AlejandroG
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I see what you mean, Maybe using the R command option can do the job; you just need to select that option (the "R" symbol square) when creating the new variable and insert the code to add up the variables you want. For example, based on …
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It seems you can use the drag and drop option (at least that's what I can see from the screenshot provided) because the drag and drop option looks like this https://forum.cogsci.nl/uploads/341/YRHF622AGMHC.png and the R option looks like this https…
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Hi Berenike, Check if these steps help you to solve the issue. First, click on "Add computed column." https://forum.cogsci.nl/uploads/409/CN62P7OQ59A7.png Next, type the new variable's name and its measurement level (in this example, it …
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Another option to get the results in JASP is: Create a new variable with the differences between the two variables (Variable 1 - Variable 2) in JASP. Use the One Sample T-Test in the T-Tests module. Move the new calculated variable with the differen…
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Hello, I tried this module and had the same issue. It seems to be a bug because the "pairs = list(list(i1 = p1, i2 = p2))" argument should be solved once you have selected the pair of variables to be compared (at least that's what it sugg…
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Hi, Sorry for the late response; I don't get notifications either. After checking your database, it seems that ANOVA might not be the most appropriate for testing your hypotheses because your data are highly skewed (you can check it out with the De…
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Hello, I think we would need a bit more information to understand whether you used the appropriate analysis and how to interpret the results. For instance, it seems that your dependent variable is "the number of individuals impacted by a data …
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Hi John, The paired-samples t-test compares whether the differences between two repeated samples are statistically significantly different to zero or not (zero means no difference; thus, this is the null hypothesis). Therefore, there's no way (or at…
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Hi @JohnnyB , Thanks a lot for the explanation. Now all makes sense. Best wishes, Alejandro.
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Hi @JohnnyB , Thanks for your answer. I understand that the paired samples t-test analyzes the differences, but the problem is that the descriptive graph depicts something weird with the CI's. I did the math, and the graph is not reflecting the 95%C…
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It is apparently a matter of sample size. It seems you are running a 3-way ANOVA with "Temp", "Raw," and "Feed" as grouping variables. Each grouping variable must have at least two categories (or levels) to be compared.…
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It seems the same occurs with the repeated-measures ANOVA descriptive plot. https://forum.cogsci.nl/uploads/923/0QZIH2IUX45K.png https://forum.cogsci.nl/uploads/297/Z8TNWQI5U3AG.png https://forum.cogsci.nl/uploads/574/S6DEWH691Q93.png