Lifetime Data Analysis

805 papers and 13.6k indexed citations i.

About

The 805 papers published in Lifetime Data Analysis in the last decades have received a total of 13.6k indexed citations. Papers published in Lifetime Data Analysis usually cover Statistics and Probability (697 papers), Artificial Intelligence (131 papers) and Economics and Econometrics (100 papers) specifically the topics of Statistical Methods and Inference (563 papers), Statistical Methods and Bayesian Inference (389 papers) and Statistical Distribution Estimation and Applications (205 papers). The most active scholars publishing in Lifetime Data Analysis are Philip Hougaard, G. À. Whitmore, W. J. Padgett, Jerry Lawless, Martin Crowder, Daniel Commenges, Per Kragh Andersen, Ørnulf Borgan, Jianwen Cai and Fred Schenkelberg.

In The Last Decade

Fields of papers published in Lifetime Data Analysis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Lifetime Data Analysis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Lifetime Data Analysis.

Countries where authors publish in Lifetime Data Analysis

Since Specialization
Citations

This map shows the geographic impact of research published in Lifetime Data Analysis. 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 papers published in Lifetime Data Analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lifetime Data Analysis more than expected).

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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