qdap (version 0.2.5)

cm_distance: Distance Matrix Between Codes

Description

Generate distance measures to ascertain a mean distance measure between codes.

Usage

cm_distance(dataframe, time.var = NULL, parallel = FALSE,
    code.var = "code", causal = FALSE, start.var = "start",
    end.var = "end", mean.digits = 2, sd.digits = 2,
    stan.digits = 2)

Arguments

dataframe

A data frame from the cm_x2long family (cm_range2long; cm_df2long; cm_time2long).

time.var

An optional variable to split the dataframe by (if you have data that is by various times this must be supplied).

parallel

logical. If TRUE runs the cm_distance on multiple cores. This is effective with larger data sets but may actually be slower with smaller data sets.

code.var

The name of the code variable column. Defaults to "codes" as out putted by x2long family.

causal

logical. If TRUE measures the distance between x and y given that x must proceed y.

start.var

The name of the start variable column. Defaults to "start" as out putted by x2long family.

end.var

The name of the end variable column. Defaults to "end" as out putted by x2long family.

mean.digits

The number of digits to be displayed in the mean matrix.

sd.digits

The number of digits to be displayed in the sd (standard deviation) matrix.

stan.digits

The number of digits to use in the standardized mean difference matrix.

Value

• An object of the class cm.dist. This is a list of n lists with the following components per each list (time.var):
• mean
  A distance matrix of average distances between codes
• sd
  A matrix of standard deviations of distances between codes
• n
  A matrix of counts of distances between codes
• combined
  A matrix of combined mean, sd and n of distances between codes
• standardized
  A matrix of standardized values of distances between codes. The closer a value is to zero the closer two codes relate.

Examples

foo <- list(
    AA = qcv(terms="02:03, 05"),
    BB = qcv(terms="1:2, 3:10"),
    CC = qcv(terms="1:9, 100:150")
)

foo2  <- list(
    AA = qcv(terms="40"),
    BB = qcv(terms="50:90"),
    CC = qcv(terms="60:90, 100:120, 150"),
    DD = qcv(terms="")
)

(dat <- cm_range2long(foo, foo2, v.name = "time"))
(out <- cm_distance(dat, time.var = "time", causal=TRUE))
names(out)
names(out$foo2)
out$foo2
#========================================
x <- list(
    transcript_time_span = qcv(00:00 - 1:12:00),
    A = qcv(terms = "2.40:3.00, 6.32:7.00, 9.00,
        10.00:11.00, 59.56"),
    B = qcv(terms = "3.01:3.02, 5.01,  19.00, 1.12.00:1.19.01"),
    C = qcv(terms = "2.40:3.00, 5.01, 6.32:7.00, 9.00, 17.01")
)
(dat <- cm_time2long(x))
gantt_wrap(dat, "code", border.color = "black", border.size = 5,
    sig.dig.line.freq = -2)
(a <- cm_distance(dat))
names(a)
names(a$dat)
a$dat