Weighting and estimation
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All (638)
All (638) (0 to 10 of 638 results)
- Articles and reports: 12-001-X202600100003Description: Probability-proportional-to-size sampling is widely used by national statistical offices. Here population units are selected with probabilities proportional to an auxiliary variable. Variance formulas in such designs require both first- and second-order inclusion probabilities. The computation of second-order inclusion probabilities is particularly challenging for large populations, and has been the subject of extensive research. This article presents some new exact and approximation formulas for second-order inclusion probabilities in randomized systematic sampling with unequal probabilities and without replacement.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100005Description: Confidence intervals are very often constructed based on a probability distribution that uses a certain number of degrees of freedom as a parameter. This is the case with the Student and the modified Wilson confidence intervals, discussed in this article, which use quantiles from the Student distribution where the number of degrees of freedom is generally unknown. For the length of a confidence interval to be representative of the reliability of an estimate, the actual coverage rate must match the nominal rate. To that end, the number of degrees of freedom in the probability distribution used in practice to calculate the confidence interval must be estimated as precisely as possible. An approximate rule is often used, although it tends to overestimate the actual number of degrees of freedom. In this article, a more precise version of degrees of freedom, derived from the Satterthwaite approximation, is obtained in the context of the Canadian Census of Population. The sampling design is equivalent to a simple random design without replacement, cluster-stratified, and the variance estimation method is an adaptation of the balanced repeated replication method. An explicit expression of the degrees of freedom is obtained under these conditions, enabling the factors influencing them to be identified. For comparison, the degree of freedom formula is also established for the conventional variance estimator. A simulation study shows that using this version of degrees of freedom corrects the undercoverage problem observed with the approximate rule, showing the importance of accurately assessing this number.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100009Description: Combining estimates from independent surveys via inverse-variance weights can lead to negative bias when unknown variances are estimated and the target variable is non-negative and positively skewed. In such cases, strong positive correlations typically arise between the estimators and their corresponding variance estimators, causing standard linear combinations with inverse-variance weights to exhibit negative bias. We introduce a strikingly simple method to reduce bias: replace the standard weight with the ratio of the estimator to the variance estimator. Under a linear model linking the two, we show that the new ratio-weighted estimator is approximately unbiased, whereas the conventional inverse-variance combination exhibits downward bias. Through simulations, we demonstrate that the new method brings both the bias and the mean squared error closer to the optimum for a wide range of different target variables. As our method uses only standardly reported summary statistics, it can be immediately adopted to reduce this widespread bias and improve the reliability of scientific findings in various fields.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100010Description: With the exception of two-phase sampling, the standard variance approximation of the generalized regression (GREG) estimator assumes that the population totals in the weighting scheme are observed without error. If the weighting model of the GREG estimator contains population totals that are observed with measurement error sources other than the sampling error of first-phase estimates, then this uncertainty will be ignored by the variance approximation of the GREG estimator. This paper proposes a variance approximation for the GREG estimator that accounts for additional uncertainty arising from measurement error in one or more of the population totals used in the weighting scheme. This approach has been developed for, and is being applied to, the Dutch Labour Force Survey (DLFS). The monthly publications of the DLFS are obtained with a time series model, which corrects for rotation group bias and discontinuities caused by major redesigns and the loss of face-to-face interviews during COVID-19. The GREG estimates for the quarterly figures are benchmarked to the average of the monthly publications to enforce numerical consistency between monthly and quarterly publication tables. The standard variance approximation of the GREG estimator assumes that these population totals are observed without error. This results in an underestimation of the variance of the GREG estimator. The variance approximation proposed in this paper results in more realistic standard errors for the quarterly GREG estimates.