Title:	Dyadic Structural Equation Modeling
Version:	1.1.1
Description:	Scripting of structural equation models via 'lavaan' for Dyadic Data Analysis, and helper functions for supplemental calculations, tabling, and model visualization. Current models supported include Dyadic Confirmatory Factor Analysis, the Actor–Partner Interdependence Model (observed and latent), the Common Fate Model (observed and latent), Mutual Influence Model (latent), and the Bifactor Dyadic Model (latent).
License:	GPL-3
Encoding:	UTF-8
RoxygenNote:	7.3.2
URL:	https://github.com/jsakaluk/dySEM, https://jsakaluk.github.io/dySEM/
BugReports:	https://github.com/jsakaluk/dySEM/issues
Imports:	dplyr, gt, lavaan, lifecycle, magrittr, rlang, semPlot, stringr, tibble
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
VignetteBuilder:	knitr
LazyData:	true
Depends:	R (≥ 2.10)
Config/testthat/edition:	3
NeedsCompilation:	no
Packaged:	2025-01-07 21:49:08 UTC; johnsakaluk
Author:	John Sakaluk [aut, cre, cph], Omar Camanto [aut], Robyn Kilshaw [ctb], Alexandra Fisher [ctb]
Maintainer:	John Sakaluk <jksakaluk@gmail.com>
Repository:	CRAN
Date/Publication:	2025-01-07 22:20:02 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Value

No return value

Relationship quality and sexual satisfaction of 121 couples

Description

A dataset containing 9 observed indicators of relationship quality (PRQC) and 5 observed indicators of sexual satisfaction from 121 couples in the DRES (Daily Relationship Experiences Study; Raposo, Impett, & Muise, in press)

Usage

data(DRES)

Format

A data frame with 121 rows and 28 variables:

PRQC_1.1

PRQC item 1 for partner 1

PRQC_2.1

PRQC item 2 for partner 1

PRQC_3.1

PRQC item 3 for partner 1

PRQC_4.1

PRQC item 4 for partner 1

PRQC_5.1

PRQC item 5 for partner 1

PRQC_6.1

PRQC item 6 for partner 1

PRQC_7.1

PRQC item 7 for partner 1

PRQC_8.1

PRQC item 8 for partner 1

PRQC_9.1

PRQC item 9 for partner 1

PRQC_1.2

PRQC item 1 for partner 2

PRQC_2.2

PRQC item 2 for partner 2

PRQC_3.2

PRQC item 3 for partner 2

PRQC_4.2

PRQC item 4 for partner 2

PRQC_5.2

PRQC item 5 for partner 2

PRQC_6.2

PRQC item 6 for partner 2

PRQC_7.2

PRQC item 7 for partner 2

PRQC_8.2

PRQC item 8 for partner 2

PRQC_9.2

PRQC item 9 for partner 2

sexsat1.1

sexual satisfaction item 1 for partner 1

sexsat2.1

sexual satisfaction item 2 for partner 1

sexsat3.1

sexual satisfaction item 3 for partner 1

sexsat4.1

sexual satisfaction item 4 for partner 1

sexsat5.1

sexual satisfaction item 5 for partner 1

sexsat1.2

sexual satisfaction item 1 for partner 2

sexsat2.2

sexual satisfaction item 2 for partner 2

sexsat3.2

sexual satisfaction item 3 for partner 2

sexsat4.2

sexual satisfaction item 4 for partner 2

sexsat5.2

sexual satisfaction item 5 for partner 2

References

Raposo, S., Impett, E. A., & Muise, A. (2020). Avoidantly Attached Individuals Are More Exchange‐Oriented and Less Communal in the Bedroom. Archives of Sexual Behavior, 49, 2863–2881. https://doi.org/10.1007/s10508-020-01813-9

Ratings of relational satisfaction and commitment from 282 (M)ixed-sex couples

Description

A data set containing 5 ratings of satisfaction and 5 ratings of commitment for each member of a mixed-sex romantic dyad. Measured using the Investment Model Scale subscales (Rusbult, Martz, & Agnew, 1998). Data are from Sakaluk, Fisher, and Kilshaw's (2021) study of dyadic invariance. Variable names have been re-coded to follow a stem-item-partner ("sip") order, with a delimiter ("_") between the item number and partner distinguishing character.

