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r-qcewas
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public |
Tools for (automated and manual) quality control of the results of Epigenome-Wide Association Studies.
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2024-01-16 |
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r-qcba
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public |
CBA postprocessing algorithm that creates smaller models for datasets containing quantitative (numerical) attributes. Article describing QCBA is published in Tomas Kliegr (2017) <arXiv:1711.10166>. The package can also postprocess results of the SBRL package, which is no longer in CRAN, but can be obtained from <https://github.com/cran/sbrl>.
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2024-01-16 |
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r-pzfx
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public |
Read and write 'GraphPad Prism' '.pzfx' files in R.
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2024-01-16 |
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r-qaig
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public |
A tool for automatic generation of sibling items from a parent item model defined by the user. It is an implementation of the process automatic item generation (AIG) focused on generating quantitative multiple-choice type of items (see Embretson, Kingston (2018) <doi:10.1111/jedm.12166>).
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2024-01-16 |
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r-qboxplot
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public |
Produce quantile-based box-and-whisker plot(s).
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2024-01-16 |
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r-pwrss
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public |
Statistical power and minimum required sample size calculations for (1) testing a proportion (one-sample) against a constant, (2) testing a mean (one-sample) against a constant, (3) testing difference between two proportions (independent samples), (4) testing difference between two means or groups (parametric and non-parametric tests for independent and paired samples), (5) testing a correlation (one-sample) against a constant, (6) testing difference between two correlations (independent samples), (7) testing a single coefficient in multiple linear regression, logistic regression, and Poisson regression (with standardized or unstandardized coefficients, with no covariates or covariate adjusted), (8) testing an indirect effect (with standardized or unstandardized coefficients, with no covariates or covariate adjusted) in the mediation analysis (Sobel, Joint, and Monte Carlo tests), (9) testing an R-squared against zero in linear regression, (10) testing an R-squared difference against zero in hierarchical regression, (11) testing an eta-squared or f-squared (for main and interaction effects) against zero in analysis of variance (could be one-way, two-way, and three-way), (12) testing an eta-squared or f-squared (for main and interaction effects) against zero in analysis of covariance (could be one-way, two-way, and three-way), (13) testing an eta-squared or f-squared (for between, within, and interaction effects) against zero in one-way repeated measures analysis of variance (with non-sphericity correction and repeated measures correlation), and (14) testing goodness-of-fit or independence for contingency tables. Alternative hypothesis can be formulated as "not equal", "less", "greater", "non-inferior", "superior", or "equivalent" in (1), (2), (3), and (4); as "not equal", "less", or "greater" in (5), (6), (7) and (8); but always as "greater" in (9), (10), (11), (12), (13), and (14). Reference: Bulus and Polat (2023) <https://osf.io/ua5fc>.
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2024-01-16 |
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r-pwt10
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The Penn World Table 10.x (<https://www.rug.nl/ggdc/productivity/pwt/>) provides information on relative levels of income, output, input, and productivity for 183 countries between 1950 and 2019.
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2024-01-16 |
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r-pymturkr
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public |
Provides access to the latest 'Amazon Mechanical Turk' ('MTurk') <https://www.mturk.com> Requester API (version '2017–01–17'), replacing the now deprecated 'MTurkR' package.
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2024-01-16 |
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r-pyramid
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public |
Drawing population pyramid using (1) data.frame or (2) vectors. The former is named as pyramid() and the latter pyramids(), as wrapper function of pyramid(). pyramidf() is the function to draw population pyramid within the specified frame.
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2024-01-16 |
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r-pxweb
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Generic interface for the PX-Web/PC-Axis API. The PX-Web/PC-Axis API is used by organizations such as Statistics Sweden and Statistics Finland to disseminate data. The R package can interact with all PX-Web/PC-Axis APIs to fetch information about the data hierarchy, extract metadata and extract and parse statistics to R data.frame format. PX-Web is a solution to disseminate PC-Axis data files in dynamic tables on the web. Since 2013 PX-Web contains an API to disseminate PC-Axis files.
