nlme and geepack

[sahirbhatnagar]

Would you consider expanding this package to work on objects of class lme (from nlme) and objects of type geeglm (from geepack)?

[rubenarslan]

Here's what I currently substitute for your tidy.lme because it gives no confidence intervals. HTH, can also try a PR.

my_tidy.lme = function(fit, effects = "fixed") {
  if(effects == "fixed") {
    confintervals = data.frame(nlme::intervals(fit)$fixed)
    confintervals$term = rownames(confintervals)
    mydf = confintervals[confintervals$term != "(Intercept)", ]
    names(mydf) = c("conf.low", "estimate", "conf.high", "term")
    pvals = data.frame(nlme:::summary.lme(fit)$tTable)
    names(pvals) = c("estimate","std.error","df","statistic","p.value")
    pvals$term = rownames(pvals)
    mydf = merge(mydf, pvals[, c("term","p.value","std.error","statistic")], by = 'term')

    rownames(mydf) = NULL
    mydf = mydf[, c("term", "estimate", "std.error", "statistic", "p.value", "conf.low","conf.high")]
    mydf
  } else {
    stop("Only fixed effects implemented.")
  }
}

[mmulvahill]

If so, consider nlme::gls as well.

[sebpardo]

Expanding this package to work with nlme::lme and nlme::gls would be great!

[strengejacke]

Here are my tidiers for lme and gls, but only for fixed effects

#' @importFrom broom tidy
#' @importFrom tibble has_name
#' @importFrom sjstats p_value
#' @importFrom nlme intervals
tidy_lme_model <- function(model, ci.lvl) {
  # get tidy summary. for lme, this excludes CI,
  # so we compute them separately

  dat <- broom::tidy(model, conf.int = TRUE, conf.level = ci.lvl, effects = "fixed")
  ci <- as.data.frame(nlme::intervals(model, level = ci.lvl, which = "fixed")$fixed)

  dat$conf.low <- ci$lower
  dat$conf.high <- ci$upper

  # see if we have p-values. if not, add them
  if (!tibble::has_name(dat, "p.value"))
    dat$p.value <- sjstats::p_value(model)[["p.value"]]

  dat
}


#' @importFrom sjmisc var_rename
#' @importFrom nlme intervals
#' @importFrom dplyr select
#' @importFrom tibble rownames_to_column
tidy_gls_model <- function(model, ci.lvl) {
  # get tidy summary. for lme, this excludes CI,
  # so we compute them separately

  dat <- as.data.frame(summary(model)$tTable)
  ci <- as.data.frame(nlme::intervals(model, level = ci.lvl, which = "coef")$coef)

  dat$conf.low <- ci$lower
  dat$conf.high <- ci$upper


  sjmisc::var_rename(
    dat,
    Value = "estimate",
    Std.Error = "std.error",
    `t-value` = "statistic",
    `p-value` = "p.value"
  ) %>%
    tibble::rownames_to_column("term")
}

[alexpghayes]

At some point we gained tidy.geeglm(). Not sure if there are unmet requests for nlme tidiers in this thread, but if there are they belong in broom.mixed per #329. Linking in bbolker/broom.mixed#2 just in case.

[github-actions]

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