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- Articles and reports: 11-522-X20020016712Description:
In this paper, we consider the effect of the interval censoring of cessation time on intensity parameter estimation with regard to smoking cessation and pregnancy. The three waves of the National Population Health Survey allow the methodology of event history analysis to be applied to smoking initiation, cessation and relapse. One issue of interest is the relationship between smoking cessation and pregnancy. If a longitudinal respondent who is a smoker at the first cycle ceases smoking by the second cycle, we know the cessation time to within an interval of length at most a year, since the respondent is asked for the age at which she stopped smoking, and her date of birth is known. We also know whether she is pregnant at the time of the second cycle, and whether she has given birth since the time of the first cycle. For many such subjects, we know the date of conception to within a relatively small interval. If we knew the time of smoking cessation and pregnancy period exactly for each member who experienced one or other of these events between cycles, we could model their temporal relationship through their joint intensities.
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016714Description:
In this highly technical paper, we illustrate the application of the delete-a-group jack-knife variance estimator approach to a particular complex multi-wave longitudinal study, demonstrating its utility for linear regression and other analytic models. The delete-a-group jack-knife variance estimator is proving a very useful tool for measuring variances under complex sampling designs. This technique divides the first-phase sample into mutually exclusive and nearly equal variance groups, deletes one group at a time to create a set of replicates and makes analogous weighting adjustments in each replicate to those done for the sample as a whole. Variance estimation proceeds in the standard (unstratified) jack-knife fashion.
Our application is to the Chicago Health and Aging Project (CHAP), a community-based longitudinal study examining risk factors for chronic health problems of older adults. A major aim of the study is the investigation of risk factors for incident Alzheimer's disease. The current design of CHAP has two components: (1) Every three years, all surviving members of the cohort are interviewed on a variety of health-related topics. These interviews include cognitive and physical function measures. (2) At each of these waves of data collection, a stratified Poisson sample is drawn from among the respondents to the full population interview for detailed clinical evaluation and neuropsychological testing. To investigate risk factors for incident disease, a 'disease-free' cohort is identified at the preceding time point and forms one major stratum in the sampling frame.
We provide proofs of the theoretical applicability of the delete-a-group jack-knife for particular estimators under this Poisson design, paying needed attention to the distinction between finite-population and infinite-population (model) inference. In addition, we examine the issue of determining the 'right number' of variance groups.
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016743Description:
There is much interest in using data from longitudinal surveys to help understand life history processes such as education, employment, fertility, health and marriage. The analysis of data on the durations of spells or sojourns that individuals spend in certain states (e.g., employment, marriage) is a primary tool in studying such processes. This paper examines methods for analysing duration data that address important features associated with longitudinal surveys: the use of complex survey designs in heterogeneous populations; missing or inaccurate information about the timing of events; and the possibility of non-ignorable dropout or censoring mechanisms. Parametric and non-parametric techniques for estimation and for model checking are considered. Both new and existing methodology are proposed and applied to duration data from Canada's Survey of Labour and Income Dynamics (SLID).
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016744Description:
A developmental trajectory describes the course of a behaviour over age or time. This technical paper provides an overview of a semi-parametric, group-based method for analysing developmental trajectories. This methodology provides an alternative to assuming a homogenous population of trajectories as is done in standard growth modelling.
Four capabilities are described: (1) the capability to identify, rather than assume, distinctive groups of trajectories; (2) the capability to estimate the proportion of the population following each such trajectory group; (3) the capability to relate group membership probability to individual characteristics and circumstances; and (4) the capability to use the group membership probabilities for various other purposes, such as creating profiles of group members.
In addition, two important extensions of the method are described: the capability to add time-varying covariates to trajectory models and the capability to estimate joint trajectory models of distinct but related behaviours. The former provides the statistical capacity for testing if a contemporary factor, such as an experimental intervention or a non-experimental event like pregnancy, deflects a pre-existing trajectory. The latter provides the capability to study the unfolding of distinct but related behaviours such as problematic childhood behaviour and adolescent drug abuse.
Release date: 2004-09-13 - Articles and reports: 12-001-X20040016998Description:
The Canadian Labour Force Survey (LFS) was not designed to be a longitudinal survey. However, given that respondent households typically remain in the sample for six consecutive months, it is possible to reconstruct six-month fragments of longitudinal data from the monthly records of household members. Such longitudinal micro-data - altogether consisting of millions of person-months of individual and family level data - is useful for analyses of monthly labour market dynamics over relatively long periods of time, 25 years and more.
