Ian Fellows writes:
Being as you are an R user at the intersection of the social sciences and statistics, I thought some recent work I’ve done might be of interest to you. SPSS has long dominated the teaching and practice of statistics in the social sciences (at least among non-statisticians). I’ve created a new menu driven data analysis graphical user interface aimed at replacing SPSS (or at least that’s the long term lofty goal). It has just been released under GPL-2 on CRAN. Feel free to check out some screen shots in the online wiki manual (not yet complete).
I don’t know SPSS, but just yesterday someone told me that people can run R from SPSS and get a convenient menu system, so if this freeware would have the same capacity, that would be great. Here’s the description:
Deducer 0.1 has been released to CRAN
Deducer is designed to be a free, easy to use, alternative to proprietary software such as SPSS, JMP, and Minitab. It has a menu system to do common data manipulation and data analysis tasks, and an excel-like spreadsheet in which to view and edit data frames. The goal of the project is to two fold.
1. Provide an intuitive interface so that non-technical users
can learn and perform analyses without programming getting
in their way.
2. Increase the efficiency of expert R users when performing
common tasks by replacing hundreds of keystrokes with a few
mouse clicks. Also, as much as possible the GUI should not
get in their way if they just want to do some programming.
Deducer is integrated into the Windows RGui, and the cross-platform Java console JGR, and is also usable and accessible from the command line. Screen shots and examples can be viewed in the online wiki manual
Comments and questions are more than welcome. A discussion group has been created for any questions or recommendations.
1. Factor editor
2. Variable recoding
3. data sorting
4. data frame merging
5. transposing a data frame
3. Contingency tables
a. Nicely formatted tables with optional
ii. Expected counts
b. Statistical tests
ii. likelihood ratio
iii. fisher’s exact
iv. mantel haenszel
v. kendall’s tau
vi. spearman’s rho
viii. mid-p values for all exact/monte carlo tests
4. One sample tests
c. Histogram/box-plot summaries
5. Two sample tests
a. T-test (student and welch)
b. Permutation test
f. Jitter/box-plot group comparison
6. K-sample tests
a. Anova (usual and welch)
c. Jitter/boxplot comparison
a. Nicely formatted correlation matrices
e. Scatterplot paneled array
f. Circle plot
g. Full correlation matrix plot
8.Generalized Linear Models
a. Model preview
b. Intuitive model builder
c. diagnostic plots
d. Component residual and added variable plots
e. Anova (type II and III implementing LR, Wald and F tests)
f. Parameter summary tables and parameter correlations
g. Influence and colinearity diagnostics
h. Post-hoc tests and confidence intervals
with (or without) adjustments for multiple testing.
i. Custom linear hypothesis tests
j. Effect mean summaries (with confidence intervals),
k. Exports: Residuals, Standardized residuals, Studentized
residuals, Predicted Values (linear and link), Cooks
distance, DFBETA, DFFITS, hat values, and Cov Ratio
l. Observation weights and subseting
9. Logistic Regression
a. All GLM features
b. ROC Plot
10. Linear Model
a. All GLM features
b. Heteroskedastic robust tests
I’m not thrilled with how focused this all is on p-values, but I guess that doesn’t really matter. Once more capabilities are added, it’s fine that this other stuff is out there. I hope this catches on. And I hope they can set it up so it can run bayesglm(), lmer()/glmer(), and also I recommend that they set the default summaries from regressions using the display() rather than summarize() functions.
And does it make graphs? That’s key, no?