Prediction and Cross-Validation of Video Cartographic Symbol Location Performance

Williges, Robert C.; North, Robert A.

doi:10.1177/001872087301500404

Cited by 11 publications

(2 citation statements)

References 12 publications

(9 reference statements)

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“…The resulting polynomial regressions provided high multiple correlation coefficients, R, that were stable under cross validation (Williges and North, 1973) and within R adj prediction …”

Section: Ccd Examplesmentioning

confidence: 92%

Human Factors Experimental Design and Analysis Reference

Willages¹

2007

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Approved for public release; distribution is unlimited.ii REPORT DOCUMENTATION PAGEForm Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY)July 2007 ARL-RP-0186 SPONSOR/MONITOR'S ACRONYM(S) 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) SPONSOR/MONITOR'S REPORT NUMBERS DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution is unlimited. SUPPLEMENTARY NOTESThe contracting officer's representative (COR) is Sam Middlebrooks, U.S. Army Research Laboratory, ATTN: AMSRD-ARL-HR-MV, Fort Hood, TX, telephone number 254-288-9379. ABSTRACTCADRE (computer-aided design reference for experiments) is a desktop computer tool for human factors and ergonomic researchers. The tool is in Acrobat 1 format for cross-platform computer use and has more than 500 bookmarks for information search. This tool provides more than 850 Power-Point 2 note pages of applied experimental design and analysis reference material. The reference material covers 25 topics and is divided into five major sections including introduction to experimental design, supplemental data collection design and analysis, basic analysis of variance (ANOVA) designs, advanced ANOVA designs, and empirical model building. References to the scientific literature are provided in each topic for supplemental reading. The CADRE tool also provides more than 200 pages explaining 40 examples of statistical analyses covered by the reference material. These examples are hyperlinked to Version 9.1.3 of the SAS 3 (2004) statistical analysis software, and the sample SAS programs can be easily modified for user-specific data.

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“…The resulting polynomial regressions provided high multiple correlation coefficients, R, that were stable under cross validation (Williges and North, 1973) and within R adj prediction …”

Section: Ccd Examplesmentioning

confidence: 92%

Human Factors Experimental Design and Analysis Reference

Willages¹

2007

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“…The number of generalization tests that could be made of this act must, in principle, cover all the regions that the arm can reach and all the velocities that it can perform; the task is so formidable that only the most dogged investigator would attempt it. Fortunately, Williges and his associates (Clark & Williges, 1973;Williges & Baron, 1973;Williges & North, 1973;Williges & Simon, 1971) have brought a technique to our attention, first developed for industrial research, where only some combinations of variables need be tested and where the others are estimated by a predictive equation. Williges and Simon (1971) describe the technique, called response surface methodology:…”

Section: Transformationsmentioning

confidence: 99%