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(Version 0.4.0, updated on 2026-07-20, release history)

semptools

Helper functions for modifying (postprocessing) plots generated by semPlot::semPaths() from the semPlot package.

Installation

The latest stable version can be installed from CRAN:

install.packages("semptools")

The latest development version at GitHub can be installed by remotes::install_github():

remotes::install_github("sfcheung/semptools")

To read the guides (vignettes) on how to use the functions, you can build the vignettes locally when installing the package:

remotes::install_github("sfcheung/semptools", build_vignettes = TRUE)

You can also find the guides under Articles of the Github page of this package.

Background

semPlot::semPaths() is a very useful function for visualizing structural equation models. We use it a lot. The output is a qgraph object which is highly customizable. Our area is in psychology and some users in this area may not know how to customize the graphs in aspects relevant to psychology. Therefore, we think it would be useful for users in psychology, including us, to have some functions for customizing the graphs from semPlot::semPaths(), without knowing the technical details of qgraph.

Philosophy

We though about the tasks we usually want to do with a semPlot::semPaths() graph, and wrote one function for each task. We wrote the functions such that all of them work by postprocessing a semPlot::semPaths() graph: receive a semPlot::semPaths() graph, modify it, and return a modified semPlot::semPaths() graph. This also allows users to use the the R pipe operator |> available since R 4.1.x (or the %>% operator from the magrittr package) to chain together modifications. For example:

modified_graph <- original_graph |>
                    task_1() |>
                    task_2(other_arguments) |>
                    task_3()

In psychology, two typical models are confirmatory factor analysis model and structural models with latent factors. Therefore, we also wrote two functions, set_cfa_layout() and set_sem_layout(), that can combine several common tasks together, such as specifying the positions of the latent factors and adjusting the positions of the indicators.

We also wrote the functions in a way that users do not need to know the technical detail (e.g., the position of the path in the list of all paths). For example, if a user wants to move the path coefficient of the path from x to y closer to y, the user only needs to tell the function that it is the path from x to y. The function will find which path it is in the qgraph object.

What we have so far

These are some functions included so far:

Add elements based on parameter estimates

• mark_se(): Add the standard errors to parameter estimates.

• mark_ci(): Add the confidence intervals to parameter estimates.

• mark_sig(): Add asterisks (“*”, “**”, “***”) based on \(p\)-values of parameter estimates.

• add_rsq(): Add R-squares (and remove the error variances) to endogenous variables.

Edit lines (“edges”, such as paths, covariances, and error variances)

• rotate_resid(): Rotate the residuals of selected variables.

• set_curve(): Change the curvature of selected paths.

• set_edge_color(): Change the colors of selected paths.

• set_edge_line_type(), set_edge_line_width(): Change the line types (e.g., solid, dashed, dotted) and line widths of selected paths.

• set_edge_label(), set_edge_label_bg(), set_edge_label_size(): Change the labels of selected paths directly.

• set_edge_label_position(): Move the parameter labels of selected paths along the paths.

• safe_edge_label_position(): Try to move edge labels (e.g., regression coefficients) to prevent overlapping of labels.

• safe_resid_position(): Try to rotate residuals of nodes to prevent overlapping.

• set_edge_attribute(): A generic function to change any named attributes of selected paths.

Edit variables (“nodes”, the “squares” and “circles”)

• change_node_label(): Change the labels of nodes.

• set_node_label_color(), set_node_label_size(): Change the colors and sizes of the labels of selected nodes.

• set_node_color(), set_node_height(), set_node_shape(), set_node_size(), set_node_width(): Change the aesthetic aspects of selected nodes.

• set_node_border_color(), set_node_border_width(): Change the colors and widths of the borders of nodes (e.g., the color and width of the line of a square).

• drop_nodes() and keep_nodes(): Drop or keeps nodes (e.g., drop all control variables).

• move_node(): “Move” (change the positions of) selected nodes.

• node_labels_equal_scale(): Make all labels of nodes have the same font size.

• set_node_attribute(): A generic function to change any named attributes of selected nodes.

Common layouts

• set_cfa_layout(): A function for typical confirmatory factor analysis models. It can be used for specifying the orders of the indicators and factors, specifying the positions of the factors, setting the curvatures of the interfactor covariances, set the position of all loadings, and setting the orientation of the model (down, left, up, or right).

• set_sem_layout(): A function for typical SEM models. It can be used for specifying the orders of the indicators and factors, specifying the positions of the factors using a grid, specifying the orientation of each factor’s indicators (down, left, up, right), fine tuning the positions of indicators of selected factor, setting the curvatures of selected paths, and specifying the position of all or selected loadings.

• quick_simple_mediation(), quick_serial_mediation(), and quick_parallel_mediation(): Functions for common mediation models. They will try to set the positions of nodes automatically. The positions of nodes can be adjusted by move_node() to achieve the desired layout.

Miscellaneous helpers

• layout_matrix(): A helper to specify how to place the nodes.

• set_graph_margins(): Change the margins of a plot.

• rescale_layout(): Rescale a plot to fit the plot area.

See the Get Started to learn more about these and other functions.

Multigroup models and list of models

Since version 0.3.3.17, most functions support figures of multigroup models, which are stored as a list of qgraph plots.

Status

This package is still under development. There will be bugs, and there are limitations. Please post your comments and suggestions as issues at GitHub.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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