Usage

data(commitmentM)

Format

A data frame with 282 rows and 20 variables:

sat.g1_f

Satisfaction item 1 for female partner

sat.g2_f

Satisfaction item 2 for female partner

sat.g3_f

Satisfaction item 3 for female partner

sat.g4_f

Satisfaction item 4 for female partner

sat.g5_f

Satisfaction item 5 for female partner

com1_f

Commitment items item 1 for female partner

com2_f

Commitment items item 2 for female partner

com3_f

Commitment items item 3 for female partner

com4_f

Commitment items item 4 for female partner

com5_f

Commitment items item 5 for female partner

sat.g1_m

Satisfaction item 1 for male partner

sat.g2_m

Satisfaction item 2 for male partner

sat.g3_m

Satisfaction item 3 for male partner

sat.g4_m

Satisfaction item 4 for male partner

sat.g5_m

Satisfaction item 5 for male partner

com1_m

Commitment items item 1 for male partner

com2_m

Commitment items item 2 for male partner

com3_m

Commitment items item 3 for male partner

com4_m

Commitment items item 4 for male partner

com5_m

Commitment items item 5 for male partner

References

Sakaluk, J. K., Fisher, A. N., & Kilshaw, R. E.(2021). Dyadic measurement invariance and its importance for replicability in romantic relationship research. Personal Relationships, 28(1), 190-226. .

Ratings of relational satisfaction and commitment from 282 (Q)ueer couples

Description

A data set containing 5 ratings of satisfaction and 5 ratings of commitment for each member of a dyad in which one or more members identify as LGBTQ+. Measured using the Investment Model Scale subscales (Rusbult, Martz, & Agnew, 1998). Data are from Sakaluk, Fisher, and Kilshaw (2021). Variable names follow a stem-partner-item ("spi") order, with a delimiter (".") between the stem and distinguishing partner character, and another delimiter ("_") between the distinguishing partner character and item number.

Usage

data(commitmentQ)

Format

A data frame with 118 rows and 20 variables:

sat.g.1_1

Satisfaction item 1 for partner1

sat.g.1_2

Satisfaction item 2 for partner1

sat.g.1_3

Satisfaction item 3 for partner1

sat.g.1_4

Satisfaction item 4 for partner1

sat.g.1_5

Satisfaction item 5 for partner1

com.1_1

Commitment items item 1 for partner1

com.1_2

Commitment items item 2 for partner1

com.1_3

Commitment items item 3 for partner1

com.1_4

Commitment items item 4 for partner1

com.1_5

Commitment items item 5 for partner1

sat.g.2_1

Satisfaction item 1 for partner 2

sat.g.2_2

Satisfaction item 2 for partner 2

sat.g.2_3

Satisfaction item 3 for partner 2

sat.g.2_4

Satisfaction item 4 for partner 2

sat.g.2_5

Satisfaction item 5 for partner 2

com.2_1

Commitment items item 1 for partner 2

com.2_2

Commitment items item 2 for partner 2

com.2_3

Commitment items item 3 for partner 2

com.2_4

Commitment items item 4 for partner 2

com.2_5

Commitment items item 5 for partner 2

References

Sakaluk, J. K., Fisher, A. N., & Kilshaw, R. E.(2021). Dyadic measurement invariance and its importance for replicability in romantic relationship research. Personal Relationships, 28(1), 190-226. .#'

A function that performs a score test for relaxing each invariance equality constraint between partners in a given dyadic SEM model.

Description

A function that performs a score test for relaxing each invariance equality constraint between partners in a given dyadic SEM model.

Usage

getConstraintTests(constrainFit, filterSig = FALSE)

Arguments

Value

a data frame with rows of equality constraints (now with readable param labels) and test statistic, df, and p for whether constraint worsens model fit

Examples

dvn <- scrapeVarCross(dat = commitmentM, x_order = "sip", x_stem = "sat.g",
x_delim2="_", distinguish_1="f", distinguish_2="m")

sat.resids.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts", "residuals"),
constr_dy_struct = "none")

sat.resids.mod <- lavaan::cfa(sat.resids.script, data = commitmentM, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

getConstraintTests(sat.resids.mod)

A Function Calculates Omega Total Coefficients from a Dyadic CFA

Description

This function takes the model from fitted scriptCFA() scripts and returns omega total coefficients for each dyad member, adapted following Formula 2 in McNeish (2018).

