A part of the df without NA:
## Subject True_value Response.(CD3_blast)
##1 1 -1.76 0
##2 1 -2.16 0
##3 1 0.9750 0.9750
##4 1 -0.6 0
##5 1 2.0350 2.0350
##6 1 0.1400 0.1400
##7 1 -3.26 0
##8 1 3.9350 3.9350
##9 1 0.0300 0.0300
##10 1 -20.7 0
Histogram of the data:
As I'm setting the zero values myself: 'IF True_Value (Stimulation response - Negative control) < 0 => assign 0'. I'm wondering whether the smaller values below e.g. 1 are responses or should also be zero and thus whether < 0 should be changed to < 1 or <0.5 or <0.1. However, I don't know how I could test this in R.
Code Score Tests for Zero-Inflation:
# JVDB score test *
numerator <- (n0 -np0_tilde)^2
denominator <- np0_tilde*(1-p0_tilde) - nlambda_est(p0_tilde^2)*
test_stat <- numerator/denominator
pvalue <- pchisq(test_stat,df=1, ncp=0, lower.tail=FALSE)
However, I guess this test just determines whether my data is zero-inflated and does not give any information on whether the low values should be zero's as well.