The British Journal of Mathematical and Statistical Psychology
Overview
The British Journal of Mathematical and Statistical Psychology is a scholarly journal that focuses on the application of mathematical and statistical methods in the field of psychology. It publishes research articles and reviews that explore the use of quantitative techniques to analyze psychological data, model psychological processes, and advance statistical methodologies in psychological research. The journal aims to foster interdisciplinary collaboration and promote the integration of mathematical and statistical approaches in psychological science.
Details
Details
Abbr.
Br J Math Stat Psychol
Start
1965
End
Continuing
Frequency
Three no. a year, 2009-
p-ISSN
0007-1102
e-ISSN
2044-8317
Country
United Kingdom
Language
English
Specialty
Psychology
Metrics
Metrics
h-index / Ranks: 6131
60
SJR / Ranks: 1520
1735
CiteScore / Ranks: 5670
4.60
JIF / Ranks: 4138
2.6
Recent Articles
1.
Bjermo J, Fackle-Fornius E, Miller F
Br J Math Stat Psychol
. 2025 Mar;
PMID: 40065545
Before items can be implemented in a test, the item characteristics need to be calibrated through pretesting. To achieve high-quality tests, it's crucial to maximize the precision of estimates obtained...
2.
Brusco M, Steinley D, Watts A
Br J Math Stat Psychol
. 2025 Feb;
PMID: 40012163
Integer programming (IP) is an extension of linear programming (LP) whereby the goal is to determine values for a set of decision variables (some or all of which have integer...
3.
Liu Z, Wang S, Xiao H, Zhang S, Qiu T
Br J Math Stat Psychol
. 2025 Feb;
PMID: 39985192
Understanding students' learning trajectories is crucial for educators to effectively monitor and enhance progress. With the rise of computer-based testing, researchers now have access to rich datasets that provide deeper...
4.
Liu F, Chen M, Wang X, Hancock R
Br J Math Stat Psychol
. 2025 Feb;
PMID: 39981572
Nowadays, multidimensional data are often available from educational testing. One natural issue is to identify whether more dimensional data are useful in fitting the item response data. To address this...
5.
6.
Jointly modeling responses and omitted items by a competing risk model: A survival analysis approach
Guo J, Xu X, Fang G, Ying Z, Zhang S
Br J Math Stat Psychol
. 2025 Jan;
PMID: 39888000
Item response theory models are commonly adopted in educational assessment and psychological measurement. Such models need to be modified to accommodate practical situations when statistical sampling assumptions are violated. Omission...
7.
Rahman A, Jiang D, Lix L
Br J Math Stat Psychol
. 2025 Jan;
PMID: 39838811
Recent technological advancements have enabled the collection of intensive longitudinal data (ILD), consisting of repeated measurements from the same individual. The threshold autoregressive (TAR) model is often used to capture...
8.
Frutos-Bernal E, Ceulemans E, Galindo-Villardon P, Wilderjans T
Br J Math Stat Psychol
. 2025 Jan;
PMID: 39812328
In various areas of science, researchers try to gain insight into important processes by jointly analysing different datasets containing information regarding common aspects of these processes. For example, to explain...
9.
Sinharay S, Monroe S
Br J Math Stat Psychol
. 2025 Jan;
PMID: 39760153
This paper provides a literature review of assessment of fit of item response theory models. Various types of fit procedures for item response theory models are reviewed, with a focus...
10.
Guastadisegni L, Cagnone S, Moustaki I, Vasdekis V
Br J Math Stat Psychol
. 2024 Dec;
PMID: 39723492
This paper introduces the generalized Hausman test as a novel method for detecting the non-normality of the latent variable distribution of the unidimensional latent trait model for binary data. The...