从lme、lmer、glmer到乳胶的提取回归结果如何？

我正在用lme、lmer和glmer为模型装配。我需要用summary（）对象构造表，并导出到Latex以显示结果。xtable、mtable和aprtable不工作。我在之前的一篇文章（下面的链接）中看到了lme4对象的解决方案，但没有看到这些对象的解决方案

以下是我正在安装的两个模型示例：

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))

有什么帮助吗

---

感谢lme的

lme

，我的个人版本如下；您可以将其与其他类似的插件一起下载，例如，从中提取lme/lm/glm表的p值的

\Sexpr{}

字符串作为Dmisc

这是非常个性化的，但是如果我非常喜欢舍入到真正的有效数字。对不起，包nlme做了所有我需要的（并且比lme/gaussian更多），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,...)
}

“latex.summary.lme”编辑：

编辑时，lme4包已更新，memisc不再使用这些对象。包texreg是另一种选择。我留下了这个答案，以防memisc更新后重新开始工作

该软件包包含4个表：

以下是我编写的一些代码的片段：

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)

显然，如果您想要任何这些东西，您可以将summary.stats=TRUE

请注意，默认情况下都会使用dcolumn和booktabs Latex软件包，因此可以将它们放在Latex前言中，或者使用帮助文件中的命令（useBooktabs=FALSE，useDcolumn=FALSE）将其关闭。
以下是我的解决方案：假设
fit
是lme模型的结果，例如
fit fit\u text属性（fit\u text）

您将看到类似于结构的结果。然后，您可以将摘要报告的某些组件保存到txt文件或Rdata文件中。
我刚刚发现，对于
summary.mer
对象存在一个
coef
方法，该方法提供了所有必要的数据（用于固定效果）。返回的对象（强制转换为
data.frame
）可以很容易地移交给所选的格式包（例如
xtable
或
ascii
）。

请参见以下示例（仅生成可用的
data.frame
）：

require（lme4）
谢谢你，迪特！这真的很有帮助。我在使用你的函数时出错了。你能帮我吗？错误是“error in
[.data.frame
（xtTab，“p-value”）：未定义的列被选中“这可能是语言问题吗？当您创建摘要时，请检查您的区域设置中是否存在列“p-value”（lme（..））（谢谢！
mtable
与我的GLMERs配合使用效果很好。帮助页面（
？mtable
）对于展示如何以比您在R中可能选择使用的更正式的术语重新标记变量和模型，它也非常有用
> fit_text <- unclass(fit)
> attributes(fit_text)

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