---
title: "``superb`` and SPSS"
bibliography: "../inst/REFERENCES.bib"
csl: "../inst/apa-6th.csl"
output: 
  rmarkdown::html_vignette
description: >
  This vignette shows how to use superb with SPSS files or
  within SPSS.
vignette: >
  %\VignetteIndexEntry{``superb`` and SPSS}
  %\VignetteEngine{knitr::rmarkdown}
  \usepackage[utf8]{inputenc}
---


```{r, echo = FALSE, warning=FALSE, message = FALSE, results = 'hide', warning = FALSE}
cat("this will be hidden; use for general initializations.\n")
library(superb)
library(ggplot2)
library(png)
options(superb.feedback = c('design','warnings') )
```

The purpose of ``superb`` it to make plots showing adjusted error bars. However, not everyone 
are using R. Luckily, for those of you who are using SPSS, you have three options:
1) R can read SPSS file and therefore, you can open the data and make the plot in R before
returning to SPSS. 2) It is possible to use SPSS only --from a syntax window-- get access to 
all the capabilities of ``superb``. 3) Using the graphical user interface superbShiny,
you can also open SPSS files. This interface is available online as well.

In this vignette, we demonstrate how to use these three options to make a plot with
SPSS data.


## First option: Using R

Suppose that you have a file called ``SPSS_Demo.sav``. Using the library ``foreign``, you can 
open the file and use it in R to make your plot. 

The following syntax for example will open an SPSS file, assuming it is in a folder on
your hard drive C:. First, set the working directory and the file name with

```{r, echo=TRUE, eval=FALSE}
setwd("c:")
file <- "Demo_SPSS.sav"
```

```{r, echo=FALSE, results="hide"}
file <- system.file("extdata", "SPSS_Demo.sav", package = "superb")
```

Then you are ready to read the file with the help of the ``foreign`` library

```{r}
library(foreign)
data <- read.spss(file, to.data.frame = TRUE)
```

Finally, ask for a plot with 

```{r, fig.width = 4, eval=FALSE, fig.cap="**Figure 1: A plot with SPSS data within R**"}
superb( 
    cbind(time1, time2) ~ .,
    data, 
    WSFactors      = "Temps(2)",
    plotStyle      = "line",
    adjustments    = list(purpose = "single", 
                          decorrelation = "CA"),
    errorbarParams = list(color = "purple"),
    pointParams    = list( size = 2, color = "purple")
)
```


## Second option: Using SPSS

The recent versions of SPSS comes bundled with an R interpretor. Further, if you open 
a Syntax window (menu File: New: Syntax), you can send R instructions enclosed within
``BEGIN PROGRAM R.`` and ``END PROGRAM``.

To know if your SPSS installation has R installed, you could for example type these
instructions:

```{r}`r ''`
BEGIN PROGRAM R.
    # a quick test
    cat("R is up and running: ", R.version.string, "\n")
END PROGRAM.
```

then select them all and press Ctrl-R to execute. It R is accepted within SPSS, you
should see an ouptut indicating the version of R installed. It has to be R above 4.0.

If things are working, then you are ready to make your plot with

```{r}`r ''`
BEGIN PROGRAM R.
    # this will install superb if needed; may take a few minutes
    if(!require(superb)) 
        install.packages("superb", type="binary")

    # set the library to be in used
    library(superb)  

    # transfer the data from SPSS into R
    data <- spssdata.GetDataFromSPSS() 

    # all good! make a plot using superbPlot()
    superbPlot(   data, 
                  WSFactors      = "Temps(2)",
                  variables      = c("time1","time2"),
                  plotStyle      = "line",
                  adjustments    = list(purpose = "single", decorrelation = "CA"),
                  errorbarParams = list(color = "purple"),
                  pointParams    = list( size = 2, color = "purple")
    )

END PROGRAM.
```

Here are screen captures showing the syntax window:

```{r fig2, echo=FALSE, fig.cap="**Figure 2: Syntax to generate a plot**", fig.width = 8, fig.height = 8}
library(png)
fle1 <- system.file("extdata", "Syntax1.png", package = "superb")
img1 <- readPNG(fle1)
plot.new() 
rasterImage(img1, 0, 0, 1, 1)
```





## Third option: Using a graphical user interface

A graphical user interface is available at 
[this link](https://dcousin3.shinyapps.io/superbshiny/)

This interface can read a few file format, including SPSS files. You can consult a Youtube
demonstration [here](https://www.youtube.com/watch?v=rw_6ll5nVus).




## In summary

The ``superb`` framework can be used to display any summary statistics. Here, 
we showed how ``superbPlot()`` can be used with SPSS datasets. 

I thank Michael Cantinotti for raising my awarness to the fact that 
new versions of SPSS can show plots produced within ``BEGIN PROGRAM R.`` 
and ``END PROGRAM.`` syntax lines and providing a short example.



# References

<p>Cousineau D, Goulet M, Harding B (2021).
"Summary plots with adjusted error bars: The superb framework with an implementation in R."
<em>Advances in Methods and Practices in Psychological Science</em>, <b>2021</b>, 1--46.
doi: https://doi.org/10.1177/25152459211035109
</p>
<p>Walker, J. A. L. (2021).
"Summary plots with adjusted error bars (superb)."
<em>Youtube video</em>, <b><a href="https://www.youtube.com/watch?v=rw_6ll5nVus">accessible here</a>)</b>.
</p>