Showing 5 of total 5 results (show query)
kenaho1
asbio:A Collection of Statistical Tools for Biologists
Contains functions from: Aho, K. (2014) Foundational and Applied Statistics for Biologists using R. CRC/Taylor and Francis, Boca Raton, FL, ISBN: 978-1-4398-7338-0.
Maintained by Ken Aho. Last updated 3 months ago.
5 stars 7.32 score 310 scripts 3 dependents
spkaluzny
splus2R:Supplemental S-PLUS Functionality in R
Currently there are many functions in S-PLUS that are missing in R. To facilitate the conversion of S-PLUS packages to R packages, this package provides some missing S-PLUS functionality in R.
Maintained by Stephen Kaluzny. Last updated 1 years ago.
1 stars 6.56 score 82 scripts 30 dependents
jeksterslab
semmcci:Monte Carlo Confidence Intervals in Structural Equation Modeling
Monte Carlo confidence intervals for free and defined parameters in models fitted in the structural equation modeling package 'lavaan' can be generated using the 'semmcci' package. 'semmcci' has three main functions, namely, MC(), MCMI(), and MCStd(). The output of 'lavaan' is passed as the first argument to the MC() function or the MCMI() function to generate Monte Carlo confidence intervals. Monte Carlo confidence intervals for the standardized estimates can also be generated by passing the output of the MC() function or the MCMI() function to the MCStd() function. A description of the package and code examples are presented in Pesigan and Cheung (2023) <doi:10.3758/s13428-023-02114-4>.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 3 months ago.
confidence-intervalsmonte-carlostructural-equation-modeling
2 stars 5.39 score 76 scriptsjeksterslab
betaMC:Monte Carlo for Regression Effect Sizes
Generates Monte Carlo confidence intervals for standardized regression coefficients (beta) and other effect sizes, including multiple correlation, semipartial correlations, improvement in R-squared, squared partial correlations, and differences in standardized regression coefficients, for models fitted by lm(). 'betaMC' combines ideas from Monte Carlo confidence intervals for the indirect effect (Pesigan and Cheung, 2023 <doi:10.3758/s13428-023-02114-4>) and the sampling covariance matrix of regression coefficients (Dudgeon, 2017 <doi:10.1007/s11336-017-9563-z>) to generate confidence intervals effect sizes in regression.
Maintained by Ivan Jacob Agaloos Pesigan. Last updated 3 months ago.
confidence-intervalsmonte-carloregression-effect-sizesstandardized-regression-coefficients
1 stars 4.27 score 22 scripts
r-forge
TopKLists:Inference, Aggregation and Visualization for Top-K Ranked Lists
For multiple ranked input lists (full or partial) representing the same set of N objects, the package TopKLists offers (1) statistical inference on the lengths of informative top-k lists, (2) stochastic aggregation of full or partial lists, and (3) graphical tools for the statistical exploration of input lists, and for the visualization of aggregation results.
Maintained by Michael G. Schimek. Last updated 9 years ago.
4.05 score 37 scripts 1 dependents