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| Package: mclogit | ||
| Type: Package | ||
| Title: Mixed Conditional Logit | ||
| Version: 0.2-7 | ||
| Date: 2013-09-19 | ||
| Version: 0.3-1 | ||
| Date: 2014-10-13 | ||
| Author: Martin Elff | ||
| Maintainer: Martin Elff <martin.elff@uni-konstanz.de> | ||
| Description: This packages provides a function to estimate parameters for the | ||
| mixed conditional logit model, or conditional logit with random effects. | ||
| The current implementation of random effects is limited to | ||
| Maintainer: Martin Elff <elff@gmx.com> | ||
| Description: This packages provides a function to estimate parameters for | ||
| the conditional logit model (also with multinomial counts), and for the | ||
| mixed conditional logit model, or conditional logit with random effects | ||
| (random intercepts only, no random slopes yet). | ||
| The current implementation of random effects is limited to | ||
| the PQL technique, which requires large cluster sizes. | ||
| License: GPL-2 | ||
| Depends: stats, memisc, Matrix | ||
| Depends: stats, Matrix | ||
| Enhances: memisc | ||
| LazyLoad: Yes | ||
| Packaged: 2013-09-20 12:11:40 UTC; elff | ||
| Packaged: 2014-10-13 21:17:58 UTC; elff | ||
| NeedsCompilation: no | ||
| Repository: CRAN | ||
| Date/Publication: 2013-09-20 14:58:31 | ||
| Date/Publication: 2014-10-14 05:27:20 |
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| anova.mclogit <- function (object, ..., dispersion = NULL, test = NULL) | ||
| { | ||
| dotargs <- list(...) | ||
| named <- if (is.null(names(dotargs))) | ||
| rep_len(FALSE, length(dotargs)) | ||
| else (names(dotargs) != "") | ||
| if (any(named)) | ||
| warning("the following arguments to 'anova.mclogit' are invalid and dropped: ", | ||
| paste(deparse(dotargs[named]), collapse = ", ")) | ||
| dotargs <- dotargs[!named] | ||
| is.mclogit <- vapply(dotargs, function(x) inherits(x, "mclogit") , | ||
| #&!inherits(x,"mclogitRandeff"), | ||
| NA) | ||
| dotargs <- dotargs[is.mclogit] | ||
| if (length(dotargs)) | ||
| return(anova.mclogitlist(c(list(object), dotargs), dispersion = dispersion, | ||
| test = test)) | ||
| stop("'anova.mclogit' can only be used to compare fitted models") | ||
| } | ||
|
|
||
| anova.mclogitlist <- function (object, ..., dispersion = NULL, test = NULL) | ||
| { | ||
| responses <- as.character(lapply(object, function(x) { | ||
| deparse(formula(x)[[2L]]) | ||
| })) | ||
| sameresp <- responses == responses[1L] | ||
| if (!all(sameresp)) { | ||
| object <- object[sameresp] | ||
| warning(gettextf("models with response %s removed because response differs from model 1", | ||
| sQuote(deparse(responses[!sameresp]))), domain = NA) | ||
| } | ||
| ns <- sapply(object, function(x) x$N) | ||
| if (any(ns != ns[1L])) | ||
| stop("models were not all fitted to the same size of dataset") | ||
| nmodels <- length(object) | ||
| if (nmodels == 1) stop("'anova.mclogit' can only be used to compare fitted models") | ||
|
|
||
| resdf <- as.numeric(lapply(object, function(x) x$residual.df)) | ||
| resdev <- as.numeric(lapply(object, function(x) x$deviance)) | ||
| table <- data.frame(resdf, resdev, c(NA, -diff(resdf)), c(NA, | ||
| -diff(resdev))) | ||
| variables <- lapply(object, function(x) paste(deparse(formula(x)), | ||
| collapse = "\n")) | ||
| dimnames(table) <- list(1L:nmodels, c("Resid. Df", "Resid. Dev", | ||
| "Df", "Deviance")) | ||
| title <- "Analysis of Deviance Table\n" | ||
| topnote <- paste("Model ", format(1L:nmodels), ": ", variables, | ||
| sep = "", collapse = "\n") | ||
| if (!is.null(test)) { | ||
| bigmodel <- object[[order(resdf)[1L]]] | ||
