Programje
Statistical software developed at the Institute of Biomedical Informatics, Faculty of Medicine, University of Ljubljana:
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re R function for calculating the Re measure of explained variation for the Cox model, Aalen's model or any of the parametric models included in the survreg function
- function
- programmed by Maja Pohar Perme
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pseucheck R function for model diagnostics using pseudo-observations: for models fitted with 'coxph', 'crr', 'lm' and 'geese' function
- function
- requires packages: pseudo, survival, cmprsk, geese
- programmed by Maja Pohar Perme
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koq function for S/S-PLUS (available at StatLib)
- calculates Kent & O'Quigley's measure of dependence for censored data when dependence between time and covariates is modelled by Cox's model
- programmed by Andrej Blejec & Janez Stare
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bj function for S/S-PLUS/R (incorporated into Design package by Frank E. Harrell)
- fits the Buckley-James distribution-free least squares multiple regression model to a possibly right-censored response variable
- programmed by Janez Stare, Harald Heinzl & Frank E. Harrell
- measures of explained variation in survival analysis (other than koq) for S/S-PLUS (available upon request)
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pseu R function for Cox and additive model diagnostics using pseudo-observations for producing plots described in Pohar Perme M, Andersen PK. Checking hazard regression models using pseudo-observations. Statistics in Medicine 2008;27:5309-5328.
- function
- help file
- requires the following libraries: survival, Design, geepack (all available from CRAN) and timereg (available from http://staff.pubhealth.ku.dk/~ts/timereg.html)
- programmed by Maja Pohar
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relsurv package for relative survival analysis in R (version 2.0, included as contributed package into CRAN)
- implementation of existing regression methods plus our own method (Stare, Henderson & Pohar: An individual measure of relative survival. JRSS Series C, 2005, 54(1), 115-126)
- implementation of goodness of fit methods based on residuals (Stare, Pohar & Henderson: Goodness of fit of relative survival. Statistics in Medicine, 2005, 24(24), 3911-3925)
- paper describing the package (Pohar & Stare: Relative survival analysis in R. Computer Methods and Programs in Biomedicine, 2006, 81(3), 272-278)
- programmed by Maja Pohar
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interactive demonstration of relative survival
- website (form with links to instructions and references)
- based on the individual measure of relative survival and the relsurv package (see above)
- idea by Janez Stare, implementation by Brane Leskošek (Perl, Linux) and Maja Pohar (R)
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R functions for calculating the reduced citation distribution (h-index) function
- function
- programmed by Maja Pohar Perme
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chplot package for R (current version 1.2, included as contributed package into CRAN)
- produces augmented convex hull plots, which are a nice and informative way of displaying large amounts of grouped bivariate data
- paper describing the package (Vidmar & Pohar: Augmented convex hull plots: Rationale, implementation in R and biomedical applications. Computer Methods and Programs in Biomedicine, 2005, 78(1), 69-74)
- package source (tar.gz)
- binary package for Windows (zip)
- idea and design by Gaj Vidmar, programmed by Maja Pohar
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visualisation of concordance
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two newly proposed graphical displays for the previously unaddressed task of visualising concordance (for ranked data, as for, e.g., Kendall's W)
- concordance bubble-plot (Excel workbook with macro and sample data) -- depicts raw data, i.e., the actual ranks assigned to objects
- pin-cushion plot (interactive and batch-mode code with sample data for jsplot; zipped) -- depicts within-object rank differences
- paper describing the methods (Vidmar & Rode: Visualising concordance. Computational Statistics, 2007, 22(3), in press)
- concordance parallel-coordinates-plot (SigmaPlot 2000 notebook; zipped) -- another possibility (depicts pairs of ranks assigned to objects), which proved to be less practically useful (though esthetically appealing)
- ideas, design and implementation by Gaj Vidmar & Nino Rode
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two newly proposed graphical displays for the previously unaddressed task of visualising concordance (for ranked data, as for, e.g., Kendall's W)
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Bland-Altman function for R
- displays the classic Bland-Altman difference plot with limits of agreement, prints the mean difference and both agreement limits (along with 95% CIs) and returns a list of relevant parameters (the mean difference, its SD and SE, upper and lower agreement limits, their SE, and the t value used in the calculation of CIs)
- function and sample data (zip)
- programmed by Jaro Lajovic
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Excel workbooks for demonstrational and teaching purposes
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Poisson regression
- estimation procedure demonstrated with example 4.5 from A.J.Dobson, An Introduction to Generalized Linear Models (1st ed.), Chapman & Hall, 1990
- based on Excel's matrix functions, step-by-step iteration with macro
- requires Excel 97 or higher
