Social and Behavioral Sciences Commons^™

Ordering Up Gimlet For Data Mining Success., Susan Gardner, Ken Simon

Susan Gardner Archambault

What Counts? Assessing The Value Of Non-Text Resources, Tammy Sugarman, Stephanie Krueger

Tammy Sugarman

In this era of tightening budgets, librarians are increasingly turning to usage data from licensed resource providers to support difficult collection development decisions. The most recent release of the COUNTER code of practice for usage data reporting and the SUSHI XML protocol further support this decision-making process. Providing "COUNTER compliant" usage reports is an increasingly important feature expected of licensed digital materials by academic libraries. COUNTER reports are designed to primarily measure usage of textual resources such as: journals, e-books and database indexes. However, for multimedia resources that contain exclusively images, time-based media, or audio content, the usage patterns and …

Using Database Use Reports To Assess Library Instruction, Judith Garrison

Judith Garrison

No abstract provided.

Advice From The Trenches: Post Purchase Evaluation, Annie Smith, Regina Koury, Cheryl Sebold, Jenny Semenza

Annie Smith

Presented as part of a larger presentation about evaluating and purchasing databases and negotiating database licenses, this section focused on post purchase evaluation of databases. Databases are constantly changing their content and their features and these need to be monitored. In addition, this presentation covers how to collect and analyze usage statistics.

Big Macs And Eigenfactor Scores: Don't Let The Correlation Coefficients Fool You, Jevin D. West, Carl T. Bergstrom, Theodore C. Bergstrom

Ted C Bergstrom

A recent article by Phil Davis suggested that the Eigenvalue metric does adds little useful information to the more simply calculated measure of total citations published by the ISI. This paper argues that Davis's claim is an instance of a classic statistical fallacy of spurious correlation. Based on an analysis of the entire 2006 ISI Journal Citation Reports, we show that there are statistically and economically significant differences between the Eigenfactor metrics and the ISI's impact factor and total citations.

Temporal Changes In The Parameters Of Statistical Distribution Of Journal Impact Factor, Sudhanshu K. Mishra

Sudhanshu K Mishra

Statistical distribution of Journal Impact Factor (JIF) is characteristically asymmetric and non-mesokurtic. Even the distribution of log10(JIF) exhibits conspicuous skewness and non-mesokurticity. In this paper we estimate the parameters of Johnson SU distribution fitting to the log10(JIF) data for 10 years, 1999 through 2008, and study the temporal variations in those estimated parameters. We also study ‘over-the-samples stability’ in the estimated parameters for each year by the method of re-sampling close to bootstrapping. It has been found that log10(JIF) is Pearson-IV distributed. Johnson SU distribution fits very well to the data and yields parameters stable over the samples. We conclude …

Interlibrary Loan Patron Use Patterns: An Examination Of Borrowing Requests At A Mid-Sized Academic Library, Bradley P. Tolppanen, Janice Derr

Bradley P. Tolppanen

The results of a recently conducted study of interlibrary loan fee-based borrowing requests are presented in this article. The study examined 3,074 borrowing requests completed over a three-year period from January 2007 to December 2009. An analysis of the statistics was made to determine patron behavior in submitting requests and the types of materials being requested.

Empirical Probability Distribution Of Journal Impact Factor And Over-The-Samples Stability In Its Estimated Parameters, Sudhanshu K. Mishra

Sudhanshu K Mishra

The data on JIFs provided by Thomson Scientific can only be considered as a sample since they do not cover the entire universe of those documents that cite an intellectual output (paper, article, etc) or are cited by others. Then, questions arise if the empirical distribution (best fit to the JIF data for any particular year) really represents the true or universal distribution, are its estimated parameters stable over the samples and do they have some scientific interpretation? It may be noted that if the estimated parameters do not exhibit stability over the samples (while the sample size is large …

A Note On Empirical Sample Distribution Of Journal Impact Factors In Major Discipline Groups, Sudhanshu K. Mishra

Sudhanshu K Mishra

What type of statistical distribution do the Journal Impact Factors follow? In the past, researchers have hypothesized various types of statistical distributions underlying the generation mechanism of journal impact factors. These are: lognormal, normal, approximately normal, Weibull, negative exponential, combination of exponentials, Poisson, Generalized inverse Gaussian-Poisson, negative binomial, generalized Waring, gamma, etc. It is pertinent to note that the major characteristics of JIF data lay in the asymmetry and non-mesokurticity. The present study, frequently encounters Burr-XII, inverse Burr-III (Dagum), Johnson SU, and a few other distributions closely related to Burr distributions to best fit the JIF data in subject groups …

2009 Utah Valley University Database Report, Annie Smith

Annie Smith

This report was prepared for the UVU Library administration.