# [R] Frustration to get help R users group

John Fox jfox at mcmaster.ca
Tue Apr 23 14:26:37 CEST 2013

```Dear Champak Ishram,

It's not surprising that what you did doesn't work because the model specification and the arguments that you employed bear no relationship that I can discern to the sem() function in the sem() package.

I think that you're probably confusing the sem package with something else.

I hope this helps,
John

------------------------------------------------
John Fox
Sen. William McMaster Prof. of Social Statistics
Department of Sociology
McMaster University
http://socserv.mcmaster.ca/jfox/

On Tue, 23 Apr 2013 12:44:11 +1200
Champak Ishram <champak.ishram at gmail.com> wrote:
> Dear  R users/developers
> I requested help to solve the problem of formulating Multivariate Sample
> selection model by using Full Information Maximum Likelihood
> (FIML)estimation method. I could not get any response. I formulated the
> following code of FIML to analyse univariate sample selection problem.
>
> library (sem)
> library(nrmlepln)
>
> Selection equation
> ws = c(w1, w2, w3)
>
> # values of dependent variables in selection equations are binary  (1 and 0)
> zs = c(z1, z2, z3, z4, z5)
> # z1, z2, z3 continuous and z4 and z5 dummies explanatory variables in
> selection equation
>
> Level equation (extent of particular option use)
> ys = c(y1, y2, y3)
> # values of dependent variables are percentage with some zero cases
> xs = c(x1, x2, x3, x4, x5)
> # x1, x2, x3 continuous and x4 and x5 dummies dependent variables.
>
> #Note: The variables in both selection and level equations are mostly same.
>
>
>                     #Selection model
>
> models1 = 'w1 ~ 1 + zs'
>
>  # Level model
> model1 = 'w1 ~ 1 + zs|y1 ~ 1 + xs'
>
> fit.fiml = sem(model1, data=MyRdata, estimator="Fiml") # not sure "ML" or
> "Fiml"
> summary(fit.fiml)
>
> I greatly appreciate your help.
>
> Regards
> Champak Ishram
>
> 	[[alternative HTML version deleted]]
>
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