# Jamovi

Norsk versjon av denne nettsiden.

# jamoviguiden

jamoviguiden is available in English or Swedish. It contains brief, accessible guides (with pictures) of commonly used procedures in jamovi. To keep the content short, no (or little) description of the assumptions behind the statistical tests and how to interpret the results is described. When you get started, it's often easy to explore on your own.
To learn more about jamovi and statistics, the (free!) e-book ”Learning statistics with jamovi” by Danielle Navarro and David Foxcroft is recommended.

jamoviguiden was created by Jonas Rafi and is available in English or Swedish. It is licensed under Creative Commons License Attribution-Non Commercial 4.0 International License .

# From SPSS to jamovi

Quite a few of us are so used to SPSS that we are a little scared to switch to another software because such transition and to get acquainted with a new software always takes time and effort. Now might be a good time to switch because SPSS is also introducing a new interface with version 26 which at least requires getting used to something new and learn it. Why not take a little bigger step and learn jamovi? jamovi does not entail the incredibly high license costs of SPSS (from \$ 1290 / year for Base Package) and can be a first step on the road to R. jamovi tries to use an interface that is relatively similar to the one in SPSS, the result version is more transparent and can be easily transferred to text processing (copy-and-paste with [mostly] keep formatting).

Comparison of analyses: provides an overview of which analysis functions are available in SPSS and the respective functions in jamovi.

Side-by-side: Shows a side-by-side comparison of how something is done in SPSS and in jamovi.

# From jamovi to R

The real power of using jamovi and the jmv-library (described below) comes with the opportunity to integrate it with other R-functions. Such functions could, e.g., be used to extract and manipulate data from log files of software used to conduct experiments (PsychoPy, e-prime, etc.).

## Preparing

To install the library that contains the functions used by jamovi (and in the examples below) open R and type the first line (the second line is required if you want to read or write SPSS files, the >-mark at the begin of the line is the input-mark of R and must not be copied / typed):

```> install.packages('jmv')
> install.packages('foreign')
```

## Use of jamovi syntax in R

First, you have to enable the syntax mode by pressing the properties icon in the top-right corner. Set a tick at syntax mode in the properties window.
Close the properties with the arrow-icon at the top-right .

 The main window changes to text mode and you can run analyses and afterwards right-click on the command the appears at the top of each analysis to export or copy the syntax.

Alternatively, you can write syntax directly. To do this, open R or RStudio and type the command in the first line (while the second line is required for if you want to use SPSS files):

```> library(jmv)
> library(foreign)
```

Afterwards you are ready to analyze your data. Typically, you have to load a dataset first. Do this using the first line if you have a CSV file («sep» has to be set to the separator between data cells, e.g., ",", ";", etc.) or with the second line for loading SPSS data:

```> dat = read.csv("data.csv", header = TRUE, sep = ",")
> dat = read.spss("data.sav", to.data.frame = TRUE)
```

Afterwards are you ready to run whatever analysis you like (here is an overview of available functions). For example, to run a simple descriptive-statistics-analysis:

```> descriptives(dat, vars = vars(var1, var2))
```

or for a correlation between to variables (quite basic in the first and more advanced - adding two non-parametric measures and plots - in the second line; please note that pearson = TRUE is not necessary because it is the default):

```> corrMatrix(dat, vars = vars(var1, var2), pearson = TRUE, sig = TRUE)
> corrMatrix(dat, vars = vars(var1, var2), spearman = TRUE, kendall = TRUE, sig = FALSE, flag = TRUE, plots = TRUE)
```

## To boldly go...

As I said above, the real power comes with the transition to R: the functionality and the access to libraries dealing with (more or less) every statistical problem you can imagine.
To learn more about R you can use two excellent websites by Danielle Navarro. The first is "Learning statistics with R" and has psychology students who use R in their first method course as the main target group. On this page you will find a PDF and a bookdown version that was the basis for «Learning statistics with jamovi» (mentioned above). The second resource "R for Psychological Science" is still under construction and aimed more at someone who has taken at least one research method class and would like to learn to use the R programming language in their own work. This site also has a strong focus on the tidyverse methodology of Hadley Wickham.

The SPSS-to-jamovi and jamovi-to-R sections were created by Sebastian Jentschke and are licensed under [http: //creativecommons.org/licenses/by-nc/4.0 Creative Commons Attribution-Non Commercial 4.0 International License] .