title: Scientific LogAnalyzer: a web-based tool for analyses of server log files in psychological research.
abstract: Scientific LogAnalyzer is a platform-independent interactive Web service for the analysis of log files. Scientific LogAnalyzer offers several features not available in other log file analysis tools--for example, organizational criteria and computational algorithms suited to aid behavioral and social scientists. Scientific LogAnalyzer is highly flexible on the input side (unlimited types of log file formats), while strictly keeping a scientific output format. Features include (1) free definition of log file format, (2) searching and marking dependent on any combination of strings (necessary for identifying conditions in experiment data), (3) computation of response times, (4) detection of multiple sessions, (5) speedy analysis of large log files, (6) output in HTML and/or tab-delimited form, suitable for import into statistics software, and (7) a module for analyzing and visualizing drop-out. Several methodological features specifically needed in the analysis of data collected in Internet-based experiments have been implemented in the Web-based tool and are described in this article. A regression analysis with data from 44 log file analyses shows that the size of the log file and the domain name lookup are the two main factors determining the duration of an analysis. It is less than a minute for a standard experimental study with a 2 x 2 design, a dozen Web pages, and 48 participants (ca. 800 lines, including data from drop-outs). The current version of Scientific LogAnalyzer is freely available for small log files. Its Web address is http://genpsylab-logcrunsh.unizh.ch/.
authors.affiliation: Sozial-und Wirtchaftspsychologie, University of Zurich, Zurich, Switzerland. u.reips@psychologie.unizh.ch
authors.forename: Ulf-Dietrich
authors.initials: UD
authors.lastname: Reips
authors.forename: Stefan
authors.initials: S
authors.lastname: Stieger
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D011589:Psychology, Experimental / Q000295:instrumentation*; D012044:Regression Analysis; D012984:Software; D014584:User-Computer Interface