search for: waldtest

Dear All, I'm trying to use waldtest to test poolability (parameter stability) between two logistic regressions. Because I need to use robust standard errors (using sandwich), I cannot use anova. anova has no problems running the test, but waldtest does, indipendently of specifying vcov or not. waldtest does not appear to see that...

...ge, 'Kenneth Train's exercises using the mlogit package for R.' In spite of using the code unchanged, as well as the data used in the examples, I have been unable to run a Wald test to test two models. Specifically, I have run the following command, where mc and mi2 are fitted models: waldtest(mc,mi2) I think that the test is taken from the 'lmtest' package. I get the following error message: Error in terms.default(x) : no terms component The two fitted models are: mc <- mlogit(depvar ~ ic + oc, H, reflevel="hp") mi2 <- mlogit(depvar ~ oc + ic | income, H, refl...

Dear All, I'm looking to perform an ANOVA between two nested panel fixed effects models. I tried with anova, as well as with waldtest. anova tells me there is no method available for plm objects, while waldtest tells me my models are not nested. I think they are instead. The difference between the two models is that in the second I let the regression coefficients of a given variable variate according to a factor. MODEL 1 depFE.p...

...F.test (as it had to be). Unfortunately I could not find how to extract AIC from the result of systemfit, so I evaluated the ADF regression by lm. So far so good. However the results of ftest.systemfit and linear.hypothesis from the "car" package are very different, while the results from waldtest.systemfit and linear.hypothesis coincide. I have no explanation for this issue a nd I could not see the code of linear.hypothesis. When I type "linear.hypothesis" I get: function (model, ...) UseMethod("linear.hypothesis") <environment: namespace:car> but when I type &q...

I would like to try a likelihood ratio test in place of waldtest. Ideally I'd like to provide two glm models, the second a submodel of the first, in the style of lrt (http://www.pik-potsdam.de/~hrust/tools/farismahelp/lrt.html). [lrt takes farimsa objects] Does anyone know of such a likelihood ratio test? Chris Elsaesser, PhD Principal Scientist,...

...e) X.re=model.matrix(re) X.fe=model.matrix(fe) auxdata<-data.frame(cbind(y.re,X.re,X.fe)) colnames(auxdata)<-c("y", paste("x", 1:17, sep="")) auxmod<-lm(y~x1+x2+x3+x4+x5+x6+x7+x8+x9+x10+x11+x12+x13+x14+x15+x16+x17-1, auxdata) return(waldtest(auxmod, 10:17)[2,4]) } using the function above to choose between "fe" and "re" hmtest(re,fe) Error in solve(vc[ovar, ovar]) : subscript out of bounds Not sure what's gone wrong this time. I would appreciate your comments! -- View this message in context: http://r.78...

...sions of several new functions (and many helpful discussions), there is new functionality for the comparison of nested and non-nested linear models. For non-nested model comparisons, the Cox test, encompassing test and J test are now available. For nested model comparisons, there is the function waldtest() which allows convenient specification of the models and into which H(A)C estimates can be plugged. Thus, waldtest() can be seen as the `econometric' counterpart to the anova() method, just as coeftest() can be seen as the `econometric' counterpart of summary() for "lm" objects....

...sions of several new functions (and many helpful discussions), there is new functionality for the comparison of nested and non-nested linear models. For non-nested model comparisons, the Cox test, encompassing test and J test are now available. For nested model comparisons, there is the function waldtest() which allows convenient specification of the models and into which H(A)C estimates can be plugged. Thus, waldtest() can be seen as the `econometric' counterpart to the anova() method, just as coeftest() can be seen as the `econometric' counterpart of summary() for "lm" objects....

