Power Analyses for SEM

Provides a-priori, post-hoc, and compromise power-analyses for structural equation models (SEM).

'SEM Shiny'

Interactive 'shiny' application for working with Structural Equation Modelling technique. Runtime examples are provided in the package function as well as at < https://kartikeyab.shinyapps.io/semwebappk/> .

Average and Conditional Effects

Use structural equation modeling to estimate average and conditional effects of a treatment variable on an outcome variable, taking into account multiple continuous and categorical covariates.

SEM Sensitivity Analysis

Performs sensitivity analysis for Structural Equation Modeling (SEM). It determines which sample points need to be removed for the sign of a specific path in the SEM model to change, thus assessing the robustness of the model. Methodological manuscript in preparation.

Fit Measure Cutoffs in SEM

Calculate cutoff values for model fit measures used in structural equation modeling (SEM) by simulating and testing data sets (cf. Hu & Bentler, 1999 ) with the same parameters (population model, number of observations, etc.) as the model under consideration.

Ancestor Regression

Causal discovery in linear structural equation models (Schultheiss, and Bühlmann (2023) ) and vector autoregressive models (Schultheiss, Ulmer, and Bühlmann (2025) ) with explicit error control for false discovery, at least asymptotically.

Post-Estimation Utilities for 'lavaan' Fitted Models

Companion toolbox for structural equation models fitted with 'lavaan'. Provides post-estimation diagnostics and graphics that operate directly on a fitted object using its estimates and covariance, and refits auxiliary models when needed. The package relies on 'lavaan' (Rosseel, 2012) .

Social Relations Analyses with Roles ("Family SRM")

Social Relations Analysis with roles ("Family SRM") are computed, using a structural equation modeling approach. Groups ranging from three members up to an unlimited number of members are supported and the mean structure can be computed. Means and variances can be compared between different groups of families and between roles.

Graphical Extension with Accuracy in Parameter Estimation (GAIPE)

Implements graphical extension with accuracy in parameter estimation (AIPE) on RMSEA for sample size planning in structural equation modeling based on Lin, T.-Z. & Weng, L.-J. (2014) . And, it can also implement AIPE on RMSEA and power analysis on RMSEA.

Computationally Efficient Maximum Likelihood Identification of Linear Dynamical Systems

Provides implementations of computationally efficient maximum likelihood parameter estimation algorithms for models representing linear dynamical systems. Currently, two such algorithms (one offline and one online) are implemented for the single-output cumulative structural equation model with an additive-noise output measurement equation and assumptions of normality and independence. The corresponding scientific papers are referenced in the descriptions of the functions implementing these algorithms.