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100011Description: We construct a hybrid Bayesian method, which includes a differentially private mechanism, to mask Census county totals for a U.S. state on acreage of a commodity. We use surrogates for data collected at the farm level from a past U.S. Census of Agriculture to illustrate our procedure. We use two Bayesian small area models (parametric and mixture) to accommodate the smaller counties with fewer farms and some counties with large acres. In these models, the Laplace distribution provides a differentially private mechanism. In pre-processing, we also incorporate the Census weights to form the observed total acreage, a scaling factor to the Laplace mechanism for each county, a square-root transformation of the observed total acreage to avoid negative masked estimates especially for small counties, and the p-percent rule and the 3+ rule to partition the counties into suppressed counties, non-sensitive counties and sensitive counties. Because of difficulties in specifying and tuning the privacy budget (an unknown parameter), to balance security and utility, we specify a prior for the privacy budget, where the values are not specified, and the Gibbs sampler is used to fit the hierarchical Bayesian models. In post-processing, we use Bayesian predictive inference to obtain masked county acreages, and this includes a benchmarking so that the masked state total matches the observed state total. As a measure of reliability of the Bayesian procedure, we use the posterior coefficients of variation for the masked posterior means of the counties. As a measure of utility, we use the absolute relative errors for the individual counties, together with other global measures. For the sensitive counties, there are some differences between the two small area models but both are much better than an individual area model; the mixture model being the best compromise for security and utility.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100012Description: We propose small area estimators of general indicators in off-census years, which avoid the use of deprecated census microdata, but are nearly optimal in census years. The procedure is based on replacing the obsolete census file with a larger unit-level survey that adequately covers the areas of interest and contains the values of useful auxiliary variables. However, the minimal data requirement of the proposed method is a single survey with microdata on the target variable and suitable auxiliary variables for the period of interest. We also develop an estimator of the mean squared error (MSE) that accounts for the uncertainty introduced by the large survey used to replace the census of auxiliary information. Our empirical results indicate that the proposed predictors perform clearly better than the alternative predictors when census data are outdated, and are very close to optimal ones when census data are correct. They also illustrate that the proposed total MSE estimator corrects for the bias of purely model-based MSE estimators that do not account for the large survey uncertainty.Release date: 2026-06-29
- Surveys and statistical programs – Documentation: 11-633-X2026002Description: Recent changes in Canada’s immigration levels have heightened interest in understanding how immigration affects housing demand. This article develops a methodological framework for projecting housing use associated with permanent residents (PRs) and non-permanent residents (NPRs) under alternative immigration scenarios. The framework applies observed per capita housing use rates from the Census of Population to estimate incremental housing use by tenure over time.Release date: 2026-04-24
- Articles and reports: 12-001-X202500200001Description: Nested error regression models are commonly used to incorporate unit specific auxiliary variables to improve small area estimates. When the mean structure of the model is misspecified, the design-based mean squared prediction error (MSPE) of Empirical Best Linear Unbiased Predictors (EBLUP) generally increases. The Observed Best Prediction (OBP) method has been proposed with the intent to improve on the design-based MSPE over EBLUP. In this paper, we conduct a Monte Carlo simulation experiments to understand the effect of misspsecification of mean structures on different small area estimators. Our findings suggest that the OBP using unit-level auxiliary variables does not outperform the EBLUP in terms of design-based MSPE, unless the number of small areas m is extremely large. Conversely, the performance of OBP significantly improves when area-level auxiliary variables are employed. This paper includes both analytical and numerical evidence to demonstrate these observations, providing practical insights for addressing model misspecification in small area estimation (SAE).Release date: 2025-12-23
- Articles and reports: 12-001-X202500200003Description: In this paper a model-based inference procedure based on a multivariate structural time series model is developed for the production of monthly figures about consumer confidence. The input for the model are five series of direct estimates for the indices that measure consumer confidence, which are derived from the Dutch Consumer Survey. The model improves the accuracy of the direct estimates, since it provides a better separation of measurement errors and sampling errors from estimated target parameters. The standard errors for the month-to-month changes are clearly smaller under the time series model. A second problem addressed in this paper is related to the transition to a new survey process in 2017. Structural time series models in combination with a parallel run are applied to estimate discontinuities induced by the redesign. An algorithm designed for the consumer confidence variables is developed to construct uninterrupted input series for the aforementioned structural time series model. This inference method facilitated a smooth transition to a new survey design and resulted in uninterrupted series about consumer confidence that date back to 1986. The method is implemented for the production of official monthly figures on consumer confidence in the Netherlands.Release date: 2025-12-23
- Articles and reports: 12-001-X202500200005Description: The use of non-probability data sources for statistical purposes and for official statistics has become increasingly popular in recent years. However, statistical inference based on non-probability samples is made more difficult by nature of their biasedness and lack of representativity. In this paper we propose quantile balancing inverse probability weighting estimator (QBIPW) for non-probability samples. We apply the idea of Harms and Duchesne (2006) allowing the use of quantile information in the estimation process to reproduce known totals and the distribution of auxiliary variables. We discuss the estimation of the QBIPW probabilities and its variance. Our simulation study has demonstrated that the proposed estimators are robust against model mis-specification and, as a result, help to reduce bias and mean squared error. Finally, we applied the proposed methods to estimate the share of job vacancies aimed at Ukrainian workers in Poland using an integrated set of administrative and survey data about job vacancies.Release date: 2025-12-23
