The Canadian Journal of Statistics
Overview
The Canadian Journal of Statistics (Revue canadienne de statistique) is a reputable scholarly journal that publishes high-quality research articles in the field of statistics. It covers a wide range of topics including theoretical and applied statistics, probability, data analysis, and statistical methodology. The journal aims to promote the advancement of statistical knowledge and its applications in various disciplines, providing a platform for researchers and practitioners to share their innovative findings and insights.
Details
Details
Abbr.
Can J Stat
Start
1973
End
Continuing
Frequency
Quarterly, <1987->
p-ISSN
0319-5724
e-ISSN
1708-945X
Country
Canada
Languages
English
French
French
Metrics
Metrics
h-index / Ranks: 6577
56
SJR / Ranks: 8789
508
CiteScore / Ranks: 12692
1.10
JIF / Ranks: 7309
0.6
Recent Articles
1.
Ye S, Yu T, Caroff D, Huang S, Zhang B, Wang R
Can J Stat
. 2025 Mar;
53(1).
PMID: 40040799
In many biomedical applications, there is a need to build risk-adjustment models based on clustered data. However, methods for variable selection that are applicable to clustered discrete data settings with...
2.
Morrison S, Gatsonis C, Dahabreh I, Li B, Steingrimsson J
Can J Stat
. 2024 Dec;
52(4).
PMID: 39678170
We present methods for estimating loss-based measures of the performance of a prediction model in a target population that differs from the source population in which the model was developed,...
3.
Lotspeich S, Amorim G, Shaw P, Tao R, Shepherd B
Can J Stat
. 2024 Dec;
52(2):532-554.
PMID: 39629097
Observational databases provide unprecedented opportunities for secondary use in biomedical research. However, these data can be error-prone and must be validated before use. It is usually unrealistic to validate the...
4.
Gao P, Wakefield J
Can J Stat
. 2024 Oct;
52(2):337-358.
PMID: 39469316
In countries where population census data are limited, generating accurate subnational estimates of health and demographic indicators is challenging. Existing model-based geostatistical methods leverage covariate information and spatial smoothing to...
5.
Yu T, Ye S, Wang R
Can J Stat
. 2024 Sep;
52(3):900-923.
PMID: 39319323
When analyzing data combined from multiple sources (e.g., hospitals, studies), the heterogeneity across different sources must be accounted for. In this paper, we consider high-dimensional linear regression models for integrative...
6.
Urban K, Bong H, Orellana J, Kass R
Can J Stat
. 2024 Jul;
51(3):824-851.
PMID: 38974813
Multiple oscillating time series are typically analyzed in the frequency domain, where coherence is usually said to represent the magnitude of the correlation between two signals at a particular frequency....
7.
Best A, Wolfson D
Can J Stat
. 2024 Jun;
45(1):4-28.
PMID: 38845689
The determination of risk factors for disease incidence has been the subject of much epidemiologic research. With this goal a common study design entails the follow-up of an initially disease-free...
8.
Zhu H, Li Y, Liu B, Yao W, Zhang R
Can J Stat
. 2024 Jan;
50(1):267-286.
PMID: 38239624
In this article, we propose a novel estimator of extreme conditional quantiles in partial functional linear regression models with heavy-tailed distributions. The conventional quantile regression estimators are often unstable at...
9.
Han P, Taylor J, Mukherjee B
Can J Stat
. 2023 Jun;
51(2):355-374.
PMID: 37346757
Consider the setting where (i) individual-level data are collected to build a regression model for the association between an event of interest and certain covariates, and (ii) some risk calculators...
10.
Wang X, Liu B, Zhang X, Liu Y
Can J Stat
. 2023 Jun;
51(2):596-629.
PMID: 37346756
Change point detection for high-dimensional data is an important yet challenging problem for many applications. In this paper, we consider multiple change point detection in the context of high-dimensional generalized...