SimplePsych (Beta)

The simplePsych package provides simplified execution of common statistical analyses in psychology, with additional but important statistics and output. SimplePsych packages provide effect sizes, confidence intervals, simple and main effects tests, plots, and bootstrapping procedures (regression), all in one function. The package also includes the option to produce output in easy to view HTML, with APA formatted tables.

Latest development build

You can view the latest development build on Github. However, be advised that the package is still in development and bugs may exist. If you encounter any issues or bugs, please let me know either by email or on Github. If you would like to install the package, you can do so using the devtools package.

Install commands

To install the latest development build enter the following commands into the R console:

    
    install("devtools")
    library("devtools")
    install_github('matthew-quesnel/simplePsych')
    
    

The current beta version of the package includes the functions:

APAhtmlTable():	Prints the output of data frames and most R functions in an APA formatted html table. The function also allows you to manually specify header rows and set column spans for each header cell to produce more complex APA formatted html tables. Open the html file in your browser and then cut and paste to word and you have beautiful APA formatted tables with data drawn directly from your analyses.
cormatrix():	Creates a correlation table with options to set the type of correlation coefficient, what is displayed (e.g., degrees of freedeom, significance level, confidence interval) and to print output as an APA formatted html table.
frequencies():	Creates a frequency table and includes the option to output a histogram.
regression():	Conduct mutiple linear regression and model comparisons. It includes tests and plots for assessing model assumptions, regression output with effect sizes, bootstrapping procedures to produce 95% confidence intervals for the regression estimates and simple slope tests.
uniANOVA():	Conduct univariate analysis of (co)variance (ANOVA/ANCOVA). It includes options to print descriptives, tests and plots of model assumptions, estimated marginal means, main and simple effects tests, and APA formatted bar plots.