Usage Notes

Video Tutorial

This video offers a comprehensive guide to using the CLC Estimator App for those new to the application or requiring assistance with its features. The tutorial is designed to be easy to understand, covering each step clearly and concisely.

The tutorial covers the following points:

Some key questions and answers to facilitate the correct use of the CLC Estimator


Rhemtulla, M., van Bork, R., & Borsboom, D. (2020). Worse than measurement error: Consequences of inappropriate latent variable measurement models. Psychological Methods, 25(1), 30–45.

Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. American Psychological Association.

Information on the CSV input file

The CLC Estimator accepts as input only .csv files, which stands for "comma-separated values".  This format is commonly used by many statistical software packages to store and exchange data. A .csv file is made up of rows and columns, much like a spreadsheet. The first row, called the header, should have labels for each column to help identify the data. The rows below the header contain the actual data, separated by a specific character called a delimiter.

For example, if we have a small dataset of people's names and ages, it might look like this in a .csv file:





Here, the first row is the header, which has the labels "Name" and "Age." The following rows contain the data, with each value separated by a comma (which is the delimiter in this case).

When using the CLC Estimator, you can choose the delimiter that separates the values in your .csv file. It can be a comma, semicolon, or a tab. This flexibility allows the tool to work with different .csv file formats. It's also important to note that the .csv file should be saved in UNICODE format, which is a standard for encoding text and characters. Additionally, decimal numbers should be written with a period (.) as the decimal separator, as per international scientific conventions.

For reference, a sample dataset is available for download in .csv format (using a comma delimiter) at the following link: You can use this sample dataset to better understand the .csv file format and practice using the CLC Estimator.

Below you you can find some examples, using the above-mentioned sample dataset, showing how the .csv should look in different software. 

Spreadsheet Example

SPSS Example

R Studio Example

Running the CLC Estimator app offline 

There are two approaches to running the CLC Estimator app offline on your PC.

Important: Please note in both cases, to run the app offline, you need to install Rtools (available only for Windows at the moment), which can be downloaded from:

Approach 1. Install from R or R Studio

Enter the following code in the R console (install also the dependencies):

install.packages('devtools') #install devtools package

library('devtools') #load devtools package

install_github('leoegidi/clc') #install clc package from GitHub

library('clc') #load clc package

clc() #load clc estimator

Approach 2. Download the package from GitHub and run it in R Studio