Daniel L. Murphy

427 total citations
19 papers, 326 citations indexed

About

Daniel L. Murphy is a scholar working on Computer Networks and Communications, Hardware and Architecture and Education. According to data from OpenAlex, Daniel L. Murphy has authored 19 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Networks and Communications, 5 papers in Hardware and Architecture and 5 papers in Education. Recurrent topics in Daniel L. Murphy's work include Parallel Computing and Optimization Techniques (5 papers), Distributed and Parallel Computing Systems (4 papers) and Psychometric Methodologies and Testing (4 papers). Daniel L. Murphy is often cited by papers focused on Parallel Computing and Optimization Techniques (5 papers), Distributed and Parallel Computing Systems (4 papers) and Psychometric Methodologies and Testing (4 papers). Daniel L. Murphy collaborates with scholars based in United States and United Kingdom. Daniel L. Murphy's co-authors include Daniel G. Bobrow, Raymond S. Tomlinson, Jerry D. Burchfiel, Keenan A. Pituch, Richard L. Tate, S. Natasha Beretvas, Barbara G. Dodd, Y. T. Chiu, Yam T. Chiu and Matthew Gaertner and has published in prestigious journals such as Geophysical Research Letters, Communications of the ACM and Structural Equation Modeling A Multidisciplinary Journal.

In The Last Decade

Daniel L. Murphy

17 papers receiving 271 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel L. Murphy United States 9 161 97 79 32 29 19 326
Carolyn Jane Anderson United States 8 268 1.7× 77 0.8× 131 1.7× 65 2.0× 32 1.1× 26 478
Len Swanson United States 7 128 0.8× 24 0.2× 62 0.8× 108 3.4× 243 8.4× 14 378
Steffen Lindner Germany 8 205 1.3× 37 0.4× 24 0.3× 31 1.0× 5 0.2× 17 359
David Mutchler United States 10 331 2.1× 50 0.5× 58 0.7× 114 3.6× 21 0.7× 29 523
Robert Stephens United Kingdom 4 121 0.8× 105 1.1× 42 0.5× 30 0.9× 6 0.2× 11 239
Keith Irwin United States 11 126 0.8× 74 0.8× 185 2.3× 124 3.9× 10 0.3× 31 459
Malolan Chetlur United States 11 125 0.8× 31 0.3× 33 0.4× 30 0.9× 72 2.5× 36 272
Christopher Walton United Kingdom 9 64 0.4× 15 0.2× 130 1.6× 109 3.4× 11 0.4× 15 249
Janice E. Cuny United States 10 232 1.4× 192 2.0× 37 0.5× 78 2.4× 13 0.4× 38 396
Jiahe Qian United States 7 73 0.5× 6 0.1× 20 0.3× 34 1.1× 132 4.6× 26 197

Countries citing papers authored by Daniel L. Murphy

Since Specialization
Citations

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

Fields of papers citing papers by Daniel L. Murphy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel L. Murphy. 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 Daniel L. Murphy. The network helps show where Daniel L. Murphy may publish in the future.

Co-authorship network of co-authors of Daniel L. Murphy

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel L. Murphy. A scholar is included among the top collaborators of Daniel L. Murphy 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 Daniel L. Murphy. Daniel L. Murphy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Murphy, Daniel L., et al.. (2016). Feedback on reflection: comparing rating-scale and forced-choice formats for measuring and facilitating teacher team reflective practice. Reflective Practice. 17(3). 317–333. 8 indexed citations
2.
Murphy, Daniel L. & S. Natasha Beretvas. (2015). A Comparison of Teacher Effectiveness Measures Calculated Using Three Multilevel Models for Raters Effects. Applied Measurement in Education. 28(3). 219–236. 5 indexed citations
3.
Murphy, Daniel L. & Matthew Gaertner. (2014). Evaluating the Predictive Value of Growth Prediction Models. Educational Measurement Issues and Practice. 33(2). 5–13.
4.
Beretvas, S. Natasha & Daniel L. Murphy. (2013). An Evaluation of Information Criteria Use for Correct Cross-Classified Random Effects Model Selection. The Journal of Experimental Education. 81(4). 429–463. 6 indexed citations
5.
Murphy, Daniel L., et al.. (2012). Value-Added Models in the Evaluation of Teacher Effectiveness: A Comparison of Models and Outcomes. Research Report.. 3 indexed citations
6.
McClarty, Katie Larsen, et al.. (2012). Putting Ducks in a Row: Methods for Empirical Alignment of Performance Standards.
7.
Murphy, Daniel L., S. Natasha Beretvas, & Keenan A. Pituch. (2011). The Effects of Autocorrelation on the Curve-of-Factors Growth Model. Structural Equation Modeling A Multidisciplinary Journal. 18(3). 430–448. 13 indexed citations
8.
Murphy, Daniel L., et al.. (2010). A Comparison of Item Selection Techniques for Testlets. Applied Psychological Measurement. 34(6). 424–437. 9 indexed citations
9.
Murphy, Daniel L. & Keenan A. Pituch. (2009). The Performance of Multilevel Growth Curve Models Under an Autoregressive Moving Average Process. The Journal of Experimental Education. 77(3). 255–284. 18 indexed citations
10.
Pituch, Keenan A., Daniel L. Murphy, & Richard L. Tate. (2009). Three-Level Models for Indirect Effects in School- and Class-Randomized Experiments in Education. The Journal of Experimental Education. 78(1). 60–95. 40 indexed citations
11.
Murphy, Daniel L. & Yam T. Chiu. (1993). <title>Geophysical effects upon magnetospheric images</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2008. 135–141. 1 indexed citations
12.
Murphy, Daniel L. & Y. T. Chiu. (1993). Effects of Doppler shifts and source perspectives on extreme ultraviolet images of ion populations moving in the inner magnetosphere. Geophysical Research Letters. 20(19). 2027–2030. 1 indexed citations
13.
Murphy, Daniel L.. (1993). Geophysical effects on magnetospheric images. Optical Engineering. 32(12). 3147–3147. 1 indexed citations
14.
Murphy, Daniel L., et al.. (1993). <title>Lidar detection of levitated lunar dust</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1936. 182–190. 1 indexed citations
15.
Bobrow, Daniel G., Jerry D. Burchfiel, Daniel L. Murphy, & Raymond S. Tomlinson. (1972). TENEX, a paged time sharing system for the PDP - 10. Communications of the ACM. 15(3). 135–143. 131 indexed citations
16.
Murphy, Daniel L.. (1972). Storage organization and management in TENEX. 23–23. 12 indexed citations
17.
Bobrow, Daniel G., Jerry D. Burchfiel, Daniel L. Murphy, & Raymond S. Tomlinson. (1971). TENEX, a paged time sharing system for the PDP-10. 1–1. 13 indexed citations
18.
Bobrow, Daniel G. & Daniel L. Murphy. (1968). A note on the efficiency of a LISP computation in a paged machine. Communications of the ACM. 11(8). 558–558. 10 indexed citations
19.
Bobrow, Daniel G. & Daniel L. Murphy. (1967). Structure of a LISP system using two-level storage. Communications of the ACM. 10(3). 155–159. 54 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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