Hong Jiao

1.3k citations
48 papers · 850 indexed · h-index 16
Topics
Psychometric Methodologies and Testing (32 papers)Advanced Statistical Modeling Techniques (20 papers)Statistical Methods and Bayesian Inference (10 papers)

In The Last Decade

Hong Jiao

45 papers receiving 773 citations

Peers

Hong Jiao
Comparison fields: 5 of 93
  • Management Science and Operations Research 327
  • Education 231
  • Artificial Intelligence 184
  • Statistics and Probability 159
  • Developmental and Educational Psychology 150
Replace G. Gage Kingsbury with:
G. Gage Kingsbury United States
Yanyan Sheng United States
Xiaojing Kong United States
Isaac I. Bejar United States
Yi‐Hsuan Lee United States
Theo J. H. M. Eggen Netherlands
Njål Foldnes Norway
Linda S. Steinberg United States
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Hong Jiao relative to G. Gage Kingsbury United States G. Gage Kingsbury's profile →
Citations per field
00.5×2.7×
G. Gage Kingsbury · 1×
Citations per year

Countries citing papers authored by Hong Jiao

Since Specialization
Citations

This map shows the geographic impact of Hong Jiao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hong Jiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong Jiao more than expected).

Fields of papers citing papers by Hong Jiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hong Jiao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hong Jiao. The network helps show where Hong Jiao may publish in the future.

Co-authorship network of co-authors of Hong Jiao

This figure shows the co-authorship network connecting the top 25 collaborators of Hong Jiao. A scholar is included among the top collaborators of Hong Jiao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hong Jiao. Hong Jiao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 5
3 5
4 1
5 3
6 29
7 48
8 12
9 4
10 75
11 9
12
A Family of Rater Accuracy Models.
17
13 19
14 4
15 8
16
Applying Multidimensional Item Response Theory Models in Validating Test Dimensionality: An Example of K-12 Large-Scale Science Assessment.
10
17
Exploring levels of performance using the mixture Rasch model for standard setting 1
13
18 6
19 13
20
Modeling local item dependence with the hierarchical generalized linear model.
21

About Hong Jiao

Hong Jiao is a scholar working on Management Science and Operations Research, Statistics and Probability and Computer Networks and Communications, having authored 48 papers that have together received 850 indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (32 papers), Advanced Statistical Modeling Techniques (20 papers) and Statistical Methods and Bayesian Inference (10 papers). The work is most often cited by research in Management Science and Operations Research (327 citations), Statistics and Probability (159 citations) and Computer Science Applications (99 citations). Hong Jiao has collaborated with scholars based in United States, China and Nigeria. Frequent co-authors include Peida Zhan, John A. Olson, Shudong Wang, Thomas Brooks, Michael J. Young, Shudong Wang, Edward W. Wolfe, Akihito Kamata, Feiming Li and Robert W. Lissitz. Their work appears in journals such as Frontiers in Psychology, Psychological Methods and Psychometrika.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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