We make use of these data to estimate hazard functions describing transitions among the labour market states: self-employed, paid employee and not employed. Data on job tenure, for employed respondents, and on the date last worked, for those not employed - together with the date of survey responses - allow the construction of models that include terms reflecting seasonality and macro-economic cycles as well as the duration dependence of each type of transition. In addition, the LFS data permits spouse labour market activity and family composition variables to be included in the hazard models as time-varying covariates. The estimated hazard equations have been incorporated in the LifePaths microsimulation model. In that setting, the equations have been used to simulate lifetime employment activity from past, present and future birth cohorts. Simulation results have been validated by comparison with the age profiles of LFS employment/population ratios for the period 1976 to 2001.
Release date: 2004-07-14 - Articles and reports: 12-002-X20040016904Description:
This article provides a practical example of the development of a survival analysis model. It begins with an overview of the software tool that was used, SAS. The next section examines the construction of a longitudinal file and the challenges that may present. Of particular interest are explanatory variables that do not have a constant value over time. An example of a practical application is provided to illustrate the survival approach. The example consists of an analysis based on data from the Survey of Labour and Income Dynamics (SLID), specifically data from panel 1 between January 1993 and December 1998. Survey information in vector form is used to develop a Cox semi-parametric model. Comments are provided on a sample computer program. The way in which the program handles the main variables is also discussed. The last section contains a brief description of the results of a relatively simple model.
Release date: 2004-04-15 - Articles and reports: 12-002-X20040016905Description:
Large data sets present several challenges to researchers, particularly to less experienced researchers. One of the most time-consuming and frustrating activities for beginning researchers, who do not have experience with large datasets, can be pruning or parsing the data set to only the variables and sample of interest. The production of an 'efficient' data file can assist in the increased performance of hardware and software as well as reducing frustration for the researcher. One way of producing a parsed efficient data file using a program called Stat/Transfer is presented.
Release date: 2004-04-15
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- Articles and reports: 11-522-X20020016712Description:
In this paper, we consider the effect of the interval censoring of cessation time on intensity parameter estimation with regard to smoking cessation and pregnancy. The three waves of the National Population Health Survey allow the methodology of event history analysis to be applied to smoking initiation, cessation and relapse. One issue of interest is the relationship between smoking cessation and pregnancy. If a longitudinal respondent who is a smoker at the first cycle ceases smoking by the second cycle, we know the cessation time to within an interval of length at most a year, since the respondent is asked for the age at which she stopped smoking, and her date of birth is known. We also know whether she is pregnant at the time of the second cycle, and whether she has given birth since the time of the first cycle. For many such subjects, we know the date of conception to within a relatively small interval. If we knew the time of smoking cessation and pregnancy period exactly for each member who experienced one or other of these events between cycles, we could model their temporal relationship through their joint intensities.
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016714Description:
In this highly technical paper, we illustrate the application of the delete-a-group jack-knife variance estimator approach to a particular complex multi-wave longitudinal study, demonstrating its utility for linear regression and other analytic models. The delete-a-group jack-knife variance estimator is proving a very useful tool for measuring variances under complex sampling designs. This technique divides the first-phase sample into mutually exclusive and nearly equal variance groups, deletes one group at a time to create a set of replicates and makes analogous weighting adjustments in each replicate to those done for the sample as a whole. Variance estimation proceeds in the standard (unstratified) jack-knife fashion.
Our application is to the Chicago Health and Aging Project (CHAP), a community-based longitudinal study examining risk factors for chronic health problems of older adults. A major aim of the study is the investigation of risk factors for incident Alzheimer's disease. The current design of CHAP has two components: (1) Every three years, all surviving members of the cohort are interviewed on a variety of health-related topics. These interviews include cognitive and physical function measures. (2) At each of these waves of data collection, a stratified Poisson sample is drawn from among the respondents to the full population interview for detailed clinical evaluation and neuropsychological testing. To investigate risk factors for incident disease, a 'disease-free' cohort is identified at the preceding time point and forms one major stratum in the sampling frame.