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Analysis (610)
Analysis (610) (590 to 600 of 610 results)
- 591. Large scale imputation of survey data ArchivedArticles and reports: 12-001-X197800254833Description: Owners of small businesses complain about the quantity of forms they are required to collectors of statistics. Administrative data are an alternative source but do not usually include all the information required by the survey takers.The “Tax Data Imputation System” makes use of tax data collected from a large number of businesses by Revenue Canada and data obtained by sample survey for a small subset of these businesses. Survey data is imputed (estimated) for all the businesses not actually surveyed using a “hot-deck” technique, with adjustments made to ensure certain edit rules are satisfied. The results of a simulation study suggest that this procedure has reasonable statistical properties. Estimators (of means or totals) are unbiased with variances of comparable size to the corresponding ratio estimators.Release date: 1978-12-15
- 592. Alternative estimators in PPS sampling ArchivedArticles and reports: 12-001-X197800254835Description: Some estimators alternative to the usual PPS estimator are suggested in this paper for situations where the size measure used for PPS sampling is not correlated with the study variable and where data are available on another supplementary variable (size measure). Properties of these estimators are studied under super-population models and also empirically.Release date: 1978-12-15
- 593. Approximate tests of independence and goodness of fit based on stratified multi-stage samples ArchivedArticles and reports: 12-001-X197800154831Description: The impact on linear statistics of the sample design used in obtaining survey data is the subject of much of sampling literature. Recently, more attention has been paid to the design’s impact on non-linear statistics; the major factor inhibiting these investigations has been the problem of estimating at least the first two moments of such statistics. The present article examines the problem of estimating the variances of non-linear statistics from complex samples, in the light of existing literature. The behaviour of the chi-square statistic computed from a complex sample to test hypotheses of goodness of fit or independence is studied. Alternative tests are developed and their properties studied in simulation experiments.Release date: 1978-06-15
- 594. A comparison of correlated response variance estimates obtained in the 1961, 1971 and 1976 Censuses ArchivedArticles and reports: 12-001-X197800154833Description: The total variance of a survey estimate incorporates sampling variance, simple response variance and correlated response variance. The last component reflects the part of the total variance due to a common influence on a group of respondents. In the Canadian census, self-enumeration was adopted as the standard method of enumeration in the 1971 Census. One factor in favor of introducing this method was evidence, from the 1961 Census, that correlated response variance made an important contribution to the total variance of census estimates. Based on a study conducted using interpenetration of interviewers, this article compares correlated response variances from the 1961, 1971 and 1976 Censuses. The empirical results demonstrate that although the self-enumeration adopted in the 1971 Census did not completely remove the correlated response variance, this approach has considerably reduced the magnitude of this component of variance for almost all the characteristics examined.Release date: 1978-06-15
- Articles and reports: 12-001-X197800154835Description: Raking ratio estimators give estimates of the population values of characteristics examined on a sample basis utilizing the row and column totals of a contingency table of characteristics examined on a 100% basis. In this paper, the asymptotic variance of the maximum likelihood estimator of a sample characteristic subject to the marginal constraints of the above contingency table is derived. From this, we are able to compute the loss in efficiency of the raking ratio estimators relative to the maximum likelihood estimator in an empirical study.Release date: 1978-06-15
- 596. An investigation of the properties of raking ratio estimators: II with cluster sampling ArchivedArticles and reports: 12-001-X197700254829Description: Results of an earlier paper on the use of raking ratio estimators are extended to the case of cluster sampling. An empirical study is discussed.Release date: 1977-12-12
- 597. Synthetic estimation in periodic household surveys ArchivedArticles and reports: 12-001-X197700254832Description: In periodic household surveys, area samples are usually selected in geographic strata with probability of selection of areal units proportional to population size in these units. The design-based estimates for areas composed of domains within strata can have poor precision due to cluster sampling with a few primary sampling units per stratum. In this paper, synthetic estimates are investigated as an alternative to these estimates. An empirical evaluation based on the design of the Canadian Labour Force, Survey is given.Release date: 1977-12-12
- 598. Estimation of variance in multi-stage sampling ArchivedArticles and reports: 12-001-X197700100002Description: In multi-stage sampling when selection is without replacement at the first stage, estimation of the variance of the estimate of the population total is often done assuming sampling with replacement. This estimate is biased and the degree of bias is not negligible. In this paper, a procedure which gives unbiased estimates of the variance making use of only estimated primary sampling unit totals is suggested for the case when sampling at the second and subsequent stages is simple random without replacement. This procedure is based on sub-samples drawn from the selected second and subsequent stage units.Release date: 1977-06-20
