Reputation: 1
When conducting a multivariate Coxph model with categorical predictors, and after releveling all predictor variables (function= relevel()), two of my predictor variables have multiple levels that are "references", eliminating several analyses. Specifically, for the "condition" and "pathogenpres" factors (below). Is this a common problem with a known solution? Do I have too many predictors (n=6)?
Code below:
mydata<-read.csv("survivaldata.csv")
mydata$concentration1 <- relevel(mydata$concentration1, "1")#
mydata$concentration2 <- relevel(mydata$concentration2, "1")#
mydata$contaminant <- relevel(mydata$contaminant, "Control")#
mydata$pathogenpres <- relevel(mydata$pathogenpres, "2")#
mydata$fam <- relevel(mydata$fam, "1")#
mydata$condition <- relevel(mydata$condition, "gg")#
surob1<-Surv(time=mydata$days.surv,event = mydata$censored)
fit.coxph1<-coxph(surob1~concentration1+concentration2+contaminant+pathogenpres+condition+fam,data=mydata,conf.type="plain")
> summary(fit.coxph1)
Call:
coxph(surob1~concentration1+concentration2+contaminant+pathogenpres+condition+fam,data=mydata)
n= 188, number of events= 83
(8 observations deleted due to missingness)
coef exp(coef) se(coef) z Pr(>|z|)
concentration12 0.62577 1.86968 0.35103 1.783 0.0746 .
concentration13 0.69556 2.00483 0.35593 1.954 0.0507 .
concentration22 -0.15399 0.85728 0.31970 -0.482 0.6300
concentration23 -0.26729 0.76545 0.31970 -0.836 0.4031
contaminant1 0.74756 2.11185 0.69261 1.079 0.2804
contaminant2 0.40921 1.50563 0.69438 0.589 0.5556
condition1 NA NA 0.00000 NA NA
condition2 NA NA 0.00000 NA NA
condition3 NA NA 0.00000 NA NA
condition4 0.53134 1.70120 0.76529 0.694 0.4875
pathogenpres1 NA NA 0.00000 NA NA
fam2 0.07799 1.08112 0.26550 0.294 0.7689
fam3 -0.03410 0.96647 0.28008 -0.122 0.9031
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Upvotes: 0
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