This function provides a number of descriptives about your data, similar to what SPSS's DESCRIPTIVES (often called with DESCR) does.
descr( x, digits = 4, errorOnFactor = FALSE, include = c("central tendency", "spread", "range", "distribution shape", "sample size"), maxModes = 1, t = FALSE, conf.level = 0.95, quantileType = 2 ) # S3 method for default descr( x, digits = 4, errorOnFactor = FALSE, include = c("central tendency", "spread", "range", "distribution shape", "sample size"), maxModes = 1, t = FALSE, conf.level = 0.95, quantileType = 2 ) # S3 method for descr print( x, digits = attr(x, "digits"), t = attr(x, "transpose"), row.names = FALSE, ... ) # S3 method for descr pander(x, headerPrefix = "", headerStyle = "**", ...) # S3 method for descr as.data.frame(x, row.names = NULL, optional = FALSE, ...) # S3 method for data.frame descr(x, ...)
The vector for which to return descriptives.
The number of digits to round the results to when showing them.
Whether to show an error when the vector is a factor, or just show the frequencies instead.
Which elements to include when showing the results.
Maximum number of modes to display: displays "multi" if more than this number of modes if found.
Whether to transpose the dataframes when printing them to the screen (this is easier for users relying on screen readers).
Confidence of confidence interval around the mean in the central tendency measures.
The type of quantiles to be used to compute the
interquartile range (IQR). See
quantile for more information.
Whether to show row names (
TRUE) or not (
Additional arguments are passed to the default
The prefix for the heading; can be used to insert
#) to create Markdown headings.
A string to insert before and after the heading (to make stuff bold or italic in Markdown).
Provided for compatibility with the default
method - see that help page for details.
A list of dataframes with the requested values.
The Hartigans' Dip Test may be unfamiliar to users; it is a measure of uni-
vs. multidimensionality, computed by
diptest::dip.test() from the
dip.test package. Depending on the sample size, values over
.025 can be seen as mildly indicative of multimodality, while values over
.05 probably warrant closer inspection (the p-value can be obtained using
diptest::dip.test(); also see Table 1 of Hartigan & Hartigan (1985) for
an indication as to critical values).
Hartigan, J. A.; Hartigan, P. M. The Dip Test of Unimodality. Ann. Statist. 13 (1985), no. 1, 70--84. doi:10.1214/aos/1176346577. https://projecteuclid.org/euclid.aos/1176346577.
descr(mtcars$mpg); #> ###### Descriptives for mtcars$mpg #> #> Describing the central tendency: #> mean median mode 95% CI mean #> 20.09 19.2 (multi) [17.92; 22.26] #> #> Describing the spread: #> var sd iqr se #> 36.32 6.027 7.45 1.065 #> #> Describing the range: #> min q1 q3 max #> 10.4 15.2 22.8 33.9 #> #> Describing the distribution shape: #> skewness kurtosis dip #> 0.6724 -0.02201 0.0569 #> #> Describing the sample size: #> total NA. valid #> 32 0 32 #>