Using the bootstrapping method to verify whether hospital physicians have different h-indexes regarding individual research achievement

Kung, Sheng-Chun; Chien, Tsair‐Wei; Yeh, Yu-Tsen; Lin, Jui-Chung John; Chou, Willy

doi:10.1097/md.0000000000021552

Cited by 18 publications

(28 citation statements)

References 15 publications

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“…Finally, although the time-to-event analysis was applied to compare the difference in IP among continents due to censored data in existence, whether another statistical method can be used to compare their IPs is worthy of discussion. For instance, the bootstrapping method [ 62 ] can be used to examine their 95% CIs among continents and shown on a dashboard [ 63 ] if censored data are ignored.…”

Section: Discussionmentioning

confidence: 99%

An online time-to-event dashboard comparing the effective control of COVID-19 among continents using the inflection point on an ogive curve

Lee¹,

Chien

Yeh

et al. 2021

Medicine

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Background: During the COVID-19 pandemic, one of the frequently asked questions is which countries (or continents) are severely hit. Aside from using the number of confirmed cases and the fatality to measure the impact caused by COVID-19, few adopted the inflection point (IP) to represent the control capability of COVID-19. How to determine the IP days related to the capability is still unclear. This study aims to (i) build a predictive model based on item response theory (IRT) to determine the IP for countries, and (ii) compare which countries (or continents) are hit most. Methods: We downloaded COVID-19 outbreak data of the number of confirmed cases in all countries as of October 19, 2020. The IRT-based predictive model was built to determine the pandemic IP for each country. A model building scheme was demonstrated to fit the number of cumulative infected cases. Model parameters were estimated using the Solver add-in tool in Microsoft Excel. The absolute advantage coefficient (AAC) was computed to track the IP at the minimum of incremental points on a given ogive curve. The time-to-event analysis (a.k.a. survival analysis) was performed to compare the difference in IPs among continents using the area under the curve (AUC) and the respective 95% confidence intervals (CIs). An online comparative dashboard was created on Google Maps to present the epidemic prediction for each country. Results: The top 3 countries that were hit severely by COVID-19 were France, Malaysia, and Nepal, with IP days at 263, 262, and 262, respectively. The top 3 continents that were hit most based on IP days were Europe, South America, and North America, with their AUCs and 95% CIs at 0.73 (0.61–0.86), 0.58 (0.31–0.84), and 0.54 (0.44–0.64), respectively. An online time–event result was demonstrated and shown on Google Maps, comparing the IP probabilities across continents. Conclusion: An IRT modeling scheme fitting the epidemic data was used to predict the length of IP days. Europe, particularly France, was hit seriously by COVID-19 based on the IP days. The IRT model incorporated with AAC is recommended to determine the pandemic IP.

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Section: Discussionmentioning

confidence: 99%

An online time-to-event dashboard comparing the effective control of COVID-19 among continents using the inflection point on an ogive curve

Lee¹,

Chien

Yeh

et al. 2021

Medicine

Self Cite

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“…The Web of Science database is the largest and one of the most reliable databases for publications and citations, providing quantitative (number of studies) as well as qualitative data, including impact (h-index). [ 26 ]…”

Section: Discussionmentioning

confidence: 99%

Aristolochic acid nephropathy

Zhang

et al. 2021

Medicine

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“…The bootstrapping method [ 19 , 20 ] was used to examine differences in metrics among author clusters. A total of 1000 median metrics were retrieved from the random samples of 100 repetitions on mean values for each metric and cluster.…”

Section: Methodsmentioning

confidence: 99%

Suitability of h- and x-indices for evaluating authors’ individual research achievements in a given short period of years

et al. 2021

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Background: The h-index of a researcher refers to the maximum number h of his/her publications that has at least h citations via the concept of the square area. The x-index is determined by the maximum area of a rectangle under the curve to interpret authors’ individual research achievements (IRAs). However, the properties of both metrics have not been compared and discussed before. This study aimed to investigate whether both metrics of h- and x-index are suitable for evaluating IRAs in a short period of years. Methods: By searching the PubMed database (Pubmed.com), we used the keyword “ PLoS One ” (journal) and downloaded 50,000 articles published in 2015 and 2016. A total of 146,346 citations were listed in PubMed Central and 27,035 authors(with h-index ≥1) were divided into 3 parts. Correlation coefficients among metrics (ie, AIF, h, g, Ag, and x-index) were examined. The bootstrapping method used for estimating 95% confidence intervals was applied to compare differences in metrics among author groups. The most cited authors and topic burst were visualized by social network analysis. The most prominent countries/areas were highlighted by the x-index and displayed via choropleth maps. Results: Results demonstrated that, first, the h-index had the least relation to other metrics and failed to differentiate authors’ IRAs among groups, particularly in a short time period. Second, the top 3 highest x-index for countries were the United States, China, and the UK but with the productivity-oriented feature. Third, the most cited medical subject headings (ie, MeSH terms) were genome, metabolome, and microbiology, and the most cited author was Lori Newman (whose x-index = 13.52, and h = 2) from Switzerland with the article (PMID = 26646541) cited 291 times. The need for the x-index combined with a visual map for displaying authors’ IRAs was verified and recommended. Conclusions: We verified that the h-index failed to differentiate authors’ IRAs among author groups in a short time period. The x-index combined with the Kano map is recommended in research for a better understanding of the authors’ IRAs in other journals or disciplines, not just limited to the journal of PloS One as we did in this study.

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Using the bootstrapping method to verify whether hospital physicians have different h-indexes regarding individual research achievement

Abstract: Supplemental Digital Content is available in the text

Cited by 18 publications

References 15 publications

An online time-to-event dashboard comparing the effective control of COVID-19 among continents using the inflection point on an ogive curve

An online time-to-event dashboard comparing the effective control of COVID-19 among continents using the inflection point on an ogive curve

Aristolochic acid nephropathy

Suitability of h- and x-indices for evaluating authors’ individual research achievements in a given short period of years

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