Usage

getDyReliability(dvn, fit)

Arguments

Value

a tibble/data frame with calculated omega total coefficients for dyad Member 1 and Member 2

See Also

Other supplemental model calculators: getDydmacs(), getIndistFit()

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2")
sat.indist.script <-  scriptCFA(dvn, lvname = "Sat")
sat.indist.mod <- lavaan::cfa(sat.indist.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)
getDyReliability(dvn, sat.indist.mod)

Calculates dmacs difference in expected indicator scores for between dyad members

Description

Calculates dmacs difference in expected indicator scores for between dyad members

Usage

getDydmacs(dat, dvn, fit, nodewidth = 0.01, lowerLV = -5, upperLV = 5)

Arguments

Value

vector of d_macs values

See Also

Other supplemental model calculators: getDyReliability(), getIndistFit()

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2")
sat.config.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = "none",
constr_dy_struct = "none")

sat.config.mod <- lavaan::cfa(sat.config.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)
getDydmacs(commitmentQ, dvn, sat.config.mod)

A Function that Computes Corrected Fit Indexes According to the ISAT and INULL Models of Olsen & Kenny (2006)

Description

This function takes the outputted model fit using scriptCFA() with model = "indist", as well as scriptISAT(), and scriptINULL() and computes corrected model fit indexes according to the approach outlined by Olsen & Kenny (2006)

Usage

getIndistFit(indmodel, isatmod, inullmod)

Arguments

Value

A data frame of the original and corrected chi sq, df, p, rmsea, and tli

See Also

Other supplemental model calculators: getDyReliability(), getDydmacs()

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2")

sat.indist.script <-  scriptCFA(dvn, lvname = "Sat")
sat.indist.mod <- lavaan::cfa(sat.indist.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

sat.isat.script <- scriptISAT(dvn, lvxname = "Sat")
sat.isat.mod <- lavaan::cfa(sat.isat.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = FALSE)

sat.inull.script <- scriptINULL(dvn, lvxname = "Sat")
sat.inull.mod <- lavaan::cfa(sat.inull.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = FALSE)

getIndistFit(sat.indist.mod, sat.isat.mod, sat.inull.mod)

Compare model fit of nested dyadic invariance models in order from most parsimonious (residual) to least parsimonious (configural)

Description

Compare model fit of nested dyadic invariance models in order from most parsimonious (residual) to least parsimonious (configural)

Usage

getInvarCompTable(mods)

Arguments

Value

a data frame of model fit statistics for each model, as well as the difference in fit statistics between each model and the previous model

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi",
x_stem = "sat.g", x_delim1 = ".", x_delim2="_", distinguish_1="1", distinguish_2="2")

sat.residual.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts", "residuals"), constr_dy_struct = "none")

sat.intercept.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts"), constr_dy_struct = "none")

sat.loading.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings"), constr_dy_struct = "none")

sat.config.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = "none", constr_dy_struct = "none")

sat.residual.fit <- lavaan::cfa(sat.residual.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.intercept.fit <- lavaan::cfa(sat.intercept.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.loading.fit <- lavaan::cfa(sat.loading.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.config.fit <- lavaan::cfa(sat.config.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

mods <- list(sat.residual.fit, sat.intercept.fit, sat.loading.fit, sat.config.fit)

getInvarCompTable(mods)

Evaluate Invariance Equality Constraints in a specified Dyadic Invariance Model

Description

outputConstraintTab() is used to perform a score test for relaxing each invariance equality constraint between partners in a given dyadic SEM model.

Usage

outputConstraintTab(
  constrainFit,
  filterSig = FALSE,
  gtTab = FALSE,
  writeTo = NULL,
  fileName = NULL
)

Arguments

Details

• If gtTab = TRUE and writeTo is specified, then output will simultaneously be saved as a .rtf file to the user's specified directory.

• If output file is successfully saved, a confirmation message will be printed to the console.

• If a file with the same name already exists in the user's chosen directory, it will be overwritten.

Value

A tibble::tibble() if gtTab = FALSE (default), or gt::gt() object if gtTab = TRUE, with rows of equality constraints (now with readable param labels) and test statistic, df, and p for whether constraint worsens model fit.

