+ Reply to Thread
Results 1 to 1 of 1

Thread: unrestricted cumulative probit model with vglm()---extend to a multivariate setting?

  1. #1
    Points: 342, Level: 6
    Level completed: 84%, Points required for next Level: 8

    Posts
    9
    Thanks
    0
    Thanked 0 Times in 0 Posts

    unrestricted cumulative probit model with vglm()---extend to a multivariate setting?




    Hello. I'm trying to fit a multivariate, unrestricted cumulative probit model. I've had success in fitting a proportional odds probit model using polr(method="probit") in the MASS package and the unrestricted cumulative probit model using vglm(cumulative(link="probit)) in the VGAM package. I've only been able to do so with one response variable, though, but I'd really like to include two response variables in one model because they are not independent. Below, I've included the results of the two univariate cases using vglm(). If interested, you can access the data as a *.csv file. Also, the attached file describes the mathematical approach that I'm following as it relates to the data. Any suggestions are welcome. Thanks in advance.

    --Trey
    ************
    Trey Batey--Anthropology Instructor
    Mt. Hood Community College
    26000 SE Stark St.
    Gresham, OR 97030


    **********************************************
    > mod.pube3<-vglm(pube3~age,data=refdata,cumulative(link="probi t",parallel=FALSE,reverse=TRUE))
    > mod.pube3
    Call:
    vglm(formula = pube3 ~ age, family = cumulative(link = "probit",
    parallel = FALSE, reverse = TRUE), data = refdata)

    Coefficients:
    (Intercept):1 (Intercept):2 age:1 age:2
    -1.65895567 -2.14755951 0.06688242 0.04055919

    Degrees of Freedom: 1492 Total; 1488 Residual
    Residual Deviance: 1188.909
    Log-likelihood: -594.4543


    > mod.auric4<-vglm(auric4~age,data=refdata,cumulative(link="prob it",parallel=FALSE,reverse=TRUE))
    > mod.auric4
    Call:
    vglm(formula = auric4 ~ age, family = cumulative(link = "probit",
    parallel = FALSE, reverse = TRUE), data = refdata)

    Coefficients:
    (Intercept):1 (Intercept):2 (Intercept):3 age:1 age:2
    -2.07719235 -2.43422370 -2.99123098 0.07319632 0.05133132
    age:3
    0.03797696

    Degrees of Freedom: 2238 Total; 2232 Residual
    Residual Deviance: 1583.47
    Log-likelihood: -791.7348
    Attached Images

+ Reply to Thread

           




Tags for this Thread

Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts






Advertise on Talk Stats