| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Psychology | 1159 | 8 | 12 | 4 |
The journal focuses on Statistics, Item response theory, Econometrics, Test (assessment) and Computerized adaptive testing. Differential item functioning, Psychometrics, Equating, Sample size determination and Polytomous Rasch model are among the areas of Statistics tackled. Most of the Psychometrics studies addressed also intersect with Test validity.
While Item response theory is the focus of the journal, it also provided insights into the studies of Data mining, Estimation theory, Item analysis, Rasch model and Artificial intelligence. Discussions in it are anchored in the subject of Artificial intelligence and the similar topic of Natural language processing. It features works in Econometrics, more specifically Nonparametric statistics, and explores their relation to disciplines like Statistical analysis.
Test (assessment) and Social psychology are closely related fields of research discussed in Applied Psychological Measurement. The concepts on Computerized adaptive testing presented in the journal can also apply to other research fields, including Machine learning and Item bank.
The journal papers cover a variety of subjects, including Statistics, Item response theory, Econometrics, Differential item functioning and Test (assessment). While work presented in the most cited publications provide substantial information on Item response theory, it also covers topics in Rasch model, Psychometrics, Equating and Item analysis. The published papers facilitate discussions in Nonparametric statistics as part of the larger field of Econometrics, however, they also tackle fields such as Statistical analysis.
The discussions in Applied Psychological Measurement mainly cover the fields of Item response theory, Statistics, Artificial intelligence, Computerized adaptive testing and Test (assessment). Item response theory research presented in the journal encompasses a variety of subjects, including Cognitive psychology, Sample size determination, Personality and Sensitivity (control systems). Some problems in Statistics that were presented in the journal overlapped with concepts under Function (mathematics) and True positive rate.
Artificial intelligence research featured in Applied Psychological Measurement incorporates concerns from various other topics such as Structure (mathematical logic), Machine learning, Test taker and Natural language processing. The studies in Computerized adaptive testing featured incorporate elements of Block (telecommunications), Cognition and Block design. The work on Test (assessment) tackled in it brings together disciplines like Statistical hypothesis testing and Theoretical computer science.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Applied Psychological Measurement (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Applied Psychological Measurement (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 15.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 27.50% of all publications and 32.50% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Despite the intriguing and groundbreaking research explored within this journal, it is essential to understand how these findings translate into real-world applications and opportunities. For instance, the skills and knowledge base explored in this journal can open the door for a variety of psychology-related careers, such as becoming a Board Certified Behavior Analyst (BCBA).
One particular area of interest is the field of behavior analysis. BCBAs use their knowledge of behavior principles to design and implement behavior intervention plans, conduct behavior analytical research, and consult with families, schools, and organizations to manage behavior challenges. They work in a variety of settings, including schools, hospitals, clinics, and even private homes.
Many of the principles outlined in the Applied Psychological Measurement journal could significantly enhance the effectiveness of BCBAs. For instance, the understanding of statistics, item response theory, and psychometrics could contribute to more effective design and implementation of intervention strategies. In addition, knowledge of artificial intelligence and machine learning could be useful in developing more efficient methods for data analysis or behavior prediction.
If you're interested in turning the knowledge gained from the Applied Psychological Measurement journal into a rewarding career, explore the steps on how to become a bcba in oregon online. This guide takes you through every step of the process, from the necessary qualifications to tips for passing the board certification exam.
Daniel M. Bolt;Nana Kim;James Wollack;Yiqin Pan
(2020)Seang-Hwane Joo;Philseok Lee;Stephen Stark
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