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A Variable Name-Scraping and Indexing Function for cross-sectional data

Source: R/scrapeVarCross.R
scrapeVarCross.Rd

This function scrapes the names of indicator variables in a wide-format data set used for dyadic analyses of two latent variables (LV; X and Y), and indexes which indicators correspond to which partner, for which LV. It is used primarily to guide the syntax-writing of the other dySEM functions.

Usage

scrapeVarCross(
  dat,
  x_order = "spi",
  x_stem,
  x_delim1 = NULL,
  x_delim2 = NULL,
  x_item_num = "\\d+",
  distinguish_1 = "1",
  distinguish_2 = "2",
  y_order = NULL,
  y_stem = NULL,
  y_delim1 = NULL,
  y_delim2 = NULL,
  y_item_num = "\\d+",
  covs_order = NULL,
  covs_stem = NULL,
  covs_delim1 = NULL,
  covs_delim2 = NULL
)

Arguments

dat

input data frame of indicators of a particular LV

x_order

input character for order of (S)tem, (P)artner number, and (I)tem number when creating variable names. Defaults to "spi" (Qualtrics-friendly)

x_stem

input character stem of indicator variables for LV X

x_delim1

optional character to separate stem from partner number (spi) or item number (sip)

x_delim2

optional character to separate stem/partner number (spi) or stem/item number (sip) from from final element of variable name

x_item_num

defaults to scrape all items that match the stem with any digits that follow. Will be updated to allow particular range of values, to make more sub-scale friendly.

distinguish_1

input character used as the identifier for the first partner

distinguish_2

input character used as the identifier for the first partner

y_order

optional character for order of (S)tem, (P)artner number, and (I)tem number when creating variable names. Defaults to "spi" (Qualtrics-friendly). This and other Y-arguments only necessary if there is a latent Y variable to model

y_stem

optional input character stem of indicator variables for LV X

y_delim1

optional character to separate stem from partner number (spi) or item number (sip)

y_delim2

optional character to separate stem/partner number (spi) or stem/item number (sip) from from final element of variable name

y_item_num

defaults to scrape all items that match the stem with any digits that follow. Will be updated to allow particular range of values, to make more sub-scale friendly.

covs_order

optional character for order of (S)tem, (P)artner number, and (I)tem number for any covariate(s). Defaults to NULL. This and other covariate arguments only necessary if there are covariates to be scripted in your model(s).

covs_stem

optional input character stem(s) of indicator variables for covariate(s). Can accept a single stem (e.g., "anx"), or a vector of stems (e.g., c("anx", "dep")). Defaults to NULL.

covs_delim1

optional character to separate stem from partner number (spi) or item number (sip) for covariate(s). Defaults to NULL.

covs_delim2

optional character to separate stem/partner number (spi) or stem/item number (sip) from

Value

a list, referred in short-hand as a "dvn" (dyad variable names list) containing variable names for p1, p2, # of items per LV, characters distinguishing partners, and total number of indicators

Examples

dvnx <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2")
dvnxy <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2",
y_order="spi", y_stem="com", y_delim1 = ".", y_delim2="_")