Dewi Rahardja

418 total citations
44 papers, 258 citations indexed

About

Dewi Rahardja is a scholar working on Statistics and Probability, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Dewi Rahardja has authored 44 papers receiving a total of 258 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Statistics and Probability, 8 papers in Management Science and Operations Research and 7 papers in Artificial Intelligence. Recurrent topics in Dewi Rahardja's work include Statistical Methods and Bayesian Inference (22 papers), Statistical Methods in Clinical Trials (16 papers) and Advanced Statistical Methods and Models (11 papers). Dewi Rahardja is often cited by papers focused on Statistical Methods and Bayesian Inference (22 papers), Statistical Methods in Clinical Trials (16 papers) and Advanced Statistical Methods and Models (11 papers). Dewi Rahardja collaborates with scholars based in United States and China. Dewi Rahardja's co-authors include Yan D. Zhao, Yongming Qu, Yan Peng, Venetia Sarode, Zhiwei Zhang, Ying Yang, Ying Yang, Yisheng Fang, David Euhus and Jingsheng Yan and has published in prestigious journals such as SHILAP Revista de lepidopterología, British Journal of Cancer and Statistics in Medicine.

In The Last Decade

Dewi Rahardja

33 papers receiving 245 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dewi Rahardja United States 8 75 64 62 31 20 44 258
Grace Hsu Canada 7 64 0.9× 70 1.1× 78 1.3× 21 0.7× 7 0.3× 13 277
Ryan Copping United States 7 63 0.8× 104 1.6× 43 0.7× 14 0.5× 5 0.3× 9 355
Pei‐Fang Su Taiwan 11 55 0.7× 40 0.6× 126 2.0× 17 0.5× 12 0.6× 60 435
Anna McGlothlin United States 9 179 2.4× 92 1.4× 189 3.0× 64 2.1× 17 0.8× 16 504
Marisa Papaluca‐Amati Netherlands 10 30 0.4× 87 1.4× 39 0.6× 24 0.8× 14 0.7× 11 395
Cong Chen United States 11 68 0.9× 174 2.7× 59 1.0× 17 0.5× 78 3.9× 37 353
André Happe France 14 32 0.4× 15 0.2× 44 0.7× 19 0.6× 15 0.8× 34 516
Xiaoyang Ruan United States 11 62 0.8× 19 0.3× 111 1.8× 29 0.9× 10 0.5× 20 399
Kaushik Ghosh United States 10 13 0.2× 123 1.9× 108 1.7× 12 0.4× 11 0.6× 27 376
Samuel Whipple United States 5 53 0.7× 100 1.6× 56 0.9× 10 0.3× 2 0.1× 9 312

Countries citing papers authored by Dewi Rahardja

Since Specialization
Citations

This map shows the geographic impact of Dewi Rahardja'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 Dewi Rahardja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dewi Rahardja more than expected).

Fields of papers citing papers by Dewi Rahardja

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dewi Rahardja. 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 Dewi Rahardja. The network helps show where Dewi Rahardja may publish in the future.

Co-authorship network of co-authors of Dewi Rahardja

This figure shows the co-authorship network connecting the top 25 collaborators of Dewi Rahardja. A scholar is included among the top collaborators of Dewi Rahardja 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 Dewi Rahardja. Dewi Rahardja 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
1.
2.
Rahardja, Dewi. (2023). A Review of the Five Sorrowful Mysteries of the Rosary Based on the Biblical Backgrounds. International Journal of Humanities and Social Science. 10(1). 53–62.
3.
Rahardja, Dewi. (2023). Computational statistics for time-series forecasts via SAS/ETS 9.4 drop-down menu. Journal of Statistics and Management Systems. 26(4). 787–800.
4.
Rahardja, Dewi & Dean M. Young. (2021). Confidence Intervals for the Risk Ratio Using Double Sampling with Misclassified Binomial Data. Journal of Data Science. 9(4). 529–548. 1 indexed citations
5.
Rahardja, Dewi, Yan D. Zhao, & Hongmei Zhang. (2021). Bayesian Credible Sets for a Binomial Proportion Based on One-Sample Binary Data Subject to One Type of Misclassification. Journal of Data Science. 10(1). 51–59.
6.
Rahardja, Dewi. (2021). A Review of the Catholic Theology on the Eucharistic Transubstantiation and the Real Presence Doctrines – Why They Matter. International Journal of Humanities and Social Science. 8(4). 70–82. 3 indexed citations
7.
Rahardja, Dewi. (2020). Multiple Comparison Procedures for the Differences of Proportion Parameters in Over-Reported Multiple-Sample Binomial Data. SHILAP Revista de lepidopterología. 3(1). 56–67. 1 indexed citations
8.
Rahardja, Dewi. (2017). A review of the multiple-sample tests for the continuous-data type. Journal of Modern Applied Statistical Methods. 16(1). 127–136. 5 indexed citations
9.
Rahardja, Dewi, Ying Yang, & Zhiwei Zhang. (2016). A Comprehensive Review of the Two-Sample Independent or Paired Binary Data, with or without Stratum Effects. Journal of Modern Applied Statistical Methods. 15(2). 215–223. 11 indexed citations
10.
Rahardja, Dewi. (2014). Comparison of Individual and Moving Range Chart Combinations to Individual Charts in Terms of ARL after Designing for a Common “All OK” ARL. Journal of Modern Applied Statistical Methods. 13(2). 364–378. 1 indexed citations
11.
12.
Rahardja, Dewi, et al.. (2012). Tumour biomarker expression relative to age and molecular subtypes of invasive breast cancer. British Journal of Cancer. 107(2). 382–387. 77 indexed citations
13.
Rahardja, Dewi & Yan D. Zhao. (2012). Bayesian inference of a binomial proportion using one-sample misclassified binary data. Model Assisted Statistics and Applications. 7(1). 17–22. 2 indexed citations
14.
Zhang, Hongmei, Yan D. Zhao, Dewi Rahardja, et al.. (2011). Adjusting wheal size measures to correct atopy misclassification. International Journal of General Medicine. 4. 597–597. 6 indexed citations
15.
Zhao, Yan D. & Dewi Rahardja. (2011). Nonlinear structural equation modeling with distribution-free method. Model Assisted Statistics and Applications. 6(1). 39–46.
16.
Rahardja, Dewi, Yan D. Zhao, & Hao Helen Zhang. (2010). Bayesian Inference of Odds Ratios in Misclassified Binary Data with a Validation Substudy. Communications in Statistics - Simulation and Computation. 39(10). 1845–1854. 1 indexed citations
17.
Rahardja, Dewi & Yan D. Zhao. (2010). Likelihood-based confidence intervals for the risk difference of two-sample binary data with a fallible classifier and a gold standard. Statistical Methodology. 8(2). 204–212. 2 indexed citations
18.
Rahardja, Dewi, Yan D. Zhao, & Yongming Qu. (2009). Sample Size Determinations for the Wilcoxon–Mann–Whitney Test: A Comprehensive Review. Statistics in Biopharmaceutical Research. 1(3). 317–322. 11 indexed citations
19.
Zhao, Yan D., Dewi Rahardja, & Yajun Mei. (2008). Sample Size Calculation for the van Elteren Test Adjusting for Ties. Journal of Biopharmaceutical Statistics. 18(6). 1112–1119. 1 indexed citations
20.
Zhao, Yan D., Dewi Rahardja, & Yongming Qu. (2007). Sample size calculation for the Wilcoxon–Mann–Whitney test adjusting for ties. Statistics in Medicine. 27(3). 462–468. 47 indexed citations

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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