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A Function That Writes, Saves, and Exports Syntax for Fitting Dyadic Exploratory Factor Analysis (DEFA) Models

Source: R/scriptDyEFA.R
scriptDyEFA.Rd

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for specifying a dyadic EFA model of a given number of exploratory factors.

Usage

scriptDyEFA(
  dvn,
  nFactor = 1,
  constr_dy_meas = "none",
  writeTo = NULL,
  fileName = NULL
)

Arguments

dvn

input dvn list from scrapeVarCross

nFactor

numeric argument for number of exploratory factors to extract. Defaults to 1. Note that higher values may cause estimation problems as solution becomes over-factored and/or in the presence of insufficient data.

constr_dy_meas

input character vector detailing which measurement model parameters to constrain across dyad members. Default is "none" but user can specify "loadings" and/or "residuals", to fit an exploratory model with loadings and/or residuals constrained across partners

writeTo

A character string specifying a directory path to where the output file(s) should be saved. If set to ".", the file(s) will be written to the current working directory. The default is NULL, and examples use a temporary directory created by tempdir(). When dealing with tabular output, writeTo is only relevant if gtTab = TRUE.

fileName

A character string specifying a desired base name for the output file. The default is NULL. The specified name will be automatically appended with the appropriate file extension (e.g., .txt for lavaan scripts, .rtf for tabular output when gtTab = TRUE, or other extensions as appropriate for the output type). If a file with the same name already exists in the user's chosen directory, it will be overwritten.

Value

character object of lavaan script that can be passed immediately to lavaan functions

See also

scrapeVarCross which this function relies on

Other multi-construct script-writing functions: scriptCFA()

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2")
#> 
#> ── Variable Scraping Summary ──
#> 
#> ✔ Successfully scraped 1 latent variable: sat.g
#> ℹ sat.g: 5 indicators for P1 (1), 5 indicators for P2 (2)
#> ℹ Total indicators: 10

sat.defa1.script <- scriptDyEFA(dvn, nFactor = 1,
writeTo = tempdir(), fileName = "DEFA_1fac")