dySEM

R Package
Methods
Dyadic Data
An R package for scripting, fitting, and reporting latent models of dyadic data via lavaan.
Published

January 1, 2021

dySEM hex logo

Overview

The dySEM package helps automate the process of scripting, fitting, and reporting on latent models of dyadic data via lavaan. It was initially developed in the course of research described in Sakaluk, Fisher, and Kilshaw (2021) and has since undergone considerable expansion.

dySEM currently contains 84 functions, of which 31 are user-facing (exported), covered by 551 unit tests.

Current Functionality

Uni-Construct Models

  • Univariate Dyadic Model
  • Correlated Dyadic Factors Model
  • Hierarchical Dyadic Factor Model
  • Bifactor Dyadic Model

Bi-Construct Models

  • Latent Actor-Partner Interdependence Models (APIM)
  • Latent Common Fate Models (CFM)
  • Latent Bifactor Dyadic (Bi-Dy) Models
  • Observed Actor-Partner Interdependence (APIM)

Multi-Construct Models

  • Multiple Correlated Dyadic Factors Model (Dyadic Confirmatory Factor Analysis)
  • Dyadic Exploratory Factor Analysis

Additional Features

  • Automated specification of invariance constraints, including full indistinguishability
  • Variable-and-parameter specific tests of noninvariance
  • Reproducible path diagrams and tables of statistical output
  • Supplemental statistics (omega reliability, noninvariance effect sizes, corrected model fit indexes)
  • Multiple open-access datasets for learning and teaching

Workflow

A typical dySEM workflow involves five steps:

  1. Import and wrangle data into dyad-structure format
  2. Scrape variables from your data frame
  3. Script your preferred model
  4. Fit and inspect your model via lavaan
  5. Output statistical visualizations and/or tables

Installation

Install the released version from CRAN:

install.packages("dySEM")

Or the development version from GitHub:

devtools::install_github("jsakaluk/dySEM")

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