I have a dataset with two level factors - fertilizers ("Nitrogen" or "Phosphorous") that differed in their concentration level("Low" or "High"). I performed a zero-inflated negative binomial and obtained this result using R. The theta value is supposed to represent "parameter k" of the negative binomial model. I want to calculate the different values of k for each of the treatments. In other literature, Fischer's variance to mean ratio is associated with the parameter k of the negative binomial model and often referred to as an index of aggregation. How can I obtain different values of parameter k for each treatment (level x fertilizer) and compare them? Note: This is just a sample exampleenter image description here

  • $\begingroup$ The model you are using does not appear to be a mixed-effects model. $\endgroup$ – Dimitris Rizopoulos Sep 26 '19 at 10:36

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