Description Usage Arguments Details Value Methods (by generic) See Also Examples
Constructs S3 class for pensieve.
1 2 3 4 5 6 7 | psOpenSorts(open_sorts)
## S3 method for class 'psLogicalOpenSorts'
tidy(x)
## S3 method for class 'psLogicalOpenSorts'
autoplot(object, by = "item")
|
open_sorts |
A list of matrices, one for each participant.
Matrices must be |
x |
a psOpenSorts, created by |
object |
a psLogicalOpenSorts, created by |
by |
a character string, must be one of:
|
Open sorting categorizations cannot be compared between participants, because each participants defines her own dimensions.
The canonical representation of open sorting data is therefore a list of matrices, one for each participant.
Every individual matrix is a psOpenSort()
object, and together, they form a psOpenSorts()
list.
The rows in these matrices are the items, the columns are the dimensions, and cells are the assignment.
Optional dimension descriptions are included as attributes of the matrices.
Object of class psOpenSorts
.
tidy
: Summarize list of open sorts
autoplot
: plots Summary
Other S3 classes from pensieve
:
correlate()
,
extract()
,
psClosedSorts()
,
psGrid()
,
psItemContent()
,
psOpenSort()
,
psPeople()
,
score()
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | # create single open sort ====
# Lisas open sort, unnamed descriptions (matched by index)
losort <- matrix(
data = c(TRUE, FALSE, FALSE, FALSE, TRUE, FALSE),
nrow = 3,
dimnames = list(items = c("cat", "dog", "cow")))
descriptions <- c(
"a pet which largely takes care of itself",
NA # dimension is assigned, but not described (not a problem)
)
lisa <- psOpenSort(osort = losort, descriptions = descriptions)
# Peters open sort, named descriptions (*also* only matched by index)
losort <- matrix(
data = c(TRUE, TRUE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE),
nrow = 3,
dimnames = list(
items = c("cat", "dog", "cow"),
categories = c("in_homes", "quiet", "herbivore")
))
descriptions <- c(
in_homes = "Animal found in peoples homes.",
quiet = "Does not make a lot of noise.",
herbivore = "Eats plants.") # defined, but never TRUE (not a problem)
peter <- psOpenSort(osort = losort, descriptions = descriptions)
# coercion methods
peter_m <- as_psOpenSort(osort = as.matrix(x = losort), descriptions = descriptions)
peter_df <- as_psOpenSort(osort = as.data.frame(x = losort), descriptions = descriptions)
# Rebeccas open sort, without any descriptions provided
losort <- matrix(
data = c(FALSE, FALSE, TRUE, TRUE, TRUE, FALSE),
nrow = 3,
dimnames = list(handles = c("cat", "dog", "cow")))
rebecca <- psOpenSort(osort = losort, descriptions = NULL)
# Ira open sort, with some problems
losort <- matrix(
data = c(
FALSE, FALSE, FALSE, # this is dropped, b/c there is just no valuable information here,
TRUE, TRUE, TRUE, # same problem; no variance
FALSE, FALSE, FALSE,
# also no variance, but there *is* a corresponding description,
# so we're setting column to NA and keeping the description
NA, TRUE, FALSE), # you can also have *actual* NAs
nrow = 3,
byrow = FALSE,
dimnames = list(handles = c("cat", "dog", "cow"))
)
descriptions <- c(NA, NA, "mammals", NA)
ira <- suppressWarnings(as_psOpenSort(osort = losort, descriptions = descriptions))
# this gives appropriate warning messages
# psOpenSort() would error out; only coercion method will attempt fix
# ordinally and intervally scaled sorts are also possible, but currently unsupported
tyler <- matrix(
data = as.integer(c(1, 2, 2, 1)),
nrow = 2,
)
tyler <- psOpenSort(
osort = tyler,
scale = "ordinal") # defaults to implicit class of base type
roberta <- matrix(
data = c(2.2, 4.3, -2.8, 0),
nrow = 2
)
roberta <- psOpenSort(osort = roberta)
# Creation ====
# you can combine individual sorts into a list ====
los <- psOpenSorts(open_sorts = list(lisa = lisa, peter = peter, rebecca = rebecca))
# or create psOpenSorts from a more convenient input ====
# recreate messy format from canonical form (don't do this at home)
ass <- pensieve:::make_messy(open_sorts = los)$ass
desc <- pensieve:::make_messy(open_sorts = los)$desc
# these two can be conveniently entered in a spreadsheet program
ass
desc
los_from_messy <- as_psLogicalOpenSorts(
logical_open_sorts = ass,
descriptions_messy = desc,
keep_LETTERS = FALSE)
ggplot2::autoplot(object = los)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.