Results

Note. In this example, attempting to reshape RT and Accuracy columns to Long format produces the following error when it should not: 'lengths(varying)' must all match 'length(times)'

Wide to Long

'lengths(varying)' must all match 'length(times)'

Getting started

With this module, you can transform a dataset from the wide format to the long format. To do this, select the variables (columns) from the original dataset that you want to convert into different long format variables. For each long format variable that you want to create, define its name and fill the field below it in the New long variable field. In the new dataset, a variable with the specified name will be created, containing one row for each column value for each case. Additionally, in the Index Variables tab you can specify the names of the indexes variables, that keep track of the original levels (e.g., conditions or times). A variable ID will also be created, containing the case ID, which represents the original row number in the wide format. If there are variables whose values should be copied for each row of the same case (invariant covariates), you can add them in the Non-varying Variables field. Once you are ready, click on the Reshape button to open a new file with the reshaped data.

Info Table
Info		Value
Original N		.
New N		.
# of original variables		.
# of new varariables		.
Cols to rows		6
Target variables		.
Fixed variables		0

Repeated measures levels
index1	RT	Accur	Freq
.	.	.	.
.	.	.	.
.	.	.	.

Data Preview
Rows	id	index1	RT	Accur
.	.	.	.	.

References

[1] The jamovi project (2023). jamovi. (Version 2.4) [Computer Software]. Retrieved from https://www.jamovi.org.

[2] R Core Team (2022). R: A Language and environment for statistical computing. (Version 4.1) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2023-04-07).