Semproducible is an R package that makes your latent variable models in lavaan reproducible. Semproducible generates all the necessary data and R code from your existing lavaan model.
This package makes it possible to reproduce a model without disclosing the raw data (which might be sensitive).
You can use semproducible in two ways:
- Generate reproducible code from a lavaan model
- Generate reproducible code from a data frame
- Only one line of code to reproduce your model
- The generated code fit a journal appendix
- Researchers can reproduce your model (and try alternative model specifications)
devtools::install_github("peterdalle/semproducible")semproducible(x, formula)Where x is either a lavaan model or a data frame.
And formula is the lavaan formula syntax (e.g., ind60 =~ x1 + x2 + x3).
Let's say you have the following lavaan model, and you want to make it reproducible:
library(lavaan)
# Example: http://lavaan.ugent.be/tutorial/sem.html
formula <- "# latent variables
ind60 =~ x1 + x2 + x3
dem60 =~ y1 + y2 + y3 + y4
dem65 =~ y5 + y6 + y7 + y8
# regressions
dem60 ~ ind60
dem65 ~ ind60 + dem60
# residual covariances
y1 ~~ y5
y2 ~~ y4 + y6
y3 ~~ y7
y4 ~~ y8
y6 ~~ y8"
fit <- sem(formula, data=PoliticalDemocracy)The only thing you need to do is to pass fit and formula into semproducible:
library(semproducible)
semproducible(fit, formula)If you have a data frame with many variables, you can reproduce the entire data frame and let other researchers choose variables to model.
library(semproducible)
library(tidyverse)
iris %>%
select(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) %>%
semproducible(formula = "Sepal.Length ~ Sepal.Width + Petal.Length")code <- semproducible(fit, formula)
save_code(code, "filename.R")If you run example 2 above, the generated code will look like this:
library(tibble)
library(lavaan)
# Number of observations.
observations <- 150
# Covariance matrix.
cov_mat <- tribble(~Sepal.Length, ~Sepal.Width, ~Petal.Length, ~Petal.Width,
0.685693512304251, -0.0424340044742729, 1.27431543624161, 0.516270693512304,
-0.0424340044742729, 0.189979418344519, -0.329656375838926, -0.12163937360179,
1.27431543624161, -0.329656375838926, 3.11627785234899, 1.29560939597315,
0.516270693512304, -0.12163937360179, 1.29560939597315, 0.581006263982103)
# Convert data frame to matrix (that lavaan can handle).
cov_mat <- as.matrix(cov_mat)
# Rows should have names too.
rownames(cov_mat) <- colnames(cov_mat)
# SEM model in lavaan syntax.
formula <- 'Sepal.Length ~ Sepal.Width + Petal.Length'
# Fit SEM model.
fit <- lavaan::sem(formula, sample.cov = cov_mat, sample.nobs = observations)
# Show results.
summary(fit)And if you then run the generated code above, you will notice that it has been successfully reproduced.
- Do I need to specify all columns?
- How do I control the width of the code?
- Can I use semproducible in a
tidyversepipeline? - How do I know that my generated code is correct?
- Why doesn't my generated code produce the exact same result?
Load semproducible and then run ?semproducible in the R console to view the full documentation.
Report problems or request a new feature by submitting a new issue.
You can help with:
- Test semproducible in your project, and report a bug
- Read the documentation and verify that it corresponds to actual behavior
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