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- 31. Particulate matter and daily mortality: Combining time series information from eight U.S. cities ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015656Description:
Time series studies have shown associations between air pollution concentrations and morbidity and mortality. These studies have largely been conducted within single cities, and with varying methods. Critics of these studies have questioned the validity of the data sets used and the statistical techniques applied to them; the critics have noted inconsistencies in findings among studies and even in independent re-analyses of data from the same city. In this paper we review some of the statistical methods used to analyze a subset of a national data base of air pollution, mortality and weather assembled during the National Morbidity and Mortality Air Pollution Study (NMMAPS).
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19990015688Description:
The geographical and temporal relationship between outdoor air pollution and asthma was examined by linking together data from multiple sources. These included the administrative records of 59 general practices widely dispersed across England and Wales for half a million patients and all their consultations for asthma, supplemented by a socio-economic interview survey. Postcode enabled linkage with: (i) computed local road density; (ii) emission estimates of sulphur dioxide and nitrogen dioxides, (iii) measured/interpolated concentration of black smoke, sulphur dioxide, nitrogen dioxide and other pollutants at practice level. Parallel Poisson time series analysis took into account between-practice variations to examine daily correlations in practices close to air quality monitoring stations. Preliminary analyses show small and generally non-significant geographical associations between consultation rates and pollution markers. The methodological issues relevant to combining such data, and the interpretation of these results will be discussed.
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19980015031Description:
The U.S. Third National Health and Nutrition Examination Survey (NHANES III) was carried out from 1988 to 1994. This survey was intended primarily to provide estimates of cross-sectional parameters believed to be approximately constant over the six-year data collection period. However, for some variable (e.g., serum lead, body mass index and smoking behavior), substantive considerations suggest the possible presence of nontrivial changes in level between 1988 and 1994. For these variables, NHANES III is potentially a valuable source of time-change information, compared to other studies involving more restricted populations and samples. Exploration of possible change over time is complicated by two issues. First, there was of practical concern because some variables displayed substantial regional differences in level. This was of practical concern because some variables displayed substantial regional differences in level. Second, nontrivial changes in level over time can lead to nontrivial biases in some customary NHANES III variance estimators. This paper considers these two problems and discusses some related implications for statistical policy.
Release date: 1999-10-22 - 34. Probability of victimization over time: Results from the U.S. National Crime Victimization Survey ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015033Description:
Victimizations are not randomly scattered through the population, but tend to be concentrated in relatively few victims. Data from the U.S. National Crime Victimization Survey (NCVS), a multistage rotating panel survey, are employed to estimate the conditional probabilities of being a crime victim at time t given the victimization status in earlier interviews. Models are presented and fit to allow use of partial information from households that move in or out of the housing unit during the study period. The estimated probability of being a crime victim at interview t given the status at interview (t-l) is found to decrease with t. Possible implications for estimating cross-sectional victimization rates are discusssed.
Release date: 1999-10-22 - 35. Toward variances for X-11 seasonal adjustments ArchivedArticles and reports: 12-001-X19990014709Description: We develop an approach to estimating variances for X-11 seasonal adjustments that recognizes the effects of sampling error and errors from forecast extension. In our approach, seasonal adjustment error in the central values of a sufficiently long series results only from the effect of the X-11 filtering on the sampling errors. Towards either end of the series, we also recognize the contribution to seasonal adjustment error from forecast and backcast errors. We extend the approach to produce variances of errors in X-11 trend estimates, and to recognize error in estimation of regression coefficients used to model, e.g., calendar effects. In empirical results, the contribution of sampling error often dominated the seasonal adjustment variances. Trend estimate variances, however, showed large increases at the ends of series due to the effects of fore/backcast error. Nonstationarities in the sampling errors produced striking patterns in the seasonal adjustment and trend estimate variances.Release date: 1999-10-08
- 36. Price index surveys as quasi-longitudinal studies ArchivedArticles and reports: 12-001-X19980024351Description:
To calculate price indexes, data on "the same item" (actually a collection of items narrowly defined) must be collected across time periods. The question arises whether such "quasi-longitudinal" data can be modeled in such a way as to shed light on what a price index is. Leading thinkers on price indexes have questioned the feasibility of using statistical modeling at all for characterizing price indexes. This paper suggests a simple state space model of price data, yielding a consumer price index that is given in terms of the parameters of the model.
Release date: 1999-01-14 - Notices and consultations: 62-010-X19970023422Description:
The current official time base of the Consumer Price Index (CPI) is 1986=100. This time base was first used when the CPI for June 1990 was released. Statistics Canada is about to convert all price index series to the time base 1992=100. As a result, all constant dollar series will be converted to 1992 dollars. The CPI will shift to the new time base when the CPI for January 1998 is released on February 27th, 1998.
