Recent content by 0.05

The dependent variable is a pathologic index, which is the result of combining 4 more indices. It combines different types of metrics: measures, estimations ... so at the end the variable is continuous, but values can't be lower than zero, but usually zero is not that often, as you can see in...

The qq plot that I posted shows the residuals of a linear regression. I did a test for the outliers and was non significant ("testOutlier" in R's package DHARMa). Certainly, there are some outliers but my impression (maybe I'm wrong) is that they don't have too much influence in the model...

Thanks. Transforming the data doesn't produce any improvement. It doesn't seem to exist a problem with outliers. I agree it doesn't look that bad, but I wasn't sure because of the aggregation of observations around zero. I was also curious about how to do this analysis with a non-parametric...

Thank you for your clarification. I have almost 300 observations. I made a q-q plot of the residuals and run a couple of tests. It's slightly non-significant in the Kolmogorov-Smirnov and clearly non-significant with others (Shapiro and Anderson). I tried various transformations, but I'm adding...

I have a continuous dependent variable and two categorical predictors. I wanted to do a linear regression but the dependent variable does not meet the assumptions of normality in the residuals. Transformations do not work. Then, what options do I have to analyze this? I was looking into things...

Hello, I have a doubt about the ways of comparing categories in logistic regression. I have 200 subjects with a dependant variable (positive/negative) and I want to test them with an independent variable (IV) of 4 categories (age). I am going to use a logistic regression, but when I do that, I...