I am trying to perform multinomial logistic regression for upsell modelling.

But the proportion of non responders in my dataset is very high, ~95%. Rest of the data is divided among 4 responding categories.

After building the model, while assigning probability to each observation using max probability criterion from depending categories, i observed that all the observation have been marked as non responders because the predicted probability for non responding category is highest for all the observation.

This is leading to wrong predictions.

Can you please suggest how can i correct this.

]]>Second, you probably want a longitudinal design here, with measurements at at least 3 time points on each person. Then you can use a multilevel model to analyze the data.

]]>I am conducted a quantitative study examining whether technology adoption has a positive effect on job performance. Specifically, 1)does perceived ease of use of technology has a positive effect on job performance 2)does perceived usefulness of technology has a positive effect on job performance. My question is would it be best to conduct a correlation study? T -test? one tailed or two tailed? Thank you so much!!!!

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