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- 1. Inverse sampling design algorithms ArchivedArticles and reports: 12-001-X19970013101Description:
In the main body of statistics, sampling is often disposed of by assuming a sampling process that selects random variables such that they are independent and identically distributed (IID). Important techniques, like regression and contingency table analysis, were developed largely in the IID world; hence, adjustments are needed to use them in complex survey settings. Rather than adjust the analysis, however, what is new in the present formulation is to draw a second sample from the original sample. In this second sample, the first set of selections are inverted, so as to yield at the end a simple random sample. Of course, to employ this two-step process to draw a single simple random sample from the usually much larger complex survey would be inefficient, so multiple simple random samples are drawn and a way to base inferences on them developed. Not all original samples can be inverted; but many practical special cases are discussed which cover a wide range of practices.
Release date: 1997-08-18 - Articles and reports: 12-001-X19970013105Description:
The problem of estimating transition rates from longitudinal survey data in the presence of misclassification error is considered. Approaches which use external information on misclassification rates are reviewed, together with alternative models for measurement error. We define categorical instrumental variables and propose methods for the identification and estimation of models including such variables by viewing the model as a restricted latent class model. The numerical properties of the implied instrumental variable estimators of flow rates are studied using data from the Panel Study of Income Dynamics.
Release date: 1997-08-18 - Articles and reports: 11F0019M1997099Geography: CanadaDescription:
Context : Lung cancer has been the leading cause of cancer deaths in Canadian males for many years, and since 1994, this has been the case for Canadian femalesas well. It is therefore important to evaluate the resources required for its diagnosis and treatment. This article presents an estimate of the direct medical costsassociated with the diagnosis and treatment of lung cancer calculated through the use of a micro-simulation model. For disease incidence, 1992 was chosen as thereference year, whereas costs are evaluated according to the rates that prevailed in 1993.Methods : A model for lung cancer has been incorporated into the Population Health Model (POHEM). The parameters of the model were drawn in part fromStatistics Canada's Canadian Cancer Registry (CCR), which provides information on the incidence and histological classification of lung cancer cases in Canada.The distribution of cancer stage at diagnosis was estimated by using information from two provincial cancer registries. A team of oncologists derived "typical" treatment approaches reflective of current practice, and the associated direct costs were calculated for these approaches. Once this information and the appropriatesurvival curves were incorporated into the POHEM model, overall costs of treatment were estimated by means of a Monte Carlo simulation.Results: It is estimated that overall, the direct medical costs of lung cancer diagnosis and treatment were just over $528 million. The cost per year of life gained as aresult of treatment of the disease was approximately $19,450. For the first time in Canada, it was possible to estimate the five year costs following diagnosis, bystage of the disease at the time of diagnosis. It was possible to estimate the cost per year of additional life gained for three alternative treatments of non small-cell lungcancer (NSCLC). Sensitivity analyses showed that these costs varied between $1,870 and $6,860 per year of additional life gained, which compares favourablywith the costs that the treatment of other diseases may involve.Conclusions: Contrary to widespread perceptions, it appears that the treatment of lung cancer is effective from an economic standpoint. In addition, the use of amicro-simulation model such as POHEM not only makes it possible to incorporate information from various sources in a coherent manner but also offers thepossibility of estimating the effect of alternative medical procedures from the standpoint of financial pressures on the health care system.
Release date: 1997-04-22 - 4. Variance estimation for calibration estimators: A comparison of jackknifing versus Taylor linearization ArchivedArticles and reports: 12-001-X19960022978Description:
The use of auxiliary information in estimation procedures in complex surveys, such as Statistics Canada's Labour Force Survey, is becoming increasingly sophisticated. In the past, regression and raking ratio estimation were the commonly used procedures for incorporating auxiliary data into the estimation process. However, the weights associated with these estimators could be negative or highly positive. Recent theoretical developments by Deville and Sárndal (1992) in the construction of "restricted" weights, which can be forced to be positive and upwardly bounded, has led us to study the properties of the resulting estimators. In this paper, we investigate the properties of a number of such weight generating procedures, as well as their corresponding estimated variances. In particular, two variance estimation procedures are investigated via a Monte Carlo simulation study based on Labour Force Survey data; they are Jackknifing and Taylor Linearization. The conclusion is that the bias of both the point estimators and the variance estimators is minimal, even under severe "restricting" of the final weights.