Examples

dvn <- scrapeVarCross(dat = commitmentM, x_order = "sip", x_stem = "sat.g",
x_delim2="_", distinguish_1="f", distinguish_2="m")

sat.resids.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts", "residuals"),
constr_dy_struct = "none")

sat.resids.mod <- lavaan::cfa(sat.resids.script, data = commitmentM, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

outputConstraintTab(sat.resids.mod, filterSig = FALSE,
gtTab = TRUE, writeTo = tempdir(), fileName = "dCFA_Residual")

Compare Model Fit of Nested Dyadic Invariance Models

Description

outputInvarCompTab() is used to compare the model fit of nested dyadic invariance models in order from most parsimonious (residual) to least parsimonious (configural)

Usage

outputInvarCompTab(mods, gtTab = FALSE, writeTo = NULL, fileName = NULL)

Arguments

Details

• If gtTab = TRUE and writeTo is specified, then output will simultaneously be saved as a .rtf file to the user's specified directory.

• If output file is successfully saved, a confirmation message will be printed to the console.

• If a file with the same name already exists in the user's chosen directory, it will be overwritten.

Value

A tibble::tibble() if gtTab = FALSE (default), or gt::gt() object if gtTab = TRUE, of model fit statistics for each model, as well as the difference in fit statistics between each model and the previous model

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi",
x_stem = "sat.g", x_delim1 = ".", x_delim2="_", distinguish_1="1", distinguish_2="2")

sat.residual.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts", "residuals"), constr_dy_struct = "none")

sat.intercept.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts"), constr_dy_struct = "none")

sat.loading.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings"), constr_dy_struct = "none")

sat.config.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = "none", constr_dy_struct = "none")

sat.residual.fit <- lavaan::cfa(sat.residual.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.intercept.fit <- lavaan::cfa(sat.intercept.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.loading.fit <- lavaan::cfa(sat.loading.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.config.fit <- lavaan::cfa(sat.config.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

mods <- list(sat.residual.fit, sat.intercept.fit, sat.loading.fit, sat.config.fit)

outputInvarCompTab(mods,
gtTab = TRUE, writeTo = tempdir(), fileName = "dCFA_Invar")

A Function That Exports Tables and/or SEM Diagrams based on dySEM models

Description

This function takes the model from fitted dySEM() scripts and exports table(s) and/or a path diagram figure of expected output.

Usage

outputModel(
  dvn,
  model = NULL,
  fit,
  table = TRUE,
  tabletype = NULL,
  figure = TRUE,
  figtype = NULL,
  writeTo = NULL,
  fileName = NULL
)

Arguments

Details

If a file with the same name already exists in the user's chosen directory, it will be overwritten.

Value

Ignore console (prints unnecessary semPlot::semPaths details). More importantly, prints word files for the table(s) and/or figure, outputted to the users working directory

Examples

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

sat.config.script <- scriptCFA(dvnx, lvname = "Sat", constr_dy_meas = "none",
constr_dy_struct = "none")

sat.config.mod <- lavaan::cfa(sat.config.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

outputModel(dvnx, model = "cfa", fit = sat.config.mod, table = TRUE,
tabletype = "measurement", figure = "TRUE", figtype = "standardized",
writeTo = tempdir(), fileName = "dCFA_configural")
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="_")

apim.indist.script <-  scriptAPIM(dvnxy, lvxname = "Sat", lvyname = "Com", est_k = TRUE)

apim.indist.mod <- lavaan::cfa(apim.indist.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

outputModel(dvnxy, model = "apim", fit = apim.indist.mod, table = TRUE,
tabletype = "measurement", figure = "TRUE", figtype = "standardized",
writeTo = tempdir(), fileName = "APIM_indist")

A function That Exports SEM diagrams based on dySEM models

Description

This function takes the model from fitted dySEM scripts and exports .png path diagram figures of expected output.

Usage

outputParamFig(fit, figtype = NULL, writeTo = NULL, fileName = NULL)

Arguments

Details

• The function uses semPlot::semPaths() to create a qgraph object of the desired SEM path diagram.

• After execution, a semPlot::semPaths() message will be printed to the console confirming the directory path of the saved output file.

• If a file with the same name already exists in the user's chosen directory, it will be overwritten.

Value

A qgraph object of the desired SEM path diagram, which is simultaneously exported as a .png file to the specified directory.