- 599. An investigation of the properties of raking ratio estimators: I with simple random sampling ArchivedArticles and reports: 12-001-X197700100004Description: The 1971 and 1976 Censuses of Population and Housing have utilized the raking ratio estimation procedure to obtain estimates for variables collected only on a sample basis. This paper derives large sample approximations for the bias and variance of such estimates and examines their performance in an empirical study.Release date: 1977-06-20
- 600. Redesign of the sour cherry, peach and grape objective yield surveys in the Niagara Peninsula ArchivedArticles and reports: 12-001-X197700100005Description: Objective yield surveys have been conducted annually in the Niagara Peninsula since 1964. The aim of each of these annual surveys is to provide a forecast of the marketable production change in the region from the previous year. These estimates are determined far enough in advance of the harvest to enable them to serve as important factors in price negotiations between growers and processors, as well as indicators of particular crop situations which could necessitate immediate changes in strategy by the marketing agencies. In 1973 an extensive redesign project was initiated. This report provides a summary of the sample design, data collection procedures and estimation procedures which were incorporated in the redesign of the sour cherry, peach and grape objective yield surveys.Release date: 1977-06-20
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Reference (28)
Reference (28) (0 to 10 of 28 results)
- Surveys and statistical programs – Documentation: 11-633-X2026002Description: Recent changes in Canada’s immigration levels have heightened interest in understanding how immigration affects housing demand. This article develops a methodological framework for projecting housing use associated with permanent residents (PRs) and non-permanent residents (NPRs) under alternative immigration scenarios. The framework applies observed per capita housing use rates from the Census of Population to estimate incremental housing use by tenure over time.Release date: 2026-04-24
- Surveys and statistical programs – Documentation: 91-528-XDescription: The Technical Guide on Demographic Estimates at Statistics Canada provides detailed descriptions of the most current data sources and methods used by the Centre for demography at Statistics Canada to produce demographic estimates as part of the Demographic estimates program. They comprise postcensal and intercensal population estimates; base population; births and deaths; immigrants; emigrants; returning emigrants; non-permanent residents; interprovincial migration; subprovincial estimates of population and intraprovincial migration; population estimates by age and gender; and census family estimates. A glossary of commonly used terms is available at the end of the guide.Release date: 2025-12-17
- Surveys and statistical programs – Documentation: 98-306-XDescription:
This report describes sampling, weighting and estimation procedures used in the Census of Population. It provides operational and theoretical justifications for them, and presents the results of the evaluations of these procedures.
Release date: 2023-10-04 - Notices and consultations: 75F0002M2019006Description:
In 2018, Statistics Canada released two new data tables with estimates of effective tax and transfer rates for individual tax filers and census families. These estimates are derived from the Longitudinal Administrative Databank. This publication provides a detailed description of the methods used to derive the estimates of effective tax and transfer rates.
Release date: 2019-04-16 - 5. Revisions to 2006 to 2011 income data ArchivedSurveys and statistical programs – Documentation: 75F0002M2015003Description:
This note discusses revised income estimates from the Survey of Labour and Income Dynamics (SLID). These revisions to the SLID estimates make it possible to compare results from the Canadian Income Survey (CIS) to earlier years. The revisions address the issue of methodology differences between SLID and CIS.
Release date: 2015-12-17 - Surveys and statistical programs – Documentation: 13-605-X201500414166Description:
Estimates of the underground economy by province and territory for the period 2007 to 2012 are now available for the first time. The objective of this technical note is to explain how the methodology employed to derive upper-bound estimates of the underground economy for the provinces and territories differs from that used to derive national estimates.
Release date: 2015-04-29 - Surveys and statistical programs – Documentation: 99-002-X2011001Description:
This report describes sampling and weighting procedures used in the 2011 National Household Survey. It provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.
Release date: 2015-01-28 - Surveys and statistical programs – Documentation: 99-002-XDescription: This report describes sampling and weighting procedures used in the 2011 National Household Survey. It provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.Release date: 2015-01-28
- Surveys and statistical programs – Documentation: 92-568-XDescription:
This report describes sampling and weighting procedures used in the 2006 Census. It reviews the history of these procedures in Canadian censuses, provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.
Release date: 2009-08-11 - Surveys and statistical programs – Documentation: 71F0031X2006003Description:
This paper introduces and explains modifications made to the Labour Force Survey estimates in January 2006. Some of these modifications include changes to the population estimates, improvements to the public and private sector estimates and historical updates to several small Census Agglomerations (CA).
Release date: 2006-01-25