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2024-01-16 |
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r-pxr
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public |
Provides a set of functions for reading and writing PC-Axis files, used by different statistical organizations around the globe for data dissemination.
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2024-01-16 |
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r-pwt9
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public |
The Penn World Table 9.x (<http://www.ggdc.net/pwt/>) provides information on relative levels of income, output, inputs, and productivity for 182 countries between 1950 and 2017.
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2024-01-16 |
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r-pwt8
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public |
The Penn World Table 8.x provides information on relative levels of income, output, inputs, and productivity for 167 countries between 1950 and 2011.
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2024-01-16 |
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r-pubmed.miner
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public |
Text mining of PubMed Abstracts (text and XML) from <https://pubmed.ncbi.nlm.nih.gov/>.
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2024-01-16 |
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r-pubmedr
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public |
A set of tools to extract bibliographic content from 'PubMed' database using 'NCBI' REST API <https://www.ncbi.nlm.nih.gov/home/develop/api/>.
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2024-01-16 |
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r-pwt
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public |
The Penn World Table provides purchasing power parity and national income accounts converted to international prices for 189 countries for some or all of the years 1950-2010.
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2024-01-16 |
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r-pwrrasch
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public |
Statistical power simulation for testing the Rasch Model based on a three-way analysis of variance design with mixed classification.
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2024-01-16 |
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r-pwrab
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public |
Power analysis for AB testing. The calculations are based on the Welch's unequal variances t-test, which is generally preferred over the Student's t-test when sample sizes and variances of the two groups are unequal, which is frequently the case in AB testing. In such situations, the Student's t-test will give biased results due to using the pooled standard deviation, unlike the Welch's t-test.
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2024-01-16 |
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r-pwr2
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public |
User friendly functions for power and sample size analysis at one-way and two-way ANOVA settings take either effect size or delta and sigma as arguments. They are designed for both one-way and two-way ANOVA settings. In addition, a function for plotting power curves is available for power comparison, which can be easily visualized by statisticians and clinical researchers.
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2024-01-16 |
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r-pwr
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public |
Power analysis functions along the lines of Cohen (1988).
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2024-01-16 |
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r-pvclust
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public |
An implementation of multiscale bootstrap resampling for assessing the uncertainty in hierarchical cluster analysis. It provides SI (selective inference) p-value, AU (approximately unbiased) p-value and BP (bootstrap probability) value for each cluster in a dendrogram.
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2024-01-16 |
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r-pvclass
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public |
Computes nonparametric p-values for the potential class memberships of new observations as well as cross-validated p-values for the training data. The p-values are based on permutation tests applied to an estimated Bayesian likelihood ratio, using a plug-in statistic for the Gaussian model, 'k nearest neighbors', 'weighted nearest neighbors' or 'penalized logistic regression'. Additionally, it provides graphical displays and quantitative analyses of the p-values.
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2024-01-16 |
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r-pushoverr
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public |
Send push notifications to mobile devices or the desktop using 'Pushover' <https://pushover.net>. These notifications can display things such as results, job status, plots, or any other text or numeric data.
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2024-01-16 |
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r-pushbar
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public |
Create sliders from left, right, top and bottom which may include any html or 'Shiny' input or output.
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2024-01-16 |
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r-purging
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public |
Simple method of purging independent variables of mediating effects. First, regress the direct variable on the indirect variable. Then, used the stored residuals as the new purged (direct) variable in the updated specification. This purging process allows for use of a new direct variable uncorrelated with the indirect variable. Please cite the method and/or package using Waggoner, Philip D. (2018) <doi:10.1177/1532673X18759644>.
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2024-01-16 |
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r-purge
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public |
Enables the removal of training data from fitted R models while retaining predict functionality. The purged models are more portable as their memory footprints do not scale with the training sample size.
