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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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Analysis (49)
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- 21. Seasonal adjustment of short series ArchivedArticles and reports: 11-522-X20030017693Description:
This paper evaluates changes in the quality performances of two different and widely used programs for seasonal adjustment, X-12-Regarima and Tramo-Seats, when the length of time series is progressively reduced.
Release date: 2005-01-26 - Articles and reports: 11-522-X20030017694Description:
This paper evaluates the performance of diagnostics for seasonal adjustment as they relate to the performance of X-12-ARIMA and SEATS on a large sample of real and simulated economic time series.
Release date: 2005-01-26 - Articles and reports: 11-522-X20030017695Description:
This paper proposes methods to correct a seasonally adjusted series so that its annual totals match those of the raw series. The methods are illustrated with a seasonally adjusted series obtained with either X-11-ARIMA or X-12-ARIMA.
Release date: 2005-01-26 - 24. Reporting on the quality of seasonal adjustment process at the Statistical Office for the European Commission ArchivedArticles and reports: 11-522-X20030017707Description:
The paper discusses the structure and the quality measures Eurostat uses to provide European Union and EU-Zone with economic seasonally adjusted series.
Release date: 2005-01-26 - Articles and reports: 12-001-X20010026097Description:
A compositional time series is defined as a multivariate time series in which each of the series has values bounded between zero and one and the sum of the series equals one at each time point. Data with such characteristics are observed in repeated surveys when a survey variable has a multinomial response but interest lies in the proportion of units classified in each of its categories. In this case, the survey estimates are proportions of a whole subject to a unity-sum constraint. In this paper we employ a state space approach for modelling compositional time series from repeated surveys taking into account the sampling errors. The additive logistic transformation is used in order to guarantee predictions and signal estimates bounded between zero and one which satisfy the unity-sum constraint. The method is applied to compositional data from the Brazilian Labour Force Survey. Estimates of the vector of proportions and the unemployment rate are obtained. In addition, the structural components of the signal vector, such as the seasonals and the trends, are produced.
Release date: 2002-02-28 - 26. The impact of different rotation patterns on the sampling variance of seasonally adjusted and trend estimates ArchivedArticles and reports: 12-001-X20000025536Description:
Many economic and social time series are based on sample surveys which have complex sample designs. The sample design affects the properties of the time series. In particular, the overlap of the sample from period to period affects the variability of the time series of survey estimates and the seasonally adjusted and trend estimates produced from them.
Release date: 2001-02-28 - 27. Multilevel modelling of complex survey longitudinal data with time varying random effects ArchivedArticles and reports: 12-001-X20000015178Description:
Longitudinal observations consist of repeated measurements on the same units over a number of occasions, with fixed or varying time spells between the occasions. Each vector observation can be viewed therefore as a time series, usually of short length. Analyzing the measurements for all the units permits the fitting of low-order time series models, despite the short lengths of the individual series.
Release date: 2000-08-30 - 28. 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
- 29. 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 - 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
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