We provide proofs of the theoretical applicability of the delete-a-group jack-knife for particular estimators under this Poisson design, paying needed attention to the distinction between finite-population and infinite-population (model) inference. In addition, we examine the issue of determining the 'right number' of variance groups.
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016743Description:
There is much interest in using data from longitudinal surveys to help understand life history processes such as education, employment, fertility, health and marriage. The analysis of data on the durations of spells or sojourns that individuals spend in certain states (e.g., employment, marriage) is a primary tool in studying such processes. This paper examines methods for analysing duration data that address important features associated with longitudinal surveys: the use of complex survey designs in heterogeneous populations; missing or inaccurate information about the timing of events; and the possibility of non-ignorable dropout or censoring mechanisms. Parametric and non-parametric techniques for estimation and for model checking are considered. Both new and existing methodology are proposed and applied to duration data from Canada's Survey of Labour and Income Dynamics (SLID).
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016744Description:
A developmental trajectory describes the course of a behaviour over age or time. This technical paper provides an overview of a semi-parametric, group-based method for analysing developmental trajectories. This methodology provides an alternative to assuming a homogenous population of trajectories as is done in standard growth modelling.
Four capabilities are described: (1) the capability to identify, rather than assume, distinctive groups of trajectories; (2) the capability to estimate the proportion of the population following each such trajectory group; (3) the capability to relate group membership probability to individual characteristics and circumstances; and (4) the capability to use the group membership probabilities for various other purposes, such as creating profiles of group members.
In addition, two important extensions of the method are described: the capability to add time-varying covariates to trajectory models and the capability to estimate joint trajectory models of distinct but related behaviours. The former provides the statistical capacity for testing if a contemporary factor, such as an experimental intervention or a non-experimental event like pregnancy, deflects a pre-existing trajectory. The latter provides the capability to study the unfolding of distinct but related behaviours such as problematic childhood behaviour and adolescent drug abuse.
Release date: 2004-09-13 - Articles and reports: 12-001-X20040016998Description:
The Canadian Labour Force Survey (LFS) was not designed to be a longitudinal survey. However, given that respondent households typically remain in the sample for six consecutive months, it is possible to reconstruct six-month fragments of longitudinal data from the monthly records of household members. Such longitudinal micro-data - altogether consisting of millions of person-months of individual and family level data - is useful for analyses of monthly labour market dynamics over relatively long periods of time, 25 years and more.
We make use of these data to estimate hazard functions describing transitions among the labour market states: self-employed, paid employee and not employed. Data on job tenure, for employed respondents, and on the date last worked, for those not employed - together with the date of survey responses - allow the construction of models that include terms reflecting seasonality and macro-economic cycles as well as the duration dependence of each type of transition. In addition, the LFS data permits spouse labour market activity and family composition variables to be included in the hazard models as time-varying covariates. The estimated hazard equations have been incorporated in the LifePaths microsimulation model. In that setting, the equations have been used to simulate lifetime employment activity from past, present and future birth cohorts. Simulation results have been validated by comparison with the age profiles of LFS employment/population ratios for the period 1976 to 2001.
Release date: 2004-07-14 - Articles and reports: 12-002-X20040016904Description:
This article provides a practical example of the development of a survival analysis model. It begins with an overview of the software tool that was used, SAS. The next section examines the construction of a longitudinal file and the challenges that may present. Of particular interest are explanatory variables that do not have a constant value over time. An example of a practical application is provided to illustrate the survival approach. The example consists of an analysis based on data from the Survey of Labour and Income Dynamics (SLID), specifically data from panel 1 between January 1993 and December 1998. Survey information in vector form is used to develop a Cox semi-parametric model. Comments are provided on a sample computer program. The way in which the program handles the main variables is also discussed. The last section contains a brief description of the results of a relatively simple model.
Release date: 2004-04-15 - Articles and reports: 12-002-X20040016905Description:
Large data sets present several challenges to researchers, particularly to less experienced researchers. One of the most time-consuming and frustrating activities for beginning researchers, who do not have experience with large datasets, can be pruning or parsing the data set to only the variables and sample of interest. The production of an 'efficient' data file can assist in the increased performance of hardware and software as well as reducing frustration for the researcher. One way of producing a parsed efficient data file using a program called Stat/Transfer is presented.
Release date: 2004-04-15
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