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2024-01-16 |
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r-pulsar
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public |
Model selection for penalized graphical models using the Stability Approach to Regularization Selection ('StARS'), with options for speed-ups including Bounded StARS (B-StARS), batch computing, and other stability metrics (e.g., graphlet stability G-StARS). Christian L. Müller, Richard Bonneau, Zachary Kurtz (2016) <arXiv:1605.07072>.
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2024-01-16 |
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r-pumilior
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public |
R package to query and get data out of a Pumilio sound archive system (http://ljvillanueva.github.io/pumilio/).
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2024-01-16 |
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r-publish
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public |
A bunch of convenience functions that transform the results of some basic statistical analyses into table format nearly ready for publication. This includes descriptive tables, tables of logistic regression and Cox regression results as well as forest plots.
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2024-01-16 |
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r-psyntur
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public |
Provides functions and data-sets that are helpful for teaching statistics and data analysis. It was originally designed for use when teaching students in the Psychology Department at Nottingham Trent University.
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2024-01-16 |
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r-ptycho
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public |
Bayesian variable selection for linear regression models using hierarchical priors. There is a prior that combines information across responses and one that combines information across covariates, as well as a standard spike and slab prior for comparison. An MCMC samples from the marginal posterior distribution for the 0-1 variables indicating if each covariate belongs to the model for each response.
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2024-01-16 |
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r-ptwikiwords
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public |
Contains a dataset of words used in 15.000 randomly extracted pages from the Portuguese Wikipedia (<https://pt.wikipedia.org/>).
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2024-01-16 |
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r-ptprocess
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public |
Fits and analyses time dependent marked point process models with an emphasis on earthquake modelling. For a more detailed introduction to the package, see the topic "PtProcess". A list of recent changes can be found in the topic "Change Log".
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2024-01-16 |
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r-pte
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public |
We provide inference for personalized medicine models. Namely, we answer the questions: (1) how much better does a purported personalized recommendation engine for treatments do over a business-as-usual approach and (2) is that difference statistically significant?
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2024-01-16 |
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r-psyphy
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public |
An assortment of functions that could be useful in analyzing data from psychophysical experiments. It includes functions for calculating d' from several different experimental designs, links for m-alternative forced-choice (mafc) data to be used with the binomial family in glm (and possibly other contexts) and self-Start functions for estimating gamma values for CRT screen calibrations.
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2024-01-16 |
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r-psychotree
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Recursive partitioning based on psychometric models, employing the general MOB algorithm (from package partykit) to obtain Bradley-Terry trees, Rasch trees, rating scale and partial credit trees, and MPT trees, trees for 1PL, 2PL, 3PL and 4PL models and generalized partial credit models.
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2024-01-16 |
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r-psychometric
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public |
Provides tools useful for measurement theory (Allen & Yen 2001)<ISBN: 157766230X>, meta-analysis (validity-generalization) (Schmidt & Hunter)<doi:10.4135/9781483398105>, reliability, item analysis, inter-rater reliability, classical utility, and correlation analysis (Cohen et. al. 2003)<doi:10.4324/9780203774441>.
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2024-01-16 |
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r-psycho
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public |
The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.
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2024-01-16 |
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r-psychtools
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Support functions, data sets, and vignettes for the 'psych' package. Contains several of the biggest data sets for the 'psych' package as well as four vignettes. A few helper functions for file manipulation are included as well. For more information, see the <https://personality-project.org/r/> web page.
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2024-01-16 |
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r-proreg
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Offers a variety of tools, such as specific plots and regression model approaches, for analyzing different patient reported questionnaires. Specially, mixed-effects models based on the beta-binomial distribution are implemented to deal with binomial data with over-dispersion (see Najera-Zuloaga J., Lee D.-J. and Arostegui I. (2018) <doi:10.1177/0962280217690413>).
