Automated Author ProfileLing, Jonathan
Ling, Jonathan
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 8.6 (sum of 14 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The attached data was used to assess the applicability of GLI 2012 spirometry equation and a regional equation among Iraqi adults
Authors
- Ling, Jonathan
The attached data was used to assess the applicability of GLI 2012 spirometry equation and a regional equation among Iraqi adults
Authors
- Ling, Jonathan
Supplementary files
Authors
- Tanner, Louise ;
- Pearson, Fiona ;
- Kenny, Ryan ;
- Bhardwaj-Gosling, Rashmi ;
- Ling, Jonathan ;
- Thompson, Katherine
Supplementary files
Authors
- Tanner, Louise ;
- Pearson, Fiona ;
- Kenny, Ryan ;
- Bhardwaj-Gosling, Rashmi ;
- Ling, Jonathan ;
- Thompson, Katherine
Transforming the data. Table S1. Skewness and kurtosis of suicide profile variables. (ZIP 21 kb)
Authors
- Schaik, Paul ;
- Yonghong Peng ;
- Adedokun Ojelabi ;
- Ling, Jonathan
Assessing bias. Figure S1. Plot of standardised predicted values against standardised residuals. Figure S2. Histogram and P-P plot of standardised residuals. (ZIP 91 kb)
Authors
- Schaik, Paul ;
- Yonghong Peng ;
- Adedokun Ojelabi ;
- Ling, Jonathan
Table S2. Multiple regression for transformed and original variables. (XLSX 11 kb)
Authors
- Schaik, Paul ;
- Yonghong Peng ;
- Adedokun Ojelabi ;
- Ling, Jonathan
Table S2. Multiple regression for transformed and original variables. (XLSX 11 kb)
Authors
- Schaik, Paul ;
- Yonghong Peng ;
- Adedokun Ojelabi ;
- Ling, Jonathan
Assessing bias. Figure S1. Plot of standardised predicted values against standardised residuals. Figure S2. Histogram and P-P plot of standardised residuals. (ZIP 91 kb)
Authors
- Schaik, Paul ;
- Yonghong Peng ;
- Adedokun Ojelabi ;
- Ling, Jonathan
Background: Spirometric reference values are crucial in screening, diagnosis and monitoring the therapeutic course of respiratory diseases. These values from a representative population are key to making a precise interpretation of respiratory diseases. The objective of this study is to determine the spirometric reference values of a healthy Jordanian population. Method: Participants were recruited from Al-Zaytoonah University of Jordan and from several pharmacies, polyclinics and hospitals in different cities in Jordan. To formulate Jordanian-specific spirometric reference values, generalised additive models for location scale and shape (GAMLSS) were used. Results: Spirometric reference values were derived from 1,949 healthy nonsmoking adults (1,061 females) and validated in 300 healthy nonsmoking subjects (150 females). Conclusion: Spirometric reference values were developed for a Middle Eastern adult population.
Authors
- Al-Qerem, Walid ;
- Hammad, Alaa M. ;
- Ezeddin S. Gassar ;
- Al-Qirim, Rania A. ;
- Ling, Jonathan