Release date: 1997-11-17 - Articles and reports: 12-001-X19960022979Description:
This paper empirically compares three estimation methods - regression, restricted regression, and principal person - used in a household survey of consumer expenditures. The three methods are applied to post-stratification which is important in many household surveys to adjust for under-coverage of the target population. Post-stratum population counts are typically available from an external census for numbers of persons but not for numbers of households. If household estimates are needed, a single weight must be assigned to each household while using the person counts for post-stratification. This is easily accomplished with regression estimators of totals or means by using person counts in each household's auxiliary data. Restricted regression estimation refines the weights by controlling extremes and can produce estimators with lower variance than Horvitz-Thompson estimators while still adhering to the population controls. The regression methods also allow controls to be used for both person-level counts and quantitative auxiliaries. With the principal person method, persons are classified into post-strata and person weights are ratio adjusted to achieve population control totals. This leads to each person in a household potentially having a different weight. The weight associated with the "principal person" is then selected as the household weight. We will compare estimated means from the three methods and their estimated standard errors for a number of expenditures from the Consumer Expenditure survey sponsored by the U.S. Bureau of Labor Statistics.
Release date: 1997-01-30 - 39. A new method to reduce unwanted ripples and revisions in trend-cycle estimates from X-11-ARIMA ArchivedArticles and reports: 12-001-X199600114383Description:
The estimation of the trend-cycle with the X-11-ARIMA method is often done using the 13-term Henderson filter applied to seasonally adjusted data modified by extreme values. This filter however, produces a large number of unwanted ripples in the final or “historical” trend-cycle curve which are interpreted as false turning points. The use of a longer Henderson filter such as the 23-term is not an alternative for this filter is sluggish to detect turning points and consequently is not useful for current economic and business analysis. This paper proposes a new method that enables the use of the 13-term Henderson filter with the advantages of: (i) reducing the number of unwanted ripples; (ii) reducing the size of the revisions to preliminary values and (iii) no increase in the time lag to detect turning points. The results are illustrated with nine leading indicator series of the Canadian Composite Leading Index.
Release date: 1996-06-14 - 40. Statistical process control of sampling frames ArchivedArticles and reports: 12-001-X199500214391Description:
Statistical process control can be used as a quality tool to assure the accuracy of sampling frames that are constructed periodically. Sampling frame sizes are plotted in a control chart to detect special causes of variation. Procedures to identify the appropriate time series (ARIMA) model for serially correlated observations are described. Applications of time series analysis to the construction of control charts are discussed. Data from the United States Department of Labor’s Unemployment Insurance Benefits Quality Control Program is used to illustrate the technique.
Release date: 1995-12-15
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- 31. A new method to reduce unwanted ripples and revisions in trend-cycle estimates from X-11-ARIMA ArchivedArticles and reports: 12-001-X199600114383Description:
The estimation of the trend-cycle with the X-11-ARIMA method is often done using the 13-term Henderson filter applied to seasonally adjusted data modified by extreme values. This filter however, produces a large number of unwanted ripples in the final or “historical” trend-cycle curve which are interpreted as false turning points. The use of a longer Henderson filter such as the 23-term is not an alternative for this filter is sluggish to detect turning points and consequently is not useful for current economic and business analysis. This paper proposes a new method that enables the use of the 13-term Henderson filter with the advantages of: (i) reducing the number of unwanted ripples; (ii) reducing the size of the revisions to preliminary values and (iii) no increase in the time lag to detect turning points. The results are illustrated with nine leading indicator series of the Canadian Composite Leading Index.
Release date: 1996-06-14 - 32. Statistical process control of sampling frames ArchivedArticles and reports: 12-001-X199500214391Description:
Statistical process control can be used as a quality tool to assure the accuracy of sampling frames that are constructed periodically. Sampling frame sizes are plotted in a control chart to detect special causes of variation. Procedures to identify the appropriate time series (ARIMA) model for serially correlated observations are described. Applications of time series analysis to the construction of control charts are discussed. Data from the United States Department of Labor’s Unemployment Insurance Benefits Quality Control Program is used to illustrate the technique.
Release date: 1995-12-15 - 33. Issues and strategies for small area data ArchivedArticles and reports: 12-001-X199400114436Description:
This paper identifies some technical issues in the provision of small area data derived from censuses, administrative records and surveys. Although the issues are of a general nature, they are discussed in the context of programs at Statistics Canada. For survey-based estimates, the need for developing an overall strategy is stressed and salient features of survey design that have an impact on small area data are highlighted in the context of redesigning a household survey. A brief review of estimation methods with their strengths and weaknesses is also presented.
