JournalTOCs

Journal of the Royal Statistical Society Series C (Applied Statistics)
Journal Prestige (SJR): 1.982

Citation Impact (citeScore): 2
Number of Followers: 31

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0035-9254 - ISSN (Online) 1467-9876
Published by John Wiley and Sons

[1693 journals]

Recurrent events modelling of haemophilia bleeding events
- Authors: Andrew C. Titman; Martin J. Wolfsegger, Thomas F. Jaki
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2021-01-07T06:01:23-08:00
  DOI: 10.1111/rssc.12462
Bayesian semi‐parametric G‐computation for causal inference in a
cohort study with MNAR dropout and death
- Authors: Maria Josefsson; Michael J. Daniels
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2021-01-06T04:11:32-08:00
  DOI: 10.1111/rssc.12464
Linear mixed effects models for non‐Gaussian continuous repeated
measurement data
- Authors: Özgür Asar; David Bolin, Peter J. Diggle, Jonas Wallin
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1015-1065, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12405
  Issue No: Vol. 69, No. 5 (2020)
Bayesian analysis of tests with unknown specificity and sensitivity
- Authors: Andrew Gelman; Bob Carpenter
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1269-1283, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12435
  Issue No: Vol. 69, No. 5 (2020)
Circular regression trees and forests with an application to probabilistic
wind direction forecasting
- Authors: Moritz N. Lang; Lisa Schlosser, Torsten Hothorn, Georg J. Mayr, Reto Stauffer, Achim Zeileis
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1357-1374, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12437
  Issue No: Vol. 69, No. 5 (2020)
Sensitivity analysis for publication bias in meta‐analyses
- Authors: Maya B. Mathur; Tyler J. VanderWeele
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1091-1119, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12440
  Issue No: Vol. 69, No. 5 (2020)
Nested g‐computation: a causal approach to analysis of censored medical
costs in the presence of time‐varying treatment
- Authors: Andrew J. Spieker; Emily M. Ko, Jason A. Roy, Nandita Mitra
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1189-1208, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12441
  Issue No: Vol. 69, No. 5 (2020)
Markov switching modelling of shooting performance variability and
teammate interactions in basketball
- Authors: Marco Sandri; Paola Zuccolotto, Marica Manisera
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1337-1356, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12442
  Issue No: Vol. 69, No. 5 (2020)
A calibrated sensitivity analysis for matched observational studies with
application to the effect of second‐hand smoke exposure on blood lead
levels in children
- Authors: Bo Zhang; Dylan S. Small
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1285-1305, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12443
  Issue No: Vol. 69, No. 5 (2020)
On the interplay between exposure misclassification and informative
cluster size
- Authors: Glen McGee; Marianthi‐Anna Kioumourtzoglou, Marc G. Weisskopf, Sebastien Haneuse, Brent A. Coull
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1209-1226, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12430
  Issue No: Vol. 69, No. 5 (2020)
Burglary in London: insights from statistical heterogeneous spatial point
processes
- Authors: Jan Povala; Seppo Virtanen, Mark Girolami
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1067-1090, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12431
  Issue No: Vol. 69, No. 5 (2020)
Cluster analysis of microbiome data by using mixtures of
Dirichlet–multinomial regression models
- Authors: Sanjeena Subedi; Drew Neish, Stephen Bak, Zeny Feng
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1163-1187, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12432
  Issue No: Vol. 69, No. 5 (2020)
Landmark proportional subdistribution hazards models for dynamic
prediction of cumulative incidence functions
- Authors: Qing Liu; Gong Tang, Joseph P. Costantino, Chung‐Chou H. Chang
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1145-1162, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12433
  Issue No: Vol. 69, No. 5 (2020)
A hierarchical mixed effect hurdle model for spatiotemporal count data and
its application to identifying factors impacting health professional
shortages
- Authors: Soutik Ghosal; Timothy S. Lau, Jeremy Gaskins, Maiying Kong
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1121-1144, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12434
  Issue No: Vol. 69, No. 5 (2020)
A Bayesian quest for finding a unified model for predicting volleyball
games
- Authors: Leonardo Egidi; Ioannis Ntzoufras
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1307-1336, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12436
  Issue No: Vol. 69, No. 5 (2020)
One‐class classification with application to forensic analysis
- Authors: Francesca Fortunato; Laura Anderlucci, Angela Montanari
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1227-1249, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12438
  Issue No: Vol. 69, No. 5 (2020)