Examples

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

sat.config.script <- scriptCFA(dvnx, lvname = "Sat", constr_dy_meas = "none",
constr_dy_struct = "none")

sat.config.mod <- lavaan::cfa(sat.config.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

outputParamFig(sat.config.mod, figtype = "standardized",
writeTo = tempdir(), fileName = "dCFA_configural")
 
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="_")

apim.indist.script <-  scriptAPIM(dvnxy, lvxname = "Sat", lvyname = "Com", est_k = TRUE)

apim.indist.mod <- lavaan::cfa(apim.indist.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

outputParamFig(apim.indist.mod, figtype = "standardized",
writeTo = tempdir(), fileName = "APIM_indist")

A Function That Exports Tables based on dySEM models

Description

This function takes the model from fitted dySEM scripts and creates tables of expected output and/or exports them as .rtfs.

Usage

outputParamTab(
  dvn,
  model = NULL,
  fit,
  tabletype = NULL,
  gtTab = FALSE,
  writeTo = NULL,
  fileName = NULL
)

Arguments

Details

• If gtTab = TRUE and writeTo is specified, then output will simultaneously be saved as a .rtf file to the user's specified directory.

• If output file(s) is(are) successfully saved, a confirmation message will be printed to the console.

• If a file with the same name already exists in the user's chosen directory, it will be overwritten.

Value

A tibble::tibble() if gtTab = FALSE (default), or gt::gt() object if gtTab = TRUE, of specified model parameter estimates and corresponding statistical tests.

Examples

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

sat.config.script <- scriptCFA(dvnx, lvname = "Sat", constr_dy_meas = "none",
constr_dy_struct = "none")

sat.config.mod <- lavaan::cfa(sat.config.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

outputParamTab(dvnx, model = "cfa", sat.config.mod, tabletype = "measurement",
writeTo = tempdir(), fileName = "dCFA_configural")

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="_")

apim.indist.script <-  scriptAPIM(dvnxy, lvxname = "Sat", lvyname = "Com", est_k = TRUE)

apim.indist.mod <- lavaan::cfa(apim.indist.script, data = commitmentQ, std.lv = FALSE,
auto.fix.first= FALSE, meanstructure = TRUE)

outputParamTab(dvnxy, model = "cfa", sat.config.mod, tabletype = "measurement",
writeTo = tempdir(), fileName = "APIM_indist")

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

Description

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

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="_")

A Function That Writes, Saves, and Exports Syntax for Fitting Latent Actor-Partner Interdependence Models (APIMs)

Description

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for specifying Actor-Partner Interdependence Models (APIMs). Users can also invoke configural, loading, and/or intercept invariant measurement models, and particular types of structural comparisons.

Usage

scriptAPIM(
  dvn,
  scaleset = "FF",
  lvxname,
  lvyname,
  constr_dy_x_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_x_struct = c("variances", "means"),
  constr_dy_y_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_y_struct = c("variances", "means"),
  constr_dy_xy_struct = c("actors", "partners"),
  model = lifecycle::deprecated(),
  equate = lifecycle::deprecated(),
  est_k = FALSE,
  writeTo = NULL,
  fileName = NULL
)

Arguments

Value

character object of lavaan script that can be passed immediately to lavaan functions. Users will receive message if structural comparisons are specified when the recommended level of invariance is not also specified. If user supplies dvn with containing X or Y variables, they are alerted to respecify the dvn object.

See Also

scrapeVarCross which this function relies on

Other script-writing functions: scriptBiDy(), scriptCFA(), scriptCFM(), scriptDyEFA(), scriptINULL(), scriptISAT(), scriptMIM()

Examples

dvn <- 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="_")
apim.script.indist <-  scriptAPIM(dvn, lvxname = "Sat", lvyname = "Com", est_k = TRUE,
writeTo = tempdir(),
fileName = "latAPIM_indist")

A Function That Writes, Saves, and Exports Syntax for Fitting Bifactor Dyadic (BiDy) models

Description

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for specifying dyadic configural, loading, and intercept invariant BiDy CFA (BiDy-C) or SEM (BiDy-S) Model. Currently only uses fixed-factor scale-setting

Usage

scriptBiDy(
  dvn,
  type = "CFA",
  lvxname,
  lvyname,
  constr_dy_x_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_x_struct = c("variances", "means"),
  constr_dy_y_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_y_struct = c("variances", "means"),
  constr_dy_xy_struct = c("actors"),
  model = lifecycle::deprecated(),
  equate = lifecycle::deprecated(),
  writeTo = NULL,
  fileName = NULL
)

Arguments

Value

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

See Also

Other script-writing functions: scriptAPIM(), scriptCFA(), scriptCFM(), scriptDyEFA(), scriptINULL(), scriptISAT(), scriptMIM()