Release date: 1994-06-15 - 34. Maximum likelihood estimation of constant multiplicative bias benchmarking model with application ArchivedArticles and reports: 12-001-X199300214457Description:
The maximum likelihood estimation of a non-linear benchmarking model, proposed by Laniel and Fyfe (1989; 1990), is considered. This model takes into account the biases and sampling errors associated with the original series. Since the maximum likelihood estimators of the model parameters are not obtainable in closed forms, two iterative procedures to find the maximum likelihood estimates are discussed. The closed form expressions for the asymptotic variances and covariances of the benchmarked series, and of the fitted values are also provided. The methodology is illustrated using published Canadian retail trade data.
Release date: 1993-12-15 - Articles and reports: 12-001-X199100214505Description:
The X-11-ARIMA seasonal adjustment method and the Census X-11 variant use a standard ANOVA-F-test to assess the presence of stable seasonality. This F-test is applied to a series consisting of estimated seasonals plus irregulars (residuals) which may be (and often are) autocorrelated, thus violating the basic assumption of the F-test. This limitation has long been known by producers of seasonally adjusted data and the nominal value of the F statistic has been rarely used as a criterion for seasonal adjustment. Instead, producers of seasonally adjusted data have used rules of thumb, such as, F equal to or greater than 7. This paper introduces an exact test which takes into account autocorrelated residuals following an SMA process of the (0, q) (0, Q)_s type. Comparisons of this modified F-test and the standard ANOVA test of X-11-ARIMA are made for a large number of Canadian socio-economic series.
Release date: 1991-12-16 - 36. Benchmarking of economic time series ArchivedArticles and reports: 12-001-X199000214531Description:
Benchmarking is a method of improving estimates from a sub-annual survey with the help of corresponding estimates from an annual survey. For example, estimates of monthly retail sales might be improved using estimates from the annual survey. This article deals, first with the problem posed by the benchmarking of time series produced by economic surveys, and then reviews the most relevant methods for solving this problem. Next, two new statistical methods are proposed, based on a non-linear model for sub-annual data. The benchmarked estimates are then obtained by applying weighted least squares.
Release date: 1990-12-14 - Articles and reports: 12-001-X199000214532Description:
Births by census division are studied via graphs and maps for the province of Saskatchewan for the years 1986-87. The goal of the work is to see how births are related to time and geography by obtaining contour maps that display the birth phenomenon in a smooth fashion. A principal difficulty arising is that the data are aggregate. A secondary goal is to examine the extent to which the Poisson-lognormal can replace for data that are counts, the normal regression model for continuous variates. To this end a hierarchy of models for count-valued random variates are fit to the birth data by maximum likelihood. These models include: the simple Poisson, the Poisson with year and weekday effects and the Poisson-lognormal with year and weekday effects. The use of the Poisson-lognormal is motivated by the idea that important covariates are unavailable to include in the fitting. As the discussion indicates, the work is preliminary.
Release date: 1990-12-14 - 38. A method for the analysis of seasonal ARIMA models ArchivedArticles and reports: 12-001-X199000214533Description:
A commonly used model for the analysis of time series models is the seasonal ARIMA model. However, the survey errors of the input data are usually ignored in the analysis. We show, through the use of state-space models with partially improper initial conditions, how to estimate the unknown parameters of this model using maximum likelihood methods. As well, the survey estimates can be smoothed using an empirical Bayes framework and model validation can be performed. We apply these techniques to an unemployment series from the Labour Force Survey.
Release date: 1990-12-14 - Articles and reports: 12-001-X199000214534Description:
The common approach to small area estimation is to exploit the cross-sectional relationships of the data in an attempt to borrow information from one small area to assist in the estimation in others. However, in the case of repeated surveys, further gains in efficiency can be secured by modelling the time series properties of the data as well. We illustrate the idea by considering regression models with time varying, cross-sectionally correlated coefficients. The use of past relationships to estimate current means raises the question of how to protect against model breakdowns. We propose a modification which guarantees that the model dependent predictors of aggregates of the small area means coincide with the corresponding survey estimators and we explore the statistical properties of the modification. The proposed procedure is applied to data on home sale prices used for the computation of housing price indexes.
Release date: 1990-12-14 - Articles and reports: 12-001-X199000214535Description:
Papers by Scott and Smith (1974) and Scott, Smith, and Jones (1977) suggested the use of signal extraction results from time series analysis to improve estimates in repeated surveys, what we call the time series approach to estimation in repeated surveys. We review the underlying philosophy of this approach, pointing out that it stems from recognition of two sources of variation - time series variation and sampling variation - and that the approach can provide a unifying framework for other problems where the two sources of variation are present. We obtain some theoretical results for the time series approach regarding design consistency of the time series estimators, and uncorrelatedness of the signal and sampling error series. We observe that, from a design-based perspective, the time series approach trades some bias for a reduction in variance and a reduction in average mean squared error relative to classical survey estimators. We briefly discuss modeling to implement the time series approach, and then illustrate the approach by applying it to time series of retail sales of eating places and of drinking places from the U.S. Census Bureau’s Retail Trade Survey.
