3 resultados para Kolmogorov-Smirnov

em Digital Commons at Florida International University


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The purpose of this study was to test Lotka’s law of scientific publication productivity using the methodology outlined by Pao (1985), in the field of Library and Information Studies (LIS). Lotka’s law has been sporadically tested in the field over the past 30+ years, but the results of these studies are inconclusive due to the varying methods employed by the researchers. ^ A data set of 1,856 citations that were found using the ISI Web of Knowledge databases were studied. The values of n and c were calculated to be 2.1 and 0.6418 (64.18%) respectively. The Kolmogorov-Smirnov (K-S) one sample goodness-of-fit test was conducted at the 0.10 level of significance. The Dmax value is 0.022758 and the calculated critical value is 0.026562. It was determined that the null hypothesis stating that there is no difference in the observed distribution of publications and the distribution obtained using Lotka’s and Pao’s procedure could not be rejected. ^ This study finds that literature in the field of Library and Information Studies does conform to Lotka’s law with reliable results. As result, Lotka’s law can be used in LIS as a standardized means of measuring author publication productivity which will lead to findings that are comparable on many levels (e.g., department, institution, national). Lotka’s law can be employed as an empirically proven analytical tool to establish publication productivity benchmarks for faculty and faculty librarians. Recommendations for further study include (a) exploring the characteristics of the high and low producers; (b) finding a way to successfully account for collaborative contributions in the formula; and, (c) a detailed study of institutional policies concerning publication productivity and its impact on the appointment, tenure and promotion process of academic librarians. ^

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Goodness-of-fit tests have been studied by many researchers. Among them, an alternative statistical test for uniformity was proposed by Chen and Ye (2009). The test was used by Xiong (2010) to test normality for the case that both location parameter and scale parameter of the normal distribution are known. The purpose of the present thesis is to extend the result to the case that the parameters are unknown. A table for the critical values of the test statistic is obtained using Monte Carlo simulation. The performance of the proposed test is compared with the Shapiro-Wilk test and the Kolmogorov-Smirnov test. Monte-Carlo simulation results show that proposed test performs better than the Kolmogorov-Smirnov test in many cases. The Shapiro Wilk test is still the most powerful test although in some cases the test proposed in the present research performs better.

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The purpose of this study was to test Lotka’s law of scientific publication productivity using the methodology outlined by Pao (1985), in the field of Library and Information Studies (LIS). Lotka’s law has been sporadically tested in the field over the past 30+ years, but the results of these studies are inconclusive due to the varying methods employed by the researchers. A data set of 1,856 citations that were found using the ISI Web of Knowledge databases were studied. The values of n and c were calculated to be 2.1 and 0.6418 (64.18%) respectively. The Kolmogorov-Smirnov (K-S) one sample goodness-of-fit test was conducted at the 0.10 level of significance. The Dmax value is 0.022758 and the calculated critical value is 0.026562. It was determined that the null hypothesis stating that there is no difference in the observed distribution of publications and the distribution obtained using Lotka’s and Pao’s procedure could not be rejected. This study finds that literature in the field of library and Information Studies does conform to Lotka’s law with reliable results. As result, Lotka’s law can be used in LIS as a standardized means of measuring author publication productivity which will lead to findings that are comparable on many levels (e.g., department, institution, national). Lotka’s law can be employed as an empirically proven analytical tool to establish publication productivity benchmarks for faculty and faculty librarians. Recommendations for further study include (a) exploring the characteristics of the high and low producers; (b) finding a way to successfully account for collaborative contributions in the formula; and, (c) a detailed study of institutional policies concerning publication productivity and its impact on the appointment, tenure and promotion process of academic librarians.