Examples

dvn <- scrapeVarCross(DRES, x_order = "sip", x_stem = "sexsat",
x_delim2=".", distinguish_1="1", distinguish_2="2")

sexsat.bidyc.script <- scriptBiDy(dvn, lvxname = "SexSat", type = "CFA",
writeTo = tempdir(),
fileName = "BiDy_C")

dvn <- 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="_")

comsat.bidys.config.script <- scriptBiDy(dvn, lvxname = "Sat",
lvyname = "Com", type = "SEM",
writeTo = tempdir(),
fileName = "BiDy_S")

A Function That Writes, Saves, and Exports Syntax for Fitting Latent Dyadic Confirmatory Factor Analysis (CFA) Models

Description

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for specifying dyadic configural, loading, and intercept invariant measurement models for either a specified X or Y factor.

Usage

scriptCFA(
  dvn,
  scaleset = "FF",
  lvname = "X",
  constr_dy_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_struct = c("variances", "means"),
  model = lifecycle::deprecated(),
  writeTo = NULL,
  fileName = NULL
)

Arguments

Details

By default, many dySEM:: functions (including scriptCFA() default to a fixed-factor method of scale-setting, whereby the latent variance of a given factor is constrained to 1 for both partners in the configurally invariant #model, and then one of these variances is freely estimated in subsequent #models of the invariance testing sequence. We have selected this default for two reasons: (1) the selection of a marker-variable is usually arbitrary, yet can have a large influence on the estimation and testing of of structural parameters (see https://stats.stackexchange.com/questions/402133/in-cfa-does-it-matter-which-factor-loading-is-set-to-1/402732#402732); and (2) the selection of a non-invariant marker-variable can have disastrous down-stream consequences for the identification of non-invariant measurement parameters, following a the rejection of an omnibus #invariance constraint set (see Lee, Preacher, & Little, 2011).

Value

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

See Also

scrapeVarCross which this function relies on

Other script-writing functions: scriptAPIM(), scriptBiDy(), scriptCFM(), scriptDyEFA(), scriptINULL(), scriptISAT(), scriptMIM()

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2")

sat.indist.script <- scriptCFA(dvn, lvname = "Sat")

sat.lvars.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = "loadings",
constr_dy_struct = "variances")

sat.resids.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts", "residuals"),
constr_dy_struct = "none",
writeTo = tempdir(),
fileName = "dCFA_residual")

sat.ints.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts"),
constr_dy_struct = "none",
writeTo = tempdir(),
fileName = "dCFA_intercept")

sat.loads.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings"),
constr_dy_struct = "none",
writeTo = tempdir(),
fileName = "dCFA_loading")

sat.config.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = "none",
constr_dy_struct = "none",
writeTo = tempdir(),
fileName = "dCFA_configural")

A Function That Writes, Saves, and Exports Syntax for Fitting Latent Common Fate Models (CFMs)

Description

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for specifying Common Fate Models (CFMs). Users can also invoke configural, loading, and/or intercept invariant measurement models, and particular types of structural comparisons.

Usage

scriptCFM(
  dvn,
  scaleset = "FF",
  lvxname,
  lvyname,
  constr_dy_x_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_x_struct = c("variances", "means"),
  constr_dy_y_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_y_struct = c("variances", "means"),
  constr_dy_xy_struct = "none",
  model = lifecycle::deprecated(),
  writeTo = NULL,
  fileName = NULL
)

Arguments

Value

character object of lavaan script that can be passed immediately to lavaan functions. Users will receive message if structural comparisons are specified when the recommended level of invariance is not also specified. If user supplies dvn with containing X or Y variables, they are alerted to respecify the dvn object.

See Also

scrapeVarCross which this function relies on

Other script-writing functions: scriptAPIM(), scriptBiDy(), scriptCFA(), scriptDyEFA(), scriptINULL(), scriptISAT(), scriptMIM()

Examples

dvn <- 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="_")
cfm.script.indist <-  scriptCFM(dvn, lvxname = "Sat", lvyname = "Com",
writeTo = tempdir(),
fileName = "CFM_indist")

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

Description

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

Value

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

See Also

scrapeVarCross which this function relies on

Other script-writing functions: scriptAPIM(), scriptBiDy(), scriptCFA(), scriptCFM(), scriptINULL(), scriptISAT(), scriptMIM()

