| 1. |
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| 2. |
- Dehlendorff, Christian, et al.
(författare)
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Designing simulation experiments with controllable and uncontrollable factors for applications in healthcare
- 2011
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Ingår i: The Journal of the Royal Statistical Society, Series C. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 60:1, s. 31-49
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Tidskriftsartikel (refereegranskat)abstract
- We propose a new methodology for designing computer experiments that was inspired by the split-plot designs that are often used in physical experimentation. The methodology has been developed for a simulation model of a surgical unit in a Danish hospital. We classify the factors as controllable and uncontrollable on the basis of their characteristics in the physical system. The experiments are designed so that, for a given setting of the controllable factors, the various settings of the uncontrollable factors cover the design space uniformly. Moreover the methodology allows for overall uniform coverage in the combined design when all settings of the uncontrollable factors are considered at once
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| 3. |
- Guillot, Gilles, 1972, et al.
(författare)
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Spatial prediction of weed intensities from exact count data and image-based estimates
- 2009
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Ingår i: Journal of the Royal Statistical Society Series C-Applied Statistics. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 58, s. 525-542
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Tidskriftsartikel (refereegranskat)abstract
- Collecting weed exact counts in an agricultural field is easy but extremely time consuming. Image analysis algorithms for object extraction applied to pictures of agricultural fields may be used to estimate the weed content with a high resolution (about 1 m(2)), and pictures that are acquired at a large number of sites can be used to obtain maps of weed content over a whole field at a reasonably low cost. However, these image-based estimates are not perfect and acquiring exact weed counts also is highly useful both for assessing the accuracy of the image-based algorithms and for improving the estimates by use of the combined data. We propose and compare various models for image index and exact weed count and we use them to assess how such data should be combined to obtain reliable maps. The method is applied to a real data set from a 30-ha field. We show that using image estimates in addition to exact counts allows us to improve the accuracy of maps significantly. We also show that the relative performances of the methods depend on the size of the data set and on the specific methodology (full Bayes versus plug-in) that is implemented.
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| 4. |
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| 5. |
- Lambert, PC, et al.
(författare)
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Estimating the cure fraction in population-based cancer studies by using finite mixture models
- 2010
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Ingår i: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 59, s. 35-55
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The cure fraction (the proportion of patients who are cured of disease) is of interest to both patients and clinicians and is a useful measure to monitor trends in survival of curable disease. The paper extends the non-mixture and mixture cure fraction models to estimate the proportion cured of disease in population-based cancer studies by incorporating a finite mixture of two Weibull distributions to provide more flexibility in the shape of the estimated relative survival or excess mortality functions. The methods are illustrated by using public use data from England and Wales on survival following diagnosis of cancer of the colon where interest lies in differences between age and deprivation groups. We show that the finite mixture approach leads to improved model fit and estimates of the cure fraction that are closer to the empirical estimates. This is particularly so in the oldest age group where the cure fraction is notably lower. The cure fraction is broadly similar in each deprivation group, but the median survival of the ‘uncured’ is lower in the more deprived groups. The finite mixture approach overcomes some of the limitations of the more simplistic cure models and has the potential to model the complex excess hazard functions that are seen in real data.
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| 6. |
- Asar, O., et al.
(författare)
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Linear mixed effects models for non-Gaussian continuous repeated measurement data
- 2020
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Ingår i: Journal of the Royal Statistical Society Series C-Applied Statistics. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 69:5, s. 1015-1065
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Tidskriftsartikel (refereegranskat)abstract
- We consider the analysis of continuous repeated measurement outcomes that are collected longitudinally. A standard framework for analysing data of this kind is a linear Gaussian mixed effects model within which the outcome variable can be decomposed into fixed effects, time invariant and time-varying random effects, and measurement noise. We develop methodology that, for the first time, allows any combination of these stochastic components to be non-Gaussian, using multivariate normal variance-mean mixtures. To meet the computational challenges that are presented by large data sets, i.e. in the current context, data sets with many subjects and/or many repeated measurements per subject, we propose a novel implementation of maximum likelihood estimation using a computationally efficient subsampling-based stochastic gradient algorithm. We obtain standard error estimates by inverting the observed Fisher information matrix and obtain the predictive distributions for the random effects in both filtering (conditioning on past and current data) and smoothing (conditioning on all data) contexts. To implement these procedures, we introduce an R package: ngme. We reanalyse two data sets, from cystic fibrosis and nephrology research, that were previously analysed by using Gaussian linear mixed effects models.
