Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Factor Analytic Evidence for the Construct Validity of Scores: A Historical Overview and Some Guidelines
1996746 citationsBruce Thompson, Larry G. Danielprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Larry G. Daniel
Since
Specialization
Citations
This map shows the geographic impact of Larry G. Daniel'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 Larry G. Daniel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Larry G. Daniel more than expected).
This network shows the impact of papers produced by Larry G. Daniel. 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 Larry G. Daniel. The network helps show where Larry G. Daniel may publish in the future.
Co-authorship network of co-authors of Larry G. Daniel
This figure shows the co-authorship network connecting the top 25 collaborators of Larry G. Daniel.
A scholar is included among the top collaborators of Larry G. Daniel 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 Larry G. Daniel. Larry G. Daniel 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.
Daniel, Larry G.. (2020). Kerlinger's Research Myths. Practical assessment, research & evaluation. 5(1). 4.
2.
Daniel, Larry G., et al.. (2019). Student Engagement and Achievement: A Comparison of STEM Schools, STEM Programs, and Non-STEM Settings.. Research in the schools. 26(1). 1–11.1 indexed citations
3.
Williams, Lunetta M., et al.. (2010). An Afterschool Program for Economically Disadvantaged Youth: Perceptions of Parents, Staff, and Students.. Research in the schools. 17(1). 12–28.9 indexed citations
4.
Onwuegbuzie, Anthony J. & Larry G. Daniel. (2003). Typology of analytical and interpretational errors in quantitative and qualitative educational research. SHILAP Revista de lepidopterología.146 indexed citations
5.
Daniel, Larry G., et al.. (2001). Basic Cross-Validation: Using the "Holdout" Method To Assess the Generalizability of Results.. Research in the schools. 8(1). 83–89.4 indexed citations
6.
Onwuegbuzie, Anthony J. & Larry G. Daniel. (1999). Uses and misuses of the correlation coefficient.. Research in the schools.103 indexed citations
7.
Daniel, Larry G., et al.. (1999). Theoretical Perspectives of Instructional Supervision in Contemporary Textbooks: A Content Analysis.. Research in the schools. 6(1). 25–31.1 indexed citations
8.
Daniel, Larry G.. (1998). Statistical Significance Testing: A Historical Overview of Misuse and Misinterpretation with Implications for the Editorial Policies of Educational Journals. Research in the schools. 5(2). 23–32.69 indexed citations
9.
Daniel, Larry G.. (1998). The Statistical Significance Controversy Is Definitely Not Over: A Rejoinder to Responses by Thompson, Knapp, and Levin.. Research in the schools. 5(2). 63–65.6 indexed citations
Thompson, Bruce & Larry G. Daniel. (1991). Canonical Correlation Analysis that Incorporates Measurement and Sampling Error Considerations.. 39(5). 387–91.1 indexed citations
Daniel, Larry G., et al.. (1977). Teaching caseload management.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 25(1). 27–9.6 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.