Does anyone know of a package that includes the Modified Sims test [Gewerke, 1983, Sims, 1972]? This test is used in econometrics and is a kind of alternative to the Granger test [Granger, 1969], which is in the package lmtest. Thanks in advance, chris Refernces: Gewerke, J., R. Meese, and W. Dent (1983), "Comparing Alternative Tests of Causality in Temporal Systems: Analytic Results and

...om the coxph.object, as well as the hazard ratio as follows: formula.obj = Surv(days, status) ~ type coxph.model = coxph(formula.obj, df) fit = summary(coxph.model) hazard.ratio = fit$conf.int[1] lower95 = fit$conf.int[3] upper95 = fit$conf.int[4] logrank.p.value = fit$sctest[3] wald.p.value = fit$waldtest[3] lr.p.value = fit$logtest[3] I had intended to report logrank P values with the hazard ratio and CI obtained from this function. In one case the P was 0.04 yet the CI crossed one, which confused me, and certainly will raise questions by reviewers. In retrospect I can see that the CI calculated...

...xt html latex example chm Bland.plot text html latex example Cook.plot text html latex example added.var.plot text html latex example jit.plot text html latex example waldtest text html latex example preparing package myfuncs for lazy loading Warning in list.files(lib, pattern = paste("^", pkg_regexp, sep = ""), full = TR UE) : list.files: '' is not a readable directory Error in findpack(package, li...

...t not all) useful methods is in Table 1 of vignette("betareg", package = "betareg"). For coef() and vcov() it is useful/important that the names and dimension match. Then Wald tests can be easily computed in functions like car::linearHypothesis(), car::deltaMethod(), lmtest::waldtest(), or lmtest::coeftest(). Thanks & best wishes, Achim > http://www.milbo.org/doc/modguide.pdf > > Your comments would be appreciated. > > Stephen Milborrow > > ______________________________________________ > R-package-devel at r-project.org mailing list > https://...

Hi all-- We are planning an intervention study for adolescent alcohol use, and I am planning to use simulations based on a hurdle model (using the hurdle() function in package pscl) for sample size estimation. The simulation code and power code are below -- note that at the moment the "power" code is just returning the coefficients, as something isn't working quite right. The

...you to look at the "Econometrics" view which has some remarks about Wald tests. > Ex. 1) Wald tests of linear hypotheses after max. likelihood or even after > a regression. "Wald" does not even appear in my standard R package on a > search. You might want to look at waldtest() and coeftest() in package lmtest. And you seem to have discovered linear.hypothesis() in package car. All three perform Wald tests, providing different means of specifying the hypothesis/alternative of the tests. > There's no comment in the lm help or optim help about what function > t...

Preface: this is a statistical question more than an R question. I have a vector of numbers (assume a regular time series). Within this time series, I have a set of regions of interest (all of different lengths) that I want to compare against a "baseline" (which is known). There is some autocorrelation involved. I would like to determine the "significance" of the

I am trying to get robust standard errors in a logistic regression. Is there any way to do it, either in car or in MASS? Thanks for the help, Celso [[alternative HTML version deleted]]

Hello R-users! I tried to find a package to run a CHOW TEST. As a reference package I found the STRUCCHANGE package. Do you know if it works well otherwise can you recommend a different one? Thanks, Bernd -- View this message in context: http://www.nabble.com/Chow-Test-tf3878416.html#a10990270 Sent from the R help mailing list archive at Nabble.com.

Hello! I would like to know if there are already programmed statistical tests for data under serial dependence, for example, considering the variance inflation factor? Thank you very much Best regards Rosa

Hi all, It seems that I can get White's (HC3) test using MASS. The syntax I used for the particular problem is anova(scireg3, white.adjust="hc3") where scireg3 is an object from the lm function. But, the anova summary table is all I get. I don't get the new estimates or standard errors correcting for heteroskedasticity. Is there a way to get that information? Thanks

...oups". This is similar to the example by Therneau & Grambsch in their book "Modeling survival data. Extending the Cox model", p. 47, except that I have interactions with many covariates that I would like to test jointly (and a frailty term). In S-plus there seems to be a function waldtest that does the job. Is there anything similar in R that I could use? Here is the code for my model. The covariates are a subset of all the covariates that I use. fit=coxph(Surv(tykesto, tyoll)~nainen*strata(group)+I(ika-mean(ika))*strata(group) +I(ika2-mean(ika2))*strata(group)+keski*strata(group)...