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi", x_stem = "sat.g", x_delim1 = ".",
x_delim2="_", distinguish_1="1", distinguish_2="2")

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

A Function That Writes, Saves, and Exports Syntax for Fitting the I-NULL model for indistinguishable dyads

Description

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for the I-NULL model described in Olsen & Kenny (2006)

Usage

scriptINULL(
  dvn,
  lvxname = "X",
  lvyname = NULL,
  writeTo = NULL,
  fileName = NULL
)

Arguments

Value

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

See Also

scrapeVarCross which this function relies on

Other script-writing functions: scriptAPIM(), scriptBiDy(), scriptCFA(), scriptCFM(), scriptDyEFA(), scriptISAT(), scriptMIM()

Examples

dvn <- scrapeVarCross(dat = DRES, x_order = "sip", x_stem = "PRQC", x_delim1 = "_",
x_delim2=".", x_item_num="\\d+", distinguish_1="1", distinguish_2="2")
qual.inull.script <- scriptINULL(dvn, lvxname = "Qual",
writeTo = tempdir(),
fileName = "I-NULL_script")

A Function That Writes, Saves, and Exports Syntax for Fitting the I-SAT model for indistinguishable dyads

Description

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for the I-SAT model described in Olsen & Kenny (2006)

Usage

scriptISAT(dvn, lvxname = "X", lvyname = NULL, writeTo = NULL, fileName = NULL)

Arguments

Value

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

See Also

scrapeVarCross which this function relies on

Other script-writing functions: scriptAPIM(), scriptBiDy(), scriptCFA(), scriptCFM(), scriptDyEFA(), scriptINULL(), scriptMIM()

Examples

dvn <- scrapeVarCross(dat = DRES, x_order = "sip", x_stem = "PRQC", x_delim1 = "_",
x_delim2=".", x_item_num="\\d+", distinguish_1="1", distinguish_2="2")

qual.isat.script <- scriptISAT(dvn, lvxname = "Qual",
writeTo = tempdir(),
fileName = "I-SAT_script")

A Function That Writes, Saves, and Exports Syntax for Fitting Latent Mutual influence Model

Description

This function takes the outputted object from scrapeVarCross() and automatically writes, returns, and exports (.txt) lavaan() syntax for specifying Mutual Influence Models (MIMs). Users can also invoke configural, loading, and/or intercept invariant measurement models, and particular types of structural comparisons.

Usage

scriptMIM(
  dvn,
  scaleset = "FF",
  lvxname,
  lvyname,
  constr_dy_x_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_x_struct = c("variances", "means"),
  constr_dy_y_meas = c("loadings", "intercepts", "residuals"),
  constr_dy_y_struct = c("variances", "means"),
  constr_dy_xy_struct = c("actors", "partners"),
  model = lifecycle::deprecated(),
  equate = lifecycle::deprecated(),
  est_k = FALSE,
  writeTo = NULL,
  fileName = NULL
)

Arguments

Value

character object of lavaan script that can be passed immediately to lavaan functions. Users will receive message if structural comparisons are specified when the recommended level of invariance is not also specified. If user supplies dvn with containing X or Y variables, they are alerted to respecify the dvn object.

See Also

scrapeVarCross which this function relies on

Other script-writing functions: scriptAPIM(), scriptBiDy(), scriptCFA(), scriptCFM(), scriptDyEFA(), scriptINULL(), scriptISAT()

Examples

dvn <- 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="_")

mim.script.indist <- scriptMIM(dvn, lvxname = "Sat", lvyname = "Com", est_k = TRUE,
writeTo = tempdir(),
fileName = "MIM_indist")

A Function That Writes, Saves, and Exports Syntax for Fitting Observed Actor-Partner Interdependence Models

Description

A Function That Writes, Saves, and Exports Syntax for Fitting Observed Actor-Partner Interdependence Models

Usage

scriptObsAPIM(
  X1 = NULL,
  Y1 = NULL,
  X2 = NULL,
  Y2 = NULL,
  equate = "none",
  k = FALSE,
  writeTo = NULL,
  fileName = NULL
)

Arguments

Value

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

Examples

obsAPIMScript <- scriptObsAPIM (X1 = "SexSatA", Y1 = "RelSatA",
X2 = "SexSatB", Y2 = "RelSatB",
equate = "none",
writeTo = tempdir(),
fileName = "obsAPIM_script")