GGOFF Tests for Fractional Regression Models

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Description

frm.ggoff is used to test the specification of fractional regression models.

Usage

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frm.ggoff(object, version = "LM", table = T, ...)

Arguments

object

an object containing the results of an frm command.

version

a vector containing the test versions to use. Available options: Wald, LM (the default) and, only for the binary component of two-part models, LR. More than one option may be chosen.

table

a logical value indicating whether a summary table with the test results should be printed.

...

Arguments to pass to glm, which is used to estimate the model under the alternative hypothesis when version is a vector containing "Wald" or "LR".

Details

frm.ggoff applies the GGOFF, GOFF1 and GOOFF2 test statistics to fractional regression models estimated via frm. frm.ggoff may be used to test the link specification of: (i) one-part fractional regression models; (ii) the binary component of two-part fractional regression models; and (iii) the fractional component of two-part fractional regression models. When the Wald version is implemented, it is taken into account the option that was chosen for computing standard errors in the model under evaluation. For the LM version, a robust version is computed in cases (i) and (iii) and a conventional version in case (ii). See Ramalho, Ramalho and Murteira (2014) for details on the application of the GGOFF, GOFF1 and GOOFF2 tests in the fractional regression framework.

Value

frm.ggoff returns a named vector with the test results.

Author(s)

Joaquim J.S. Ramalho <jsr@uevora.pt>

References

Ramalho, E.A., J.J.S. Ramalho and J.M.R. Murteira (2014), "A generalized goodness-of-functional form test for binary and fractional regression models", Manchester School, 82(4), 488-507.

See Also

frm, for fitting fractional regression models.
frm.reset, for asymptotically equivalent specification tests.
frm.ptest, for non-nested hypothesis tests.
frm.pe, for computing partial effects.

Examples

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N <- 250
u <- rnorm(N)

X <- cbind(rnorm(N),rnorm(N))
dimnames(X)[[2]] <- c("X1","X2")

ym <- exp(X[,1]+X[,2]+u)/(1+exp(X[,1]+X[,2]+u))
y <- rbeta(N,ym*20,20*(1-ym))
y[y > 0.9] <- 1

#Testing the logit specification of a standard fractional regression model
#using LM and Wald versions of the GGOFF test, based on 1 or 2 fitted powers of
#the linear predictor
res <- frm(y,X,linkfrac="logit",table=FALSE)
frm.ggoff(res,c("Wald","LM"))

#Testing the probit specification of the binary component of a two-part fractional
#regression model using a LR-based GGOFF test
res <- frm(y,X,linkbin="probit",type="2Pbin",inf=1,table=FALSE)
frm.ggoff(res,"LR")

## See the website http://evunix.uevora.pt/~jsr/FRM.htm for more examples.