README.Rmd

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output: github_document
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knitr::opts_chunk$set(
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# GCLM

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The goal of GCLM is to help you write lavaan() script for fitting generalized cross-lagged panel models (GCLM; Zyphur et al., 2019). Currently, there is only one function for fitting the base GCLM, but new functions and arguments may be added to automate the scripting of short-run Granger-Sims tests, and long-run impulse responses.

## Installation

You can install the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("jsakaluk/GCLM")
```

## Example

This is a basic example which shows you how to solve a common problem:

```{r gclm scripting}
library(GCLM)
library(lavaan)
#Save/export script for GCLM between Sacrifice and Satisfaction over 5 waves
base.model <- gclm(xvar = "sacrifice", yvar = "satisfaction", waves = 5)
```
The function saves a lavaan() script for you to immediately submit to its model-fitting functions (e.g., lavaan::sem()), and also outputs a .txt document of the same script to the working directory.

![](figures/script.png)

```{r lavaan model fitting, eval=FALSE}
base.model.fit <- sem(base.model, data = dat)
summary(base.model.fit)
```

Eventually, new functionality may be programmed to automate the tests of short-run and long-run effects. Until then, users can manually ammend this script and save as a new lavaan() script to conduct these additional tests.