Release date: 1997-01-30
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Articles and reports (4)
Articles and reports (4) ((4 results))
- 1. Inverse sampling design algorithms ArchivedArticles and reports: 12-001-X19970013101Description:
In the main body of statistics, sampling is often disposed of by assuming a sampling process that selects random variables such that they are independent and identically distributed (IID). Important techniques, like regression and contingency table analysis, were developed largely in the IID world; hence, adjustments are needed to use them in complex survey settings. Rather than adjust the analysis, however, what is new in the present formulation is to draw a second sample from the original sample. In this second sample, the first set of selections are inverted, so as to yield at the end a simple random sample. Of course, to employ this two-step process to draw a single simple random sample from the usually much larger complex survey would be inefficient, so multiple simple random samples are drawn and a way to base inferences on them developed. Not all original samples can be inverted; but many practical special cases are discussed which cover a wide range of practices.
Release date: 1997-08-18 - Articles and reports: 12-001-X19970013105Description:
The problem of estimating transition rates from longitudinal survey data in the presence of misclassification error is considered. Approaches which use external information on misclassification rates are reviewed, together with alternative models for measurement error. We define categorical instrumental variables and propose methods for the identification and estimation of models including such variables by viewing the model as a restricted latent class model. The numerical properties of the implied instrumental variable estimators of flow rates are studied using data from the Panel Study of Income Dynamics.
Release date: 1997-08-18 - Articles and reports: 11F0019M1997099Geography: CanadaDescription:
Context : Lung cancer has been the leading cause of cancer deaths in Canadian males for many years, and since 1994, this has been the case for Canadian femalesas well. It is therefore important to evaluate the resources required for its diagnosis and treatment. This article presents an estimate of the direct medical costsassociated with the diagnosis and treatment of lung cancer calculated through the use of a micro-simulation model. For disease incidence, 1992 was chosen as thereference year, whereas costs are evaluated according to the rates that prevailed in 1993.Methods : A model for lung cancer has been incorporated into the Population Health Model (POHEM). The parameters of the model were drawn in part fromStatistics Canada's Canadian Cancer Registry (CCR), which provides information on the incidence and histological classification of lung cancer cases in Canada.The distribution of cancer stage at diagnosis was estimated by using information from two provincial cancer registries. A team of oncologists derived "typical" treatment approaches reflective of current practice, and the associated direct costs were calculated for these approaches. Once this information and the appropriatesurvival curves were incorporated into the POHEM model, overall costs of treatment were estimated by means of a Monte Carlo simulation.Results: It is estimated that overall, the direct medical costs of lung cancer diagnosis and treatment were just over $528 million. The cost per year of life gained as aresult of treatment of the disease was approximately $19,450. For the first time in Canada, it was possible to estimate the five year costs following diagnosis, bystage of the disease at the time of diagnosis. It was possible to estimate the cost per year of additional life gained for three alternative treatments of non small-cell lungcancer (NSCLC). Sensitivity analyses showed that these costs varied between $1,870 and $6,860 per year of additional life gained, which compares favourablywith the costs that the treatment of other diseases may involve.Conclusions: Contrary to widespread perceptions, it appears that the treatment of lung cancer is effective from an economic standpoint. In addition, the use of amicro-simulation model such as POHEM not only makes it possible to incorporate information from various sources in a coherent manner but also offers thepossibility of estimating the effect of alternative medical procedures from the standpoint of financial pressures on the health care system.
Release date: 1997-04-22 - 4. Variance estimation for calibration estimators: A comparison of jackknifing versus Taylor linearization ArchivedArticles and reports: 12-001-X19960022978Description:
The use of auxiliary information in estimation procedures in complex surveys, such as Statistics Canada's Labour Force Survey, is becoming increasingly sophisticated. In the past, regression and raking ratio estimation were the commonly used procedures for incorporating auxiliary data into the estimation process. However, the weights associated with these estimators could be negative or highly positive. Recent theoretical developments by Deville and Sárndal (1992) in the construction of "restricted" weights, which can be forced to be positive and upwardly bounded, has led us to study the properties of the resulting estimators. In this paper, we investigate the properties of a number of such weight generating procedures, as well as their corresponding estimated variances. In particular, two variance estimation procedures are investigated via a Monte Carlo simulation study based on Labour Force Survey data; they are Jackknifing and Taylor Linearization. The conclusion is that the bias of both the point estimators and the variance estimators is minimal, even under severe "restricting" of the final weights.
Release date: 1997-01-30
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