- idea and implementation by Gaj Vidmar
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parallel coordinates plot
- static version for producing presentation/publication graphics
- for two variables, typical use is in conjunction with paired-samples t-test, but such plot can also accompany the Bland-Altman method (see below)
- requires Excel 97 or higher
- idea and implementation by Gaj Vidmar
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modified Box-Cox power transformation towards normal distribution
- the lambda parameter can be either input manually or estimated with the maximum-likelihood method using Excel's Solver add-in
- the transformation effect is demonstrated with automated histogram
- requires Excel 97 or higher
- idea and implementation by Gaj Vidmar
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interactive population pyramid (Eurostat's projection for Slovenia 2004-2051)
- the words are in Slovenian, but they are very few and with the image, everything should be understandable for anyone speaking any European language
- data obtained from the SI-STAT database of the Statistical Office of the Republich of SLovenia
- inspired by the demographical model movies by Erich Neuwirth (University of Vienna, Austria)
- requires Excel 97 or higher
- implementation by Gaj Vidmar
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Bland-Altman plot
- implements the classic, simple, indispensable yet still too often overlooked method-comparison procedure by Bland & Altman
- requires Excel 97 or higher
- core code by Michael Schacht Hansen (Section for Health Informatics, University of Aarhus, Dennmark); workbook, error trapping and embellishment by Jaro Lajovic & Gaj Vidmar
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windowgram and coplot
- presents two methods, endorsed by Larry Weldon (Simon Fraser University, Vancouver, Canada) as under-used but simple and ideal for inclusion into introductory statistics courses
- windowgrams are the simplest case of and hence the introduction to kernel density estimation; coplots is short for conditional plots, so it is just another name for what is also called panel plots, Trellis display or lattice graphics
- requires Excel 97 or higher
- idea and implementation by Gaj Vidmar
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dot plots
- presents simple and multi-way dotplots as invented by William S. Cleveland and promoted by S-Plus and R
- requires Excel 97 or higher
- idea and implementation by Gaj Vidmar
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univariate dot-density plot
- presents the simplest yet very nice solution, i.e, character-based cell-chart, of what is also known as stacked dot-plot
- requires Excel 97 or higher
- idea and implementation by Gaj Vidmar
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stem-and-leaf plot
- requires Excel 97 or higher
- macro by Nick Maxwell (Data Matters Resource Center); debugging and workbook design by Gaj Vidmar
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Kaplan-Maier survival curve estimation
- requires Excel 97 or higher
- unauthorised English translation and modification of the workbook with macro by Shigenobu Aoki (Faculty of Social and Information Studies, Gunma University, Japan); produced by Gaj Vidmar
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automated histogram binning (with random sampling from normal distribution)
- requires Excel 97 or higher
- idea and implementation by Gaj Vidmar
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Iris dataset
- the most (perhaps too) often used (and sometimes abused) dataset in the field of statistics (too often abused in the fields of machine learning, data mining and information visualisation)
- reference for data collection: Anderson, E. (1935). The irises of the Gaspe Peninsula. Bulletin of the American Iris Society, 59, 2-5.
- reference for data analysis: Fisher, R.A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7 (2), 179-188.
- a truly comprehensive presentation: Les Iris de Fisher ou Comment se familiariser avec le logiciel R (in French)
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Poisson regression
Ostalo programje ki smo ga razvili:
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PowerPointov makro za štetje vseh znakov v predstavitvi
- sprogramiral Gaj Vidmar
- razvit za potrebe prevajalcev, da olajša zaračunavanje prevodov predstavitev
- poleg znakov v diapozitivih, zna makro prešteti tudi znake v matricah diapozitiva, opomb, izročkov in naslova
- deluje z angleško in slovensko verzijo Microsoftove pisarne
- makro je namenjen slovenskim uporabnikom, zato je uporabniški vmesnik v slovenščini in tudi navodila za namestitev/odstranitev (spodaj) so le v slovenščini
- programska koda je zaščitena z geslom
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namestitev in odstranitev:
- datoteko StetjeZnakov.ppt shranite na disk
- zaženite PowerPoint in datoteko odprite, nato pa jo shranite kot dodatek (.ppa)
- kam se bo dodatek shranil, je odvisno od konfiguracije računalnika (npr. na Windows® 2000 v mapo C:\Documents and Settings\uporabniško_ime\Application Data\Microsoft\Addins)
- zaprite PowerPoint
- ponovno zaženite Powerpoint ter poskrbite, da so makri omogočeni (Orodja - Možnosti - Varnost - Varnost makrov... - nizka ali srednja)
- namestite nov dodatek (Orodja - Dodatki... - Dodaj nov...)
- v meniju Orodja se bo pojavila opcija "Štetje znakov"
- če ga ne želite več uporabljati, dodatek preko menija, iz katerega ste ga namestili, odstranite iz pomnilnika ali povsem odstranite
- tudi, če izberete popolno odstranitev, bo datoteka StetjeStrani.ppa ostala na disku, zato jo morate, če to želite, izbrisati ročno iz zgoraj omenjene mape