Adding measurement error to location data to protect subject
confidentiality while allowing for consistent estimation of exposure
effects
- Authors: Mahesh Karra; David Canning, Ryoko Sato
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1251-1268, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12439
  Issue No: Vol. 69, No. 5 (2020)
Index of authors, volume 69, 2020
- Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1375-1380, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12444
  Issue No: Vol. 69, No. 5 (2020)
Issue Information
- Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1013-1014, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12362
  Issue No: Vol. 69, No. 5 (2020)
Contents of volume 69, 2020
- Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 69, Issue 5, Page 1381-1383, November 2020.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-10-07T07:09:19-07:00
  DOI: 10.1111/rssc.12445
  Issue No: Vol. 69, No. 5 (2020)
Future proofing a building design using history matching inspired
level‐set techniques
- Authors: Evan Baker; Peter Challenor, Matt Eames
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-12-19T06:21:20-08:00
  DOI: 10.1111/rssc.12461
Robust estimation for small domains in business surveys
- Authors: Paul A. Smith; Chiara Bocci, Nikos Tzavidis, Sabine Krieg, Marc J. E. Smeets
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-12-11T03:12:49-08:00
  DOI: 10.1111/rssc.12460
Finite mixtures of semiparametric Bayesian survival kernel machine
regressions: Application to breast cancer gene pathway subgroup analysis
- Authors: Lin Zhang; Inyoung Kim
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-12-01T07:21:00-08:00
  DOI: 10.1111/rssc.12457
Threshold‐based subgroup testing in logistic regression models in
two‐phase sampling designs
- Authors: Ying Huang; Juhee Cho, Youyi Fong
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-28T07:10:40-08:00
  DOI: 10.1111/rssc.12459
A Bayesian approach for determining player abilities in football
- Authors: Gavin A. Whitaker; Ricardo Silva, Daniel Edwards, Ioannis Kosmidis
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-25T12:00:00-08:00
  DOI: 10.1111/rssc.12454
M‐quantile regression for multivariate longitudinal data with an
application to the Millennium Cohort Study
- Authors: Marco Alfò; Maria Francesca Marino, Maria Giovanna Ranalli, Nicola Salvati, Nikos Tzavidis
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-25T01:41:58-08:00
  DOI: 10.1111/rssc.12452
Sequential aggregation of probabilistic forecasts—Application to
wind speed ensemble forecasts
- Authors: Michaël Zamo; Liliane Bel, Olivier Mestre
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-22T11:01:55-08:00
  DOI: 10.1111/rssc.12455
Quantile‐frequency analysis and spectral measures for diagnostic checks
of time series with nonlinear dynamics
- Authors: Ta‐Hsin Li
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-22T07:21:05-08:00
  DOI: 10.1111/rssc.12458
Stacked inverse probability of censoring weighted bagging: A case study in
the InfCareHIV Register
- Authors: Pablo Gonzalez Ginestet; Ales Kotalik, David M. Vock, Julian Wolfson, Erin E. Gabriel
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-22T06:47:26-08:00
  DOI: 10.1111/rssc.12448
Quantifying the trendiness of trends
- Authors: Andreas Kryger Jensen; Claus Thorn Ekstrøm
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-20T07:36:37-08:00
  DOI: 10.1111/rssc.12451
Bayesian varying coefficient model with selection: An application to
functional mapping
- Authors: Benjamin Heuclin; Frédéric Mortier, Catherine Trottier, Marie Denis
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-20T02:44:30-08:00
  DOI: 10.1111/rssc.12447
Correcting misclassification errors in crowdsourced ecological data: A
Bayesian perspective
- Authors: Edgar Santos‐Fernandez; Erin E. Peterson, Julie Vercelloni, Em Rushworth, Kerrie Mengersen
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-11T11:03:48-08:00
  DOI: 10.1111/rssc.12453
A non‐parametric Hawkes process model of primary and secondary accidents
on a UK smart motorway
- Authors: Kieran Kalair; Colm Connaughton, Pierfrancesco Alaimo Di Loro
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-11T02:03:31-08:00
  DOI: 10.1111/rssc.12450
Modelling time‐varying mobility flows using function‐on‐function
regression: Analysis of a bike sharing system in the city of Milan
- Authors: Agostino Torti; Alessia Pini, Simone Vantini
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-08T07:26:15-08:00
  DOI: 10.1111/rssc.12456
Random effects dynamic panel models for unequally spaced multivariate
categorical repeated measures: an application to child–parent exchanges
of support
- Authors: Fiona Steele; Emily Grundy
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-07T05:42:44-08:00
  DOI: 10.1111/rssc.12446
Functional ensemble survival tree: Dynamic prediction of Alzheimer’s
disease progression accommodating multiple time‐varying covariates
- Authors: Shu Jiang; Yijun Xie, Graham A. Colditz
  Abstract: Journal of the Royal Statistical Society: Series C (Applied Statistics), EarlyView.
  Citation: Journal of the Royal Statistical Society: Series C (Applied Statistics)
  PubDate: 2020-11-07T05:40:44-08:00
  DOI: 10.1111/rssc.12449