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| 7. |
- Duffy, SW, et al.
(författare)
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Correcting for non-compliance bias in case-control studies to evaluate cancer screening programmes
- 2002
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Ingår i: The Journal of the Royal Statistical Society, Series C. - 0035-9254 .- 1467-9876. ; 51, s. 235-243
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Tidskriftsartikel (refereegranskat)abstract
- In the evaluation of uncontrolled service screening programmes for cancer, the case-control design is sometimes used, in which people who die from the disease in question are compared with live controls with respect to screening histories, Such a design tends to yield estimates of relative mortality in voluntary participants compared with non-participants. This may bias results, since compliers and non-compliers may differ a priori in ways which are not related to screening but which nevertheless affect the risk of death from the disease. We present a simple method, employing external data from previously published randomized controlled trials of screening, of correction for this bias. We illustrate it by using data from a case-control study performed within the invited arm of the Malmo mammographic screening trial, a prospective study from the service screening programme in two counties in Sweden, and a matched case-control study of mammographic screening in Florence, Italy.
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| 8. |
- Ecker, Kreske, et al.
(författare)
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Causal inference with a functional outcome
- 2024
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Ingår i: The Journal of the Royal Statistical Society, Series C. - : Oxford University Press. - 0035-9254 .- 1467-9876. ; 73:1, s. 221-240
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Tidskriftsartikel (refereegranskat)abstract
- This article presents methods to study the causal effect of a binary treatment on a functional outcome with observational data. We define a Functional Average Treatment Effect (FATE) and develop an outcome regression estimator. We show how to obtain valid inference on the FATE using simultaneous confidence bands, which cover the FATE with a given probability over the entire domain. Simulation experiments illustrate how the simultaneous confidence bands take the multiple comparison problem into account. Finally, we use the methods to infer the effect of early adult location on subsequent income development for one Swedish birth cohort.
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| 9. |
- Ginestet, PG, et al.
(författare)
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Stacked inverse probability of censoring weighted bagging: A case study in the InfCareHIV Register
- 2021
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Ingår i: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 70:1, s. 51-65
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- We propose an inverse probability of censoring weighted (IPCW) bagging (bootstrap aggregation) pre-processing that enables the application of any machine learning procedure for classification to be used to predict the cause-specific cumulative incidence, properly accounting for right-censored observations and competing risks. We consider the IPCW area under the time-dependent ROC curve (IPCW-AUC) as a performance evaluation metric. We also suggest a procedure to optimally stack predictions from any set of IPCW bagged methods. We illustrate our proposed method in the Swedish InfCareHIV register by predicting individuals for whom treatment will not maintain an undetectable viral load for at least 2 years following initial suppression. The R package stackBagg that implements our proposed method is available on Github.
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| 10. |
- Hoffmann, Till, et al.
(författare)
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Faecal shedding models for SARS-CoV-2 RNA among hospitalised patients and implications for wastewater-based epidemiology
- 2023
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Ingår i: The Journal of the Royal Statistical Society, Series C. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 72:2, s. 330-345
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Tidskriftsartikel (refereegranskat)abstract
- The concentration of SARS-CoV-2 RNA in faeces is not well characterised, posing challenges for quantitative wastewater-based epidemiology (WBE). We developed hierarchical models for faecal RNA shedding and fitted them to data from six studies. A mean concentration of 1.9 × 106 mL-1 (2.3 × 105–2.0 × 108 95% credible interval) was found among unvaccinated inpatients, not considering differences in shedding between viral variants. Limits of quantification could account for negative samples based on Bayesian model comparison. Inpatients represented the tail of the shedding profile with a half-life of 34 hours (28–43 95% credible interval), suggesting that WBE can be a leading indicator for clinical presentation. Shedding among inpatients could not explain the high RNA concentrations found in wastewater, consistent with more abundant shedding during the early infection course.
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