rosettaDescr: descr (or descriptives) In rosetta: Parallel Use of Statistical Packages in Teaching

 descr R Documentation

descr (or descriptives)

Description

This function provides a number of descriptives about your data, similar to what SPSS's DESCRIPTIVES (often called with DESCR) does.

Usage

```descr(
x,
items = names(x),
varLabels = NULL,
mean = TRUE,
meanCI = TRUE,
median = TRUE,
mode = TRUE,
var = TRUE,
sd = TRUE,
se = FALSE,
min = TRUE,
max = TRUE,
q1 = FALSE,
q3 = FALSE,
IQR = FALSE,
skewness = TRUE,
kurtosis = TRUE,
dip = TRUE,
totalN = TRUE,
missingN = TRUE,
validN = TRUE,
histogram = FALSE,
boxplot = FALSE,
digits = 2,
errorOnFactor = FALSE,
convertFactor = FALSE,
maxModes = 1,
maxPlotCols = 4,
t = FALSE,
conf.level = 0.95,
quantileType = 2
)

x,
digits = attr(x, "digits"),
show = attr(x, "show"),
maxPlotCols = attr(x, "maxPlotCols"),
echoPartial = FALSE,
partialFile = NULL,
quiet = TRUE,
...
)

## S3 method for class 'rosettaDescr'
knit_print(
x,
digits = attr(x, "digits"),
show = attr(x, "show"),
maxPlotCols = attr(x, "maxPlotCols"),
echoPartial = FALSE,
partialFile = NULL,
quiet = TRUE,
...
)

## S3 method for class 'rosettaDescr'
print(
x,
digits = attr(x, "digits"),
show = attr(x, "show"),
maxPlotCols = attr(x, "maxPlotCols"),
forceKnitrOutput = FALSE,
...
)
```

Arguments

 `x` The object to print (i.e. as produced by `descr`). `items` Optionally, if `x` is a data frame, the variable names for which to produce the descriptives. `varLabels` Optionally, a named vector with 'pretty labels' to show for the variables. This has to be a vector of the same length as `items`, and if it is not a named vector with the names corresponding to the `items`, it has to be in the same order. `mean, meanCI, median, mode` Whether to compute the mean, its confidence interval, the median, and/or the mode (all logical, so `TRUE` or `FALSE`). `var, sd, se` Whether to compute the variance, standard deviation, and standard error (all logical, so `TRUE` or `FALSE`). `min, max, q1, q3, IQR` Whether to compute the minimum, maximum, first and third quartile, and inter-quartile range (all logical, so `TRUE` or `FALSE`). `skewness, kurtosis, dip` Whether to compute the skewness, kurtosis and dip test (all logical, so `TRUE` or `FALSE`). `totalN, missingN, validN` Whether to show the total sample size, the number of missing values, and the number of valid (i.e. non-missing) values (all logical, so `TRUE` or `FALSE`). `histogram, boxplot` Whether to show a histogram and/or boxplot `digits` The number of digits to round the results to when showing them. `errorOnFactor, convertFactor` If `errorOnFactor` is `TRUE`, factors throw an error. If not, if `convertFactor` is TRUE, they will be converted to numeric values using `as.numeric(as.character(x))`, and then the same output will be generated as for numeric variables. If `convertFactor` is false, the frequency table will be produced. `maxModes` Maximum number of modes to display: displays "multi" if more than this number of modes if found. `maxPlotCols` The maximum number of columns when plotting multiple histograms and/or boxplots. `t` Whether to transpose the dataframes when printing them to the screen (this is easier for users relying on screen readers). Note: this functionality has not yet been implemented! `headingLevel` The number of hashes to print in front of the headings when printing while knitting `conf.level` Confidence of confidence interval around the mean in the central tendency measures. `quantileType` The type of quantiles to be used to compute the interquartile range (IQR). See `quantile` for more information. `show` A vector of elements to show in the results, based on the arguments that activate/deactivate the descriptives (from `mean` to `validN`). `echoPartial` Whether to show the executed code in the R Markdown partial (`TRUE`) or not (`FALSE`). `partialFile` This can be used to specify a custom partial file. The file will have object `x` available. `quiet` Passed on to `knitr::knit()` whether it should b chatty (`FALSE`) or quiet (`TRUE`). `...` Any additional arguments are passed to the default print method by the print method, and to `rmdpartials::partial()` when knitting an RMarkdown partial. `forceKnitrOutput` Force knitr output.

Details

Note that R (of course) has many similar functions, such as `summary`, `psych::describe()` in the excellent psych::psych package.

The Hartigans' Dip Test may be unfamiliar to users; it is a measure of uni- vs. multimodality, computed by the `dip.test()` function from the `{diptest}` package from the. 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 that `dip.test()` function from `{diptest}`; also see Table 1 of Hartigan & Hartigan (1985) for an indication as to critical values).

Value

A list of dataframes with the requested values.

Author(s)

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com

References

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.

`summary`, [psych::describe()

Examples

```### Simplest example with default settings
descr(mtcars\$mpg);

### Also requesting a histogram and boxplot
descr(mtcars\$mpg, histogram=TRUE, boxplot=TRUE);

### To show the output as Rmd Partial in the viewer
rosetta::descr(
mtcars\$mpg
)
);

### Multiple variables, including one factor
rosetta::descr(
iris
)
);

```

rosetta documentation built on March 7, 2023, 7:40 p.m.