| df.dispersion <- Inf | ||
| table <- stat.anova(table = table, test = test, scale = 1, | ||
| df.scale = df.dispersion, n = bigmodel$N) | ||
| } | ||
| structure(table, heading = c(title, topnote), class = c("anova", | ||
| "data.frame")) | ||
| } | ||
|
|
||
|
|
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| getSummary.mclogit <- function(obj, | ||
| alpha=.05, | ||
| rearrange=NULL, | ||
| #as.columns=NULL, | ||
| ...){ | ||
|
|
||
| smry <- summary(obj) | ||
| N <- obj$N | ||
| coef <- smry$coefficients | ||
| varPar <- smry$varPar | ||
|
|
||
| lower.cf <- qnorm(p=alpha/2,mean=coef[,1],sd=coef[,2]) | ||
| upper.cf <- qnorm(p=1-alpha/2,mean=coef[,1],sd=coef[,2]) | ||
| coef <- cbind(coef,lower.cf,upper.cf) | ||
| colnames(coef) <- c("est","se","stat","p","lwr","upr") | ||
| if(length(varPar)){ | ||
| se.log.varPar <- varPar[,1]*varPar[,2] | ||
| lower.log.varPar <- qnorm(p=alpha/2,mean=log(varPar[,1]),sd=se.log.varPar[2]) | ||
| upper.log.varPar <- qnorm(p=1-alpha/2,mean=log(varPar[,1]),sd=se.log.varPar[2]) | ||
| varPar <- cbind(varPar,exp(lower.log.varPar),exp(upper.log.varPar)) | ||
| colnames(varPar) <- c("est","se","stat","p","lwr","upr") | ||
| rownames(varPar) <- paste("Var(",rownames(varPar),")",sep="") | ||
| } | ||
| if(length(rearrange)){ | ||
| coef.grps <- lapply(rearrange,function(ii){ | ||
| if(is.character(ii) && !all(ii %in% rownames(coef))) | ||
| stop("coefficient(s) ",dQuote(unname(ii[!(ii %in% rownames(coef))]))," do not exist") | ||
| structure(coef[ii,], | ||
| dimnames=list(names(ii),dimnames(coef)[[2]]) | ||
| ) | ||
| }) | ||
| grp.titles <- names(rearrange) | ||
| coef.grps <- do.call(memisc::collect,coef.grps) | ||
| coef <- array(NA,dim=c( | ||
| dim(coef.grps)[1] + NROW(varPar), | ||
| dim(coef.grps)[2], | ||
| dim(coef.grps)[3] | ||
| )) | ||
| coef[seq(dim(coef.grps)[1]),,] <- coef.grps | ||
| if(length(varPar)) | ||
| coef[dim(coef.grps)[1]+seq(nrow(varPar)),,1] <- varPar | ||
| dimnames(coef) <- list( | ||
| c(dimnames(coef.grps)[[1]],rownames(varPar)), | ||
| dimnames(coef.grps)[[2]], | ||
| grp.titles | ||
| ) | ||
| } | ||
| else { | ||
| .coef <- coef | ||
| coef <- matrix(NA,nrow=nrow(.coef)+NROW(varPar),ncol=ncol(.coef)) | ||
| coef[seq(nrow(.coef)),] <- .coef | ||
| if(length(varPar)) | ||
| coef[nrow(.coef)+seq(nrow(varPar)),] <- varPar | ||
| rownames(coef) <- c(rownames(.coef),rownames(varPar)) | ||
| colnames(coef) <- colnames(.coef) | ||
| } | ||
|
|
||
|
|
||
| phi <- smry$phi | ||
| LR <- smry$null.deviance - smry$deviance | ||
| df <- obj$model.df | ||
| deviance <- deviance(obj) | ||
|
|
||
|
|
||
| if(df > 0){ | ||
| p <- pchisq(LR,df,lower.tail=FALSE) | ||
| L0.pwr <- exp(-smry$null.deviance/N) | ||
| LM.pwr <- exp(-smry$deviance/N) | ||
|
|
||
| McFadden <- 1- smry$deviance/smry$null.deviance | ||
| Cox.Snell <- 1 - exp(-LR/N) | ||
| Nagelkerke <- Cox.Snell/(1-L0.pwr) | ||
| } | ||
| else { | ||
| LR <- NA | ||
| df <- NA | ||
| p <- NA | ||
| McFadden <- NA | ||
| Cox.Snell <- NA | ||
| Nagelkerke <- NA | ||
| } | ||
|
|
||
| ll <- obj$ll | ||
| AIC <- AIC(obj) | ||
| BIC <- AIC(obj,k=log(N)) | ||
| sumstat <- c( | ||
| phi = phi, | ||
| LR = LR, | ||
| df = df, | ||
| #p = p, | ||
| logLik = ll, | ||
| deviance = deviance, | ||
| McFadden = McFadden, | ||
| Cox.Snell = Cox.Snell, | ||
| Nagelkerke = Nagelkerke, | ||
| AIC = AIC, | ||
| BIC = BIC, | ||
| N = N | ||
| ) | ||
|
|
||
| #coef <- apply(coef,1,applyTemplate,template=coef.template) | ||
|
|
||
| #sumstat <- drop(applyTemplate(sumstat,template=sumstat.template)) | ||
| list(coef=coef,sumstat=sumstat) | ||
| } |
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