frm.reset: RESET Test for Fractional Regression Models

In frm: Regression Analysis of Fractional Responses

Description

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

Usage

frm.reset(object, lastpower.vec = 3, version = "LM", table = T, ...)

Arguments

object	an object containing the results of an frm command.
lastpower.vec	a numeric vector containing the maximum powers of the linear predictors to be used in RESET tests.
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.reset applies the RESET test statistic to fractional regression models estimated via frm. frm.reset 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 (2011) for details on the application of the RESET test in the fractional regression framework.

Value

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

Author(s)

Joaquim J.S. Ramalho <[e-mail]>

References

Ramalho, E.A., J.J.S. Ramalho and J.M.R. Murteira (2011), "Alternative estimating and testing empirical strategies for fractional regression models", Journal of Economic Surveys, 25(1), 19-68.

See Also

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

Examples

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 RESET test, based on 1 or 2 fitted powers of
#the linear predictor
res <- frm(y,X,linkfrac="logit",table=FALSE)
frm.reset(res,2:3,c("Wald","LM"))

#Testing the probit specification of the binary component of a two-part fractional
#regression model using LR-based RESET tests with quadratic and cubic fitted 
#powers of the linear predictor
res <- frm(y,X,linkbin="probit",type="2Pbin",inf=1,table=FALSE)
frm.reset(res,3,"LR")

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

Example output

*** RESET test ***

H0:  Fractional logit model

 Version Statistic p-value 
   LM(2)     0.127   0.722 
 Wald(2)     0.125   0.723 
   LM(3)     1.970   0.373 
 Wald(3)     1.387   0.500 


*** RESET test ***

H0:  Binary probit component of a two-part model

 Version Statistic p-value 
   LR(3)     0.559   0.756 

frm documentation built on May 2, 2019, 12:40 p.m.