aggregates that comprise GDP, both income- and expenditure-based, as well as prices and the financing of economic activity by institutional sector. GDP is also examined by industry. The productivity estimates are meant to assist in the analysis of the short-run relationship among the fluctuations of output, employment, compensation and hours worked. Some issues also contain more technical articles, explaining national accounts methodology or analysing a particular aspect of the economy.

This publication carries the detailed analyses, charts and statistical tables that, prior to its first issue, were released in The Daily (11-001-XIE) under the headings Provincial Economic Accounts and Provincial Gross Domestic Product by industry.

Description:

Understanding the role of women in Canadian society and how it has changed over time is dependent on having information that can begin to shed light on the diverse circumstances and experiences of women. Women in Canada provides an unparalleled compilation of data related to women's family status, education, employment, economic well-being, unpaid work, health, and more.

Women in Canada allows readers to better understand the experience of women compared to that of men. Recognizing that women are not a homogenous group and that experiences differ not only across gender but also within gender groups, Women in Canada includes chapters on immigrant women, women in a visible minority, Aboriginal women, senior women, and women with participation and activity limitations.

Description:

The publication provides data users, health professionals and individual Canadians with geometric means and selected percentiles of blood and urine concentrations of selected environmental chemicals for the Canadian population by sex and age group. The results presented in this publication were collected during cycle 4 of the Canadian Health Measures Survey from January 2014 to December 2015.

Description: In 2018, Statistics Canada will celebrate its 100th anniversary. As we count down to this important milestone, we would like to use our data to highlight some of the sweeping changes that have had a lasting impact on Canadian society and economy.

Description:

The Record Linkage Project Process Model (RLPPM) was developed by Statistics Canada to identify the processes and activities involved in record linkage. The RLPPM applies to linkage projects conducted at the individual and enterprise level using diverse data sources to create new data sources to meet analytical and operational needs.