如何从lme，lmer，glmer向Latex提取回归结果？

我是适合lme，lmer和glmer的模特。 我需要使用summary（）对象构造表并将其导出到Latex来显示我的结果。 xtable，mtable和apsrtable不起作用。 我看到一个以前的帖子（下面的链接）和一个针对lme4对象的解决方案，但不是针对这些。

http://leftcensored.skepsi.net/2011/03/13/code-latex-tables-for-lme4-models/

这些是我适合的模型的两个例子：

lme(y ~  time, data, na.action=na.omit, method="REML", random = ~ 1 | subject, control=lmeControl(msMaxIter = 200, msVerbose = TRUE))

glmer(y ~ time + (time | subject), data, family=binomial(link = "logit"), REML=T, control=list(maxIter = 800, maxFN=1000, msVerbose = TRUE))

任何帮助？

谢谢

---

对于lme ，我的个人版本低于; 您可以使用其他类似的插件下载它，例如，将lme / lm / glm表的p值的Sexpr{}字符串解压缩为Dmisc

http://www.menne-biomed.de/download

这是非常个性化的，但如果我喜欢四舍五入真正有意义的数字很多。 对不起，包nlme做我需要的一切（并且超过lme / gaussian），所以还没有lme4版本。

"latex.summary.lme" <-
function(object, title="",parameter=NULL, file="",
  shadep=0.05,caption=NULL,label=NULL,ctable=FALSE,form=NULL,
  interceptp = FALSE, moredec=0, where="!htbp", ...) {
  # This function can be mis-used for gls models when an explicit
  # form is given
  options(Hverbose=FALSE)
  require('Hmisc')
  require('nlme')
  dd <- object$dims
  method <- object$method
  fixF <- object$call$fixed
  xtTab <- as.data.frame(object$tTable)
  sigp <- xtTab[,"p-value"]< shadep # cells that will be shaded
  if (!interceptp){
    sigp[1] <- FALSE # intercept will never be shaded
    # Replace small significances, discarding p-value for (Intercept)
    xtTab[1,"p-value"] = 1 # we do not show it anyway, easier formatting
  }
  pval <- format(zapsmall(xtTab[, "p-value"],4))
  pval[as.double(pval) < 0.0001] <- "$< .0001$"
  xtTab[, "p-value"] <- pval
  xtTab[,"t-value"] <- round(xtTab[,"t-value"],1)
  if (ncol(xtTab) == 5) # not for gls
    xtTab[,"DF"] <- as.integer(xtTab[,"DF"])
  # extract formula
  if (is.null(form)) {
    if (!is.null(object$terms)) {
      form=object$terms
    } else {
      form = formula(object)
    }
  }
  if (is.null(parameter)) {
    parameter=as.character(form[[2]])
  }
  if (any(wchLv <- (as.double(levels(xtTab[, "p-value"])) == 0))) {
      levels(xtTab[, "p-value"])[wchLv] <- "<.0001"
  }
  if (is.null(label))
    label <- lmeLabel("contr",form)
  form <- deparse(removeFormFunc(as.formula(form)),width.cutoff=500)

  form <- paste(sub('~','$\sim$ ',form),sep="")
  # All I( in factors are replaced with (This could be improved)
  row.names(xtTab) <- 
    gsub("I(","(",dimnames(object$tTable)[[1]])
  row.names(xtTab) <-  gsub("^2","texttwosuperior",row.names(xtTab))

