descript {ltm} | R Documentation |
Computes descriptive statistics for dichotomous and polytomous response matrices.
descript(data, n.print = 10, chi.squared = TRUE, B = 1000)
data |
a matrix or a data.frame containing the manifest variables as columns. |
n.print |
numeric indicating the number of pairwise associations with the highest p-values to be printed. |
chi.squared |
logical; if TRUE the chi-squared test for the pairwise associations between items
is performed. See Details for more info. |
B |
an integer specifying the number of replicates used in the Monte Carlo test (i.e., this is the B
argument of chisq.test() ). |
The following descriptive statistics are returned by descript()
:
Environment
are represented as 1, 2,
and 3).simulate.p.value
is turned to TRUE
in chisq.test()
,
using B
resamples.
descript()
returns an object of class descript
with components,
sample |
a numeric vector of length 2, with elements the number of items and the number of sample units. |
perc |
a numeric matrix containing the percentages of negative and positive responses for each item. If
data contains only dichotomous manifest variables the logit of the positive responses (i.e.,
second row) is also included. |
items |
a numeric matrix containing the frequencies for the total scores. |
pw.ass |
a matrix containing the p-values for the pairwise association between the items. |
n.print |
the value of the n.print argument. |
name |
the name of argument data . |
missin |
a numeric matrix containing the frequency and percentages of missing values for each item;
returned only if any NA 's exist in data . |
bisCorr |
a numeric vector containing sample estimates of the biserial correlation of dichotomous manifest variables with the total score. |
ExBisCorr |
a numeric vector containing sample estimates of the biserial correlation of dichotomous manifest variables with the total score, where the latter is computed by excluding the specific item. |
data |
a copy of the data . |
alpha |
a numeric matrix with one column containing the sample estimates of Cronbach's alpha, for all items and excluding each time one item. |
Dimitris Rizopoulos d.rizopoulos@erasmusmc.nl
## Descriptives for LSAT data: dsc <- descript(LSAT, 3) dsc plot(dsc, type = "b", lty = 1, pch = 1:5) legend("topleft", names(LSAT), pch = 1:5, col = 1:5, lty = 1, bty = "n")