Release date: 1990-12-14
Reference (8)
Reference (8) ((8 results))
- Surveys and statistical programs – Documentation: 19-20-00012026002Description: This reference document provides answers on selected topics related to the use, interpretation, and calculation of trend-cycle estimates for seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment and trend-cycle estimation found in Statistics Canada publications and reference manuals.Release date: 2026-06-08
- Surveys and statistical programs – Documentation: 19-20-00012026001Description: This reference document provides nontechnical answers on selected topics related to the use and interpretation of seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment found in Statistics Canada publications and reference manuals.Release date: 2026-05-11
- Surveys and statistical programs – Documentation: 11-522-X19990015648Description:
We estimate the parameters of a stochastic model for labour force careers involving distributions of correlated durations employed, unemployed (with and without job search) and not in the labour force. If the model is to account for sub-annual labour force patterns as well as advancement towards retirement, then no single data source is adequate to inform it. However, it is possible to build up an approximation from a number of different sources.
Release date: 2000-03-02 - 4. Particulate matter and daily mortality: Combining time series information from eight U.S. cities ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015656Description:
Time series studies have shown associations between air pollution concentrations and morbidity and mortality. These studies have largely been conducted within single cities, and with varying methods. Critics of these studies have questioned the validity of the data sets used and the statistical techniques applied to them; the critics have noted inconsistencies in findings among studies and even in independent re-analyses of data from the same city. In this paper we review some of the statistical methods used to analyze a subset of a national data base of air pollution, mortality and weather assembled during the National Morbidity and Mortality Air Pollution Study (NMMAPS).
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19990015688Description:
The geographical and temporal relationship between outdoor air pollution and asthma was examined by linking together data from multiple sources. These included the administrative records of 59 general practices widely dispersed across England and Wales for half a million patients and all their consultations for asthma, supplemented by a socio-economic interview survey. Postcode enabled linkage with: (i) computed local road density; (ii) emission estimates of sulphur dioxide and nitrogen dioxides, (iii) measured/interpolated concentration of black smoke, sulphur dioxide, nitrogen dioxide and other pollutants at practice level. Parallel Poisson time series analysis took into account between-practice variations to examine daily correlations in practices close to air quality monitoring stations. Preliminary analyses show small and generally non-significant geographical associations between consultation rates and pollution markers. The methodological issues relevant to combining such data, and the interpretation of these results will be discussed.
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19980015031Description:
The U.S. Third National Health and Nutrition Examination Survey (NHANES III) was carried out from 1988 to 1994. This survey was intended primarily to provide estimates of cross-sectional parameters believed to be approximately constant over the six-year data collection period. However, for some variable (e.g., serum lead, body mass index and smoking behavior), substantive considerations suggest the possible presence of nontrivial changes in level between 1988 and 1994. For these variables, NHANES III is potentially a valuable source of time-change information, compared to other studies involving more restricted populations and samples. Exploration of possible change over time is complicated by two issues. First, there was of practical concern because some variables displayed substantial regional differences in level. This was of practical concern because some variables displayed substantial regional differences in level. Second, nontrivial changes in level over time can lead to nontrivial biases in some customary NHANES III variance estimators. This paper considers these two problems and discusses some related implications for statistical policy.
Release date: 1999-10-22 - 7. Probability of victimization over time: Results from the U.S. National Crime Victimization Survey ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015033Description:
Victimizations are not randomly scattered through the population, but tend to be concentrated in relatively few victims. Data from the U.S. National Crime Victimization Survey (NCVS), a multistage rotating panel survey, are employed to estimate the conditional probabilities of being a crime victim at time t given the victimization status in earlier interviews. Models are presented and fit to allow use of partial information from households that move in or out of the housing unit during the study period. The estimated probability of being a crime victim at interview t given the status at interview (t-l) is found to decrease with t. Possible implications for estimating cross-sectional victimization rates are discusssed.
Release date: 1999-10-22 - Notices and consultations: 62-010-X19970023422Description:
The current official time base of the Consumer Price Index (CPI) is 1986=100. This time base was first used when the CPI for June 1990 was released. Statistics Canada is about to convert all price index series to the time base 1992=100. As a result, all constant dollar series will be converted to 1992 dollars. The CPI will shift to the new time base when the CPI for January 1998 is released on February 27th, 1998.
Release date: 1997-11-17