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2011 Jun 01
3
Zero-inflated regression models: predicting no 0s
Hi all, First post for me here, but I have been reading on the forum for almost two years now. Thanks to everyone who contributed btw! I have a dataset of 4000 observations of count of a mammal and I am trying to predict abundance from a inflated-zero model as there is quite a bit of zeros in the response variable. I have tried multiple options, but I might do something wrong as every
2008 Sep 27
10
FW: logistic regression
Sorry. Let me try again then. I am trying to find "significant" predictors" from a list of about 44 independent variables. So I started with all 44 variables and ran drop1(sep22lr, test="Chisq")... and then dropped the highest p value from the run. Then I reran the drop1. Model: MIN_Mstocked ~ ORG_CODE + BECLBL08 + PEM_SScat + SOIL_MST_1 + SOIL_NUTR + cE + cN +