RcmdrPlugin.MPAStats-package: R Commander Plug-in for MPA Statistics
In andrewheiss/RcmdrPlugin.MPAStats: R Commander Plug-in for MPA Statistics
Description
This package provides an R Commander plugin that offers a
unified menu of new and pre-existing statistical functions
related to public management and policy analysis statistics.
Functions and menus have been renamed according to the usage
in PMGT 630 in the Master of Public Administration program at
Brigham Young University.
Details
Package: RcmdrPlugin.MPAStats
Type: Package
Version: 1.2.2
Date: 2018-05-16
License: GPL (>2)
The plug-in adds an additional top-level menu named MPA Statistics to
the R Commander interface, with the following submenus:
Descriptive statistics, Single-sample statistics,
Paired value testing, Bivariate analysis (with additional submenus
that divide statistical tests by the level of measurement of the dependent and
independent variables), and Multivariate analysis. Additionally, there is
a function to calculate logistic regression factor change coefficients (e^b) at
Models -> Factor change coefficients.
Author(s)
Andrew Heiss, Richard Payne, Christa Schank, Jessica Reese
Maintainer: Andrew Heiss <andrew@andrewheiss.com>
andrewheiss/RcmdrPlugin.MPAStats documentation built on May 10, 2019, 10:31 a.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
This package provides an R Commander plugin that offers a unified menu of new and pre-existing statistical functions related to public management and policy analysis statistics. Functions and menus have been renamed according to the usage in PMGT 630 in the Master of Public Administration program at Brigham Young University.
Details
| Package: | RcmdrPlugin.MPAStats |
| Type: | Package |
| Version: | 1.2.2 |
| Date: | 2018-05-16 |
| License: | GPL (>2) |
The plug-in adds an additional top-level menu named MPA Statistics to the R Commander interface, with the following submenus: Descriptive statistics, Single-sample statistics, Paired value testing, Bivariate analysis (with additional submenus that divide statistical tests by the level of measurement of the dependent and independent variables), and Multivariate analysis. Additionally, there is a function to calculate logistic regression factor change coefficients (e^b) at Models -> Factor change coefficients.
Author(s)
Andrew Heiss, Richard Payne, Christa Schank, Jessica Reese
Maintainer: Andrew Heiss <andrew@andrewheiss.com>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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