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2024-01-16 |
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r-pstat
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Calculating Pst values to assess differentiation among populations from a set of quantitative traits is the primary purpose of such a package. The bootstrap method provides confidence intervals and distribution histograms of Pst. Variations of Pst in function of the parameter c/h^2 are studied as well. Finally, the package proposes different transformations especially to eliminate any variation resulting from allometric growth (calculation of residuals from linear regressions, Reist standardizations or Aitchison transformation).
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2024-01-16 |
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r-psy
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public |
Kappa, ICC, reliability coefficient, parallel analysis, multi-traits multi-methods, spherical representation of a correlation matrix.
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2024-01-16 |
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r-psoptim
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public |
Particle swarm optimization - a basic variant.
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2024-01-16 |
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r-pso
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public |
Provides an implementation of particle swarm optimisation consistent with the standard PSO 2007/2011 by Maurice Clerc. Additionally a number of ancillary routines are provided for easy testing and graphics.
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2024-01-16 |
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r-pseval
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Contains the core methods for the evaluation of principal surrogates in a single clinical trial. Provides a flexible interface for defining models for the risk given treatment and the surrogate, the models for integration over the missing counterfactual surrogate responses, and the estimation methods. Estimated maximum likelihood and pseudo-score can be used for estimation, and the bootstrap for inference. A variety of post-estimation summary methods are provided, including print, summary, plot, and testing.
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2024-01-16 |
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r-psagraphics
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A collection of functions that primarily produce graphics to aid in a Propensity Score Analysis (PSA). Functions include: cat.psa and box.psa to test balance within strata of categorical and quantitative covariates, circ.psa for a representation of the estimated effect size by stratum, loess.psa that provides a graphic and loess based effect size estimate, and various balance functions that provide measures of the balance achieved via a PSA in a categorical covariate.
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2024-01-16 |
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r-provviz
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Displays provenance graphically for provenance collected by the 'rdt' or 'rdtLite' packages, or other tools providing compatible PROV JSON output. The exact format of the JSON created by 'rdt' and 'rdtLite' is described in <https://github.com/End-to-end-provenance/ExtendedProvJson>. More information about rdtLite and associated tools is available at <https://github.com/End-to-end-provenance/> and Barbara Lerner, Emery Boose, and Luis Perez (2018), Using Introspection to Collect Provenance in R, Informatics, <doi: 10.3390/informatics5010012>.
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2024-01-16 |
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r-prroc
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public |
Computes the areas under the precision-recall (PR) and ROC curve for weighted (e.g., soft-labeled) and unweighted data. In contrast to other implementations, the interpolation between points of the PR curve is done by a non-linear piecewise function. In addition to the areas under the curves, the curves themselves can also be computed and plotted by a specific S3-method. References: Davis and Goadrich (2006) <doi:10.1145/1143844.1143874>; Keilwagen et al. (2014) <doi:10.1371/journal.pone.0092209>; Grau et al. (2015) <doi:10.1093/bioinformatics/btv153>.
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2024-01-16 |
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r-provparser
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R functions to access provenance information collected by 'rdt' or 'rdtLite'. The information is stored inside a 'ProvInfo' object and can be accessed through a collection of functions that will return the requested data. The exact format of the JSON created by 'rdt' and 'rdtLite' is described in <https://github.com/End-to-end-provenance/ExtendedProvJson>.
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2024-01-16 |
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r-proton
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public |
'The Proton Game' is a console-based data-crunching game for younger and older data scientists. Act as a data-hacker and find Slawomir Pietraszko's credentials to the Proton server. You have to solve four data-based puzzles to find the login and password. There are many ways to solve these puzzles. You may use loops, data filtering, ordering, aggregation or other tools. Only basics knowledge of R is required to play the game, yet the more functions you know, the more approaches you can try. The knowledge of dplyr is not required but may be very helpful. This game is linked with the ,,Pietraszko's Cave'' story available at http://biecek.pl/BetaBit/Warsaw. It's a part of Beta and Bit series. You will find more about the Beta and Bit series at http://biecek.pl/BetaBit.
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2024-01-16 |
