| Literature DB >> 26999739 |
Christopher L Benson, Christopher L Magee.
Abstract
Year: 2016 PMID: 26999739 PMCID: PMC4801350 DOI: 10.1371/journal.pone.0151931
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Technological Improvement Rates vs Simple Patent Count (A), ratio of patents with greater than 20 citations (B), and average number of forward citations within 3 years of publication (C); the Pearson correlation coefficient (cp), the null hypothesis acceptance (cutoff at p = 0.05) and the values of the independent variable for the domains having maximum and minimum values are shown in the upper right corner.
Least Squares Linear Regression Models for Predicting Technological Improvement Rates with R2 shown for each model and the coefficients shown for each metric included in the model and its p value.
| Variable/Models | A | B | C | D | E | F | G | H |
|---|---|---|---|---|---|---|---|---|
| (2) Average number of forward citations | -0.01 | 0.014 | 0.015 | |||||
| (5) Average publication year | 0.0155 | 0.024 | ||||||
| (6) Average Age of Citation | -0.003 | 0.0004 | -0.018 | |||||
| (9) Total mean publication date of backward citations | 0.01 | 0.024 | 0.020 | |||||
| (10) Average Cited by within 3 years | 0.16 | 0.11 | 0.15 | 0.141 | 0.19 | |||
| Intercept | -0.23 | -20.44 | -0.19 | -31.197 | -0.21 | -47.66 | -41.37 | -47.1 |