%%COMPUTE%% {bruceR} R Documentation

## Multivariate computation.

### Description

Easily compute multivariate sum, mean, and other scores. Reverse scoring can also be easily implemented without saving extra variables. Alpha function uses a similar method to deal with reverse scoring.

Three ways to specify variables:

1. var + items: common and unique parts of variable names (suggested).

2. vars: a character vector of variable names (suggested).

3. varrange: starting and stopping positions of variables (NOT suggested).

### Usage

COUNT(data, var = NULL, items = NULL, vars = NULL, varrange = NULL, value = NA)

MODE(data, var = NULL, items = NULL, vars = NULL, varrange = NULL)

SUM(
data,
var = NULL,
items = NULL,
vars = NULL,
varrange = NULL,
rev = NULL,
range = likert,
likert = NULL,
na.rm = TRUE
)

.sum(
var = NULL,
items = NULL,
vars = NULL,
varrange = NULL,
rev = NULL,
range = likert,
likert = NULL,
na.rm = TRUE
)

MEAN(
data,
var = NULL,
items = NULL,
vars = NULL,
varrange = NULL,
rev = NULL,
range = likert,
likert = NULL,
na.rm = TRUE
)

.mean(
var = NULL,
items = NULL,
vars = NULL,
varrange = NULL,
rev = NULL,
range = likert,
likert = NULL,
na.rm = TRUE
)

STD(
data,
var = NULL,
items = NULL,
vars = NULL,
varrange = NULL,
rev = NULL,
range = likert,
likert = NULL,
na.rm = TRUE
)

CONSEC(
data,
var = NULL,
items = NULL,
vars = NULL,
varrange = NULL,
values = 0:9
)


### Arguments

 data Data frame. var [Option 1] Common part across variables: e.g., "RSES", "XX.{i}.pre" (if var string has any placeholder in braces {...}, then items will be pasted into the braces, see examples) items [Option 1] Unique part across variables: e.g., 1:10, c("a", "b", "c") vars [Option 2] Character vector specifying variables: e.g., c("X1", "X2", "X3", "X4", "X5") varrange [Option 3] Character string specifying positions ("start:stop") of variables: e.g., "A1:E5" value [Only for COUNT] The value to be counted. rev [Optional] Variables that need to be reversed. It can be (1) a character vector specifying the reverse-scoring variables (recommended), or (2) a numeric vector specifying the item number of reverse-scoring variables (not recommended). range, likert [Optional] Range of likert scale: e.g., 1:5, c(1, 5). If not provided, it will be automatically estimated from the given data (BUT you should use this carefully). na.rm Ignore missing values. Defaults to TRUE. values [Only for CONSEC] Values to be counted as consecutive identical values. Defaults to all numbers (0:9).

### Value

A vector of computed values.

### Functions

• COUNT(): Count a certain value across variables.

• MODE(): Compute mode across variables.

• SUM(): Compute sum across variables.

• .sum(): Tidy version of SUM, only can be used in add()/added()

• MEAN(): Compute mean across variables.

• .mean(): Tidy version of MEAN, only can be used in add()/added()

• STD(): Compute standard deviation across variables.

• CONSEC(): Compute consecutive identical digits across variables (especially useful in detecting careless responding).

### Examples

d = data.table(
x1 = 1:5,
x4 = c(2,2,5,4,5),
x3 = c(3,2,NA,NA,5),
x2 = c(4,4,NA,2,5),
x5 = c(5,4,1,4,5)
)
d
## I deliberately set this order to show you
## the difference between "vars" and "varrange".

## ====== Usage 1: data.table := ====== ##
d[, :=(
na = COUNT(d, "x", 1:5, value=NA),
n.2 = COUNT(d, "x", 1:5, value=2),
sum = SUM(d, "x", 1:5),
m1 = MEAN(d, "x", 1:5),
m2 = MEAN(d, vars=c("x1", "x4")),
m3 = MEAN(d, varrange="x1:x2", rev="x2", range=1:5),
cons1 = CONSEC(d, "x", 1:5),
cons2 = CONSEC(d, varrange="x1:x5")
)]
d

## ====== Usage 2: add() & added() ====== ##
data = as.data.table(psych::bfi)
gender = as.factor(gender)
education = as.factor(education)
E = .mean("E", 1:5, rev=c(1,2), range=1:6)
A = .mean("A", 1:5, rev=1, range=1:6)
C = .mean("C", 1:5, rev=c(4,5), range=1:6)
N = .mean("N", 1:5, range=1:6)
O = .mean("O", 1:5, rev=c(2,5), range=1:6)
}, drop=TRUE)
data

## ====== New Feature for var & items ====== ##
d = data.table(
XX.1.pre = 1:5,
XX.2.pre = 6:10,
XX.3.pre = 11:15
)
add(d, { XX.mean = .mean("XX.{i}.pre", 1:3) })
add(d, { XX.mean = .mean("XX.{items}.pre", 1:3) })  # the same
add(d, { XX.mean = .mean("XX.{#\$%^&}.pre", 1:3) })  # the same



[Package bruceR version 2023.9 Index]