[R] Logistic Regression

[farahnazlakhani]

I am working on my thesis in which i have couple of independent variables
that are categorical in nature and the depndent variable is dichotomus. 
Initially I run univariate analysis and added the variables with significant
p-values (p<0.25) in my full model. 
I have three confusions. Firstly, I am looking for confounding variables by
using formula "(crude beta-cofficient - adjusted beta-cofficient)/ crude
beta-cofficient x 100" as per rule if the percentage of any variable is >10%
than I have considered that as confounder. I wanted to know that from
initial model i have deducted one variable with insignificant p-value to
form adjusted model. Now how will i know if the variable that i deducted
from initial model was confounder or not? 
Secondly, I wanted to know if the percentage comes in negative like
(-17.84%) than will it be considered as confounder or not? I also wanted to
know that confounders should be removed from model? or should be kept in
model?
Lastly, I wanted to know that I am running likelihood ratio test to identify
if the value is falling in critical region or not. So if the value doesnot
fall in critical region than what does it show? what should I do in this
case? In my final reduced model all p-values are significant but still the
value identified via likelihood ratio test is not falling in critical
region. So what does that show? 


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