Filtering data is a a common step in data analysis. In this post, we explore how to filter in data.table in R, including subsetting by conditions and selecting specific groups. We also show how to save the filtered data as a new data frame for further analysis.
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This post explores summing multiple columns in data.table, including group-wise summation and dynamic column selection with %in%. We also compare this approach with dplyr and base R. Whether you’re working with large datasets or need flexible column selection, these techniques will help you get the job done. Read on to learn more!
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Learn how to select columns in data.table using names, character vectors, and indices. This guide covers selecting single and multiple columns, using .SDcols, and indexing. With practical examples, you’ll see how data.table offers a fast and flexible way to manipulate large datasets in R.
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This blog post focuses on the practical aspects of conducting mediation analysis in R. First, we will look at how to do it using the mediation package. Then, we will walk through an example of using the Lavaan package to perform mediation analysis. Both mediation examples will include R code chunks with explanations. This blog
Mediation Analysis in R: How to Run it with two Packages Read More »
When working with data in Python, using Pandas to read JSON from URL is an excellent tool that lets you directly load JSON data from a web source into a Pandas dataframe. This tutorial focuses on the steps to accomplish this task, building upon our previous discussions on reading JSON with Python more generally.
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Positiv korrelation är ett grundläggande begrepp inom statistik och ofta använt inom kognitionsvetenskapen för att förstå relationer mellan två och fler variabler. I en tidigare post lärde vi oss utföra korrelationsanalys i både R och Excel, vilket är användbart när vi vill undersöka samband. Men vad innebär egentligen att ett samband är positivt, och vad
Positiv Korrelation: Vad Det Betyder och Exempel Read More »
In this volcano plot in R tutorial, we will use ggplot2, a popular package for creating beautiful and customizable graphics in R. A volcano plot in R is a scatter plot showing the relationship between the fold change and the statistical significance in certain data types. Outline In this data visualization tutorial, we will start
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A random intercept model in R is useful for analyzing data from experiments that involve repeated measurements of the same participants or items. It allows you to control for the variability in the outcome variable due to random effects, such as individual differences or item difficulty while estimating the fixed effects of your predictors of
Random Intercept Model in R: Interpretation and Visualization Read More »
In this post, we will look at how to use the unique function in R, which is a good tool for identifying and removing duplicate values in different data structures. We will first have a look at what the unique() function is and how it works. Next, we will look at some examples of how
The Unique Function in R: How to Use it in 4 Ways Read More »
Utforska innehållsvaliditet i mätinstrument och bedömningsmetoder med exempel från minnestest och användarnöjdhetsundersökning. Upptäck hur du säkerställer att dina mätningar mäter det de är avsedda att mäta.
Innehållsvaliditet: Exempel från Kognitionsvetenskapen Read More »