Odds Ratio and OR CI

Howdy everyone



I?m trying to get Odds ratio and OR confidence intervals using a probit model, but I'm not getting.

 

Do you think you can help me?

 

I?m new with R L

 

naive                   = summary(glm(pcr.data[,7]~boldBeta_individual+pcr.data$age,family=binomial(link=probit)))

naive_answer            = c(naive$coefficients[,1:3])                           #naive estimates for

                                                                                #alpha (first 4 collumns: intercept; beta_intercept, beta_slope and age) and

                                                                                #and SE(last 4 collumns: intercept; beta_intercept, beta_slope and age)

 

OR.naive = exp(1.6*coef(naive))

 

(till here works, the problem is with the confidence interval)

 

I tried to get the Standard error from the variance, but I?m not sure if this can be done as I?ve done.

 

 

Var_coef <- 1.6^2*var(coef(naive))

SE_coef <- Var_coef/sqrt(nsample)                    ########## I thi k this is correct

 

OR.naive.inf <- exp(OR.naive - (1.96 * SE_coef))

OR.naive.sup <- exp(OR.naive + (1.96 * SE_coef))

 

if I used logit link I would get the CI with confint(na?ve) command, but with probit I don't think so. Is there a way?

 

What should I do?

 

 

 


Atenciosamente,
Rosa Oliveira

____________________________________________________________________________



Rosa Celeste dos Santos Oliveira, 

E-mail: rosita21 at gmail.com <mailto:rosita21 at gmail.com>
Tlm: +351 939355143 
Linkedin: https://pt.linkedin.com/in/rosacsoliveira <https://pt.linkedin.com/in/rosacsoliveira>
____________________________________________________________________________
"Many admire, few know"
Hippocrates