  # Determine base level  
  levs <- lapply(object$contrasts,function(object) {dimnames(object)[[1]][1]})
  levnames <- paste(names(levs),levs,sep=" = ",collapse=", ")
  # Try to locate numeric covariables
#  v1 <- all.vars(formula(object))[-1]
## Changed 8.10.2008, not regression-tested
  v1 <- all.vars(form)[-1]
  numnames <- v1[is.na(match(v1,names(levs)))]
  if (length(numnames > 0)) {
    numnames <- paste(numnames," = 0",collapse=", ")
    levnames <- paste(levnames,numnames,sep=", ")
  }
  if (is.null(caption)){ # TODO: Allow %s substitution
    if (inherits(object,"lme"))
      md = "Mixed model (lme)" else
    if (inherits(object,"gls"))
      md = "Extended linear model (gls)" else
      md = "Linear model"
    caption <- paste(md," contrast table for emph{",
       parameter, "} (model ",form,
    "). The value in row (Intercept) gives the reference value for ",
      levnames,".",sep='')
  }
  caption.lot <- paste("Contrast table for ",parameter, " by ",
      levnames)
  ndec <- pmax(round(1-log10(xtTab[,2]+0.000001)+moredec),0)
  xtTab[,1] <- formatC(round(xtTab[,1],ndec))
  xtTab[,2] <- formatC(round(xtTab[,2],ndec))
  if (ncol(xtTab) == 5) {
    names(xtTab) <- c("Value","StdErr","DF","t","p")
    pcol = 5
  } else {# gls misuse
    names(xtTab) <- c("Value","StdErr","t","p")
    pcol = 4
  }
  # Only show intercept p/t when explicitely required
  if (!interceptp){
    xtTab[1,pcol-1] <- NA
    xtTab[1,pcol] <- ''
  }
  cellTex <- matrix(rep("", NROW(xtTab) * NCOL(xtTab)), nrow=NROW(xtTab))
  cellTex[sigp,pcol] <- "cellcolor[gray]{0.9}"
  rowlabel <- ifelse(nchar(parameter) >9,"",parameter)
  latex(xtTab, title=title, file=file, caption=caption,caption.lot=caption.lot,
    caption.loc="bottom", label=label, cellTexCmds = cellTex,
    rowlabel=rowlabel, ctable=ctable, where=where,
    booktabs = !ctable, numeric.dollar=FALSE,col.just=rep("r",5),...)
}

"latex.lme" <-
function(object, title="",parameter=NULL,file="",shadep=0.05,
  caption=NULL,label=NULL,ctable=FALSE,form=NULL,
  interceptp=FALSE,  moredec= 0, where="!htbp",...) {
  options(Hverbose=FALSE)
  require('Hmisc')
  require('nlme')
  latex.summary.lme(summary(object),title=title,parameter=parameter, 
    file=file, shadep=shadep, caption=caption,
    label=label, ctable=ctable, form=form, moredec=moredec, where=where,...)
}

---

我发现存在一个用于提供所有必要数据（用于固定效果）的summary.mer对象的coef方法。 返回的对象（在强制为data.frame ）可以轻松地移交给选择的格式化包（例如xtable或ascii ）。
看下面的例子（它只产生可用的data.frame ）：

require(lme4)

gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
              family = binomial, data = cbpp)

(res.table <- as.data.frame(coef(summary(gm1))))
##             Estimate Std. Error z value        Pr(>|z|)
## (Intercept)  -1.3985     0.2279  -6.137 0.0000000008416
## period2      -0.9923     0.3054  -3.249 0.0011562741408
## period3      -1.1287     0.3260  -3.462 0.0005368285553
## period4      -1.5804     0.4288  -3.686 0.0002282168737

---

编辑：

在编辑时，lme4软件包已更新，memisc不再适用于这些对象。 包texrac是一种替代方案。 我已经离开了这个答案，以防万一memisc得到更新，它又开始工作。

memisc软件包执行lme4表格：

以下是我写的一些代码片段：

GPusenonMH=lmer(GPEtc_c~Age.y+Measure+Gender+Marital2+Work2+(1|NHS), family="poisson", data=subset(lemurdata, Measure %in% c(1,3)))

model1=mtable(GPusetotal, GPuseMH, GPusenonMH, summary.stats=FALSE)

toLatex(model1)

如果你想要这些东西，显然你可以把summary.stats = TRUE。

请注意，默认情况下使用dcolumn和booktabs Latex软件包，以便将它们放入Latex序言中或使用帮助文件中的命令（useBooktabs = FALSE，useDcolumn = FALSE）关闭它们。

链接地址: http://www.djcxy.com/p/24991.html

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