Scandinavian Journal of Statistics, Theory and Applications
Overview
The Scandinavian Journal of Statistics, Theory and Applications is a reputable academic journal that focuses on the field of statistics. It publishes high-quality research papers, theoretical advancements, and practical applications in statistics, with a particular emphasis on Scandinavian contributions. The journal serves as a platform for statisticians, researchers, and practitioners to exchange knowledge and explore innovative statistical methodologies and their applications across various disciplines.
Details
Details
Abbr.
Scand Stat Theory Appl
Start
1974
End
Continuing
Frequency
Quarterly
p-ISSN
0303-6898
e-ISSN
1467-9469
Country
United Kingdom
Language
English
Specialty
Public Health
Metrics
Metrics
h-index / Ranks: 5130
70
SJR / Ranks: 4544
892
CiteScore / Ranks: 11103
1.80
JIF / Ranks: 6819
1.0
Recent Articles
1.
Liu J, Zhang X, Lin T, Chen R, Zhong Y, Chen T, et al.
Scand Stat Theory Appl
. 2024 Aug;
51(2):672-696.
PMID: 39101047
This article proposes a distance-based framework incentivized by the paradigm shift towards feature aggregation for high-dimensional data, which does not rely on the sparse-feature assumption or the permutation-based inference. Focusing...
2.
Zhu W, Xu S, Liu C, Li Y
Scand Stat Theory Appl
. 2024 Jul;
50(1):266-295.
PMID: 39076352
We model the Alzheimer's Disease-related phenotype response variables observed on irregular time points in longitudinal Genome-Wide Association Studies as sparse functional data and propose nonparametric test procedures to detect functional...
3.
Duan R, Liang C, Shaw P, Tang C, Chen Y
Scand Stat Theory Appl
. 2024 Feb;
51(1):334-354.
PMID: 38370508
Practical problems with missing data are common, and many methods have been developed concerning the validity and/or efficiency of statistical procedures. On a central focus, there have been longstanding interests...
4.
Zaidi J, VanderWeele T
Scand Stat Theory Appl
. 2024 Feb;
48(3):881-907.
PMID: 38317823
The analysis of natural direct and principal stratum direct effects has a controversial history in statistics and causal inference as these effects are commonly identified with either untestable cross world...
5.
Li F, Kasza J, Turner E, Rathouz P, Forbes A, Preisser J
Scand Stat Theory Appl
. 2023 Aug;
50(3):1048-1067.
PMID: 37601275
Stepped wedge trials are increasingly adopted because practical constraints necessitate staggered roll-out. While a complete design requires clusters to collect data in all periods, resource and patient-centered considerations may call...
6.
Xia L, Nan B, Li Y
Scand Stat Theory Appl
. 2023 Jul;
50(2):550-571.
PMID: 37408772
For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions on the inverse of the Fisher information matrix. Such assumptions, however,...
7.
Qian J, Betensky R
Scand Stat Theory Appl
. 2023 May;
50(1):327-357.
PMID: 37179756
Truncation occurs in cohort studies with complex sampling schemes. When truncation is ignored or incorrectly assumed to be independent of the event time in the observable region, bias can result....
8.
Yang S, Zhang Y
Scand Stat Theory Appl
. 2023 Feb;
50(1):235-265.
PMID: 36844478
Propensity score matching has been a long-standing tradition for handling confounding in causal inference, however requiring stringent model assumptions. In this article, we propose novel double score matching (DSM) utilizing...
9.
Cui Y, Wu R, Zheng Q
Scand Stat Theory Appl
. 2022 Oct;
48(4):1277-1313.
PMID: 36213620
We apply a three-step sequential procedure to estimate the change-point of count time series. Under certain regularity conditions, the estimator of change-point converges in distribution to the location of the...
10.
Garcia T, Ma Y
Scand Stat Theory Appl
. 2022 Oct;
43(1):156-171.
PMID: 36187208
Logistic models with a random intercept are prevalent in medical and social research where clustered and longitudinal data are often collected. Traditionally, the random intercept in these models is assumed...