R/metahet.R

Defines functions metahet

Documented in metahet

metahet <- function(y, s2, data, n.resam = 1000){
  if(missing(y)) stop("please specify effect size.")
  if(missing(s2)) stop("please specify within-study variance.")
  if(!missing(data)){
    y <- eval(substitute(y), data, parent.frame())
    s2 <- eval(substitute(s2), data, parent.frame())
  }
  if(length(y) != length(s2) | any(s2 < 0)) stop("error in the input data.")
  n <- length(y)

  out0 <- metahet.base(y = y, s2 = s2)

  out.resam.param <- lapply(1:n.resam, function(o){
    y.temp <- rnorm(n, mean = out0$weighted.mean, sd = sqrt(s2))
    out.temp <- metahet.base(y.temp, s2)
    return(out.temp)
  })
  out.resam.param <- unlist(out.resam.param)

  out.resam.replace <- lapply(1:n.resam, function(o){
    temp <- sample(n, replace = TRUE)
    y.temp <- y[temp]
    s2.temp <- s2[temp]
    out.temp <- metahet.base(y.temp, s2.temp)
    return(out.temp)
  })
  out.resam.replace <- unlist(out.resam.replace)

  # the conventional methods
  Q <- out0$Q
  Q.resam.param <- out.resam.param[names(out.resam.param) == "Q"]
  names(Q.resam.param) <- NULL
  p.Q <- (sum(Q.resam.param > Q) + 1)/(n.resam + 1)
  p.Q.theo <- 1 - pchisq(Q, n - 1