28 research outputs found
Armitage Lecture 2011: The Design and Analysis of Life History Studies
This is the peer reviewed version of the following article: Lawless, J.F. (2013). Armitage Lecture 2011: the design and analysis of life history studies. Statistics in Medicine, 32 (13), 2155--2172, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.5754/full. DOI: 10.1002/sim.5754 This article may be used for non-commercial purposes in accordance with
http://olabout.wiley.com/WileyCDA/Section/id-828039.html Wiley Terms and Conditions for Self-ArchivingLife history studies collect information on events and other outcomes during people’s lifetimes. For
example, these may be related to childhood development, education, fertility, health, or employment.
Such longitudinal studies have constraints on the selection of study members, the duration and frequency
of follow-up, and the accuracy and completeness of information obtained. These constraints,
along with factors associated with the definition and measurement of certain outcomes, affect our
ability to understand, model, and analyze life history processes. My objective here is to discuss and
illustrate some issues associated with the design and analysis of life history studies.Natural Sciences and Engineering Research Council of Canada || JFL RGPIN 859
Score Tests for Association Under Response-dependent Sampling Designs for Expensive Covariates
This is a pre-copyedited, author-produced PDF of an article accepted for publication in Biometrika following peer review. The version of record ``Derkach, A., Lawless, J.F. and Sun, L. (2015). Score tests for association under response-dependent sampling designs for expensive covariates. Biometrika, 102 (4), 988--994"is available online at: http://biomet.oxfordjournals.org/content/102/4/988.full.pdf+html}{DOI: 10.1093/biomet/asv038.Response-dependent sampling is widely used in settings where certain variables are expensive to obtain.
Estimation has been thoroughly investigated but recent applications have emphasized tests of
association for expensive covariates and a response variable. We consider testing and provide easily
implemented likelihood score tests for generalized linear models under a broad range of sampling
plans. We show that when there are no additional covariates, the score statistics are identical for conditional
and full likelihood approaches, and are of the same form as for ordinary random sampling.
Applications in genetics are discussed briefly.Natural Sciences and Engineering Research Council of Canada || (JFL RGPIN 8597)
Canadian Institutes of Health Research Strategic Training for Advanced Genetic Epidemiology fellowship (Lei Sun
Multistate Models with Intermittent Observation
The final publication: Lawless, J.F. and Nazeri Rad, N. (2015). Estimation and assessment of markov multistate models with intermittent observations on individuals. Lifetime Data Analysis, 21 (2), 160--179 is available at Springer via http://link.springer.com/article/10.1007/s10985-014-9310-z. DOI: 10.1007/s10985-014-9310-zMultistate models provide important methods of analysis for many life history processes, and this
is an area where John Klein made numerous contributions. When individuals in a study group are
observed continuously so that all transitions between states, and their times, are known, estimation
and model checking is fairly straightforward. However, individuals in many studies are observed intermittently,
and only the states occupied at the observation times are known. We review methods
of estimation and assessment for Markov models in this situation. Numerical studies that show the
effects of inter-observation times are provided, and new methods for assessing fit are given. An illustration
involving viral load dynamics for HIV-positive persons is presented.Natural Sciences and Engineering Research Council of Canada || (JFL RGPIN 8597
Statistical Issues in Modeling Chronic Disease in Cohort Studies
The final publication (Cook, R. J., & Lawless, J. F. (2014). Statistical issues in modeling chronic disease in cohort studies. Statistics in Biosciences, 6(1), 127-161. DOI: 10.1007/s12561-013-9087-8) is available at Springer via http://link.springer.com/article/10.1007/s12561-013-9087-8Observational cohort studies of individuals with chronic disease provide information on rates of
disease progression, the effect of fixed and time-varying risk factors, and the extent of heterogeneity
in the course of disease. Analysis of this information is often facilitated by the use of multistate
models with intensity functions governing transition between disease states. We discuss modeling
and analysis issues for such models when individuals are observed intermittently. Frameworks for
dealing with heterogeneity and measurement error are discussed including random effect models,
finite mixture models, and hidden Markov models. Cohorts are often defined by convenience and
ways of addressing outcome-dependent sampling or observation of individuals are also discussed.
Data on progression of joint damage in psoriatic arthritis and retinopathy in diabetes are analysed
to illustrate these issues and related methodology.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887
Cumulative processes related to event histories
Costs or benefits which accumulate for individuals over time are of interest in many life history processes. Familiar examples include costs of health care for persons with chronic medical conditions, the payments to insured persons during periods of disability, and quality of life which is
sometimes used in the evaluation of treatments in terminally ill patients. For convenience, here we use the term costs to refer to cost or other cumulative measures. Two important scenarios are (i) where costs are associated with the occurrence of certain events, so that total cost accumulates as a step function, and (ii) where individuals may move between various states over time, with cost accumulating at a constant rate determined by the state occupied. In both cases, there is
frequently a random variable T that represents the duration of the process generating the costs. Here we consider estimation of the mean cumulative cost over a period of interest using methods based upon marginal features of the cost process and intensity based models. Robustness to
adaptive censoring is discussed in the context of the multi-state methods. Data from a quality of life study of breast cancer patients are used to illustrate the methods.Peer Reviewe
A new perspective on loss to follow-up in failure time and life history studies
This is the peer reviewed version of the following article: Jerald F. Lawless and Richard
J. Cook, A new perspective on loss to follow-up in failure time and life history studies.
Statistics in Medicine (2019), 38(23): 4583–4610 which has been published in final form
at https://doi.org/10.1002/sim.8318.A framework is proposed for the joint modeling of life history and loss to follow-up (LTF) processes
in cohort studies. This framework provides a basis for discussing independence conditions
for LTF and censoring and examining the implications of dependent LTF.We consider failure time
and more general life history processes. The joint models are based on multistate processes with
expanded state spaces encompassing both the life history and LTF processes. Tracing studies are
discussed as a means of investigating the presence of dependent censoring and providing valid
estimates of transition intensities and state occupancy probabilities. Simulation studies and an
illustration based on a cohort of individuals with systemic lupus erythematosus demonstrate the
usefulness and properties of the proposed methods.Funding was provided by the Natural Sciences and Engineering Research Council of Canada (RGPIN
8597 for JFL; RGPIN 155849 and RGPIN 04207 for RJC) and the Canadian Institutes of Health Research
(FRN 13887 for RJC)
Governmental Context Determines Institutional Value: Independently Certified Performance and Failure in the Spanish Newspaper Industry
Many societies demand that independent professionals (e.g. auditors) certify the performance of firms. The value placed on such certification (i.e. the public perception of reliability/unreliability that may impact on an organization's success/failure) is not uniform, however, but contingent upon changing political contexts. This study presents and analyses data on the entire population of newspapers in Spain from 1966 to 1993, a time of peaceful transition from military dictatorship to capitalist democracy. Our results highlight the contingent nature of institutional life, demonstrating how changes in political contexts are associated with varying understandings of institutions. In particular, our findings support the prediction that, under a dictatorship, independently certified performance is not instrumental in organizational success or failure whereas, in a modern democracy, the certification process has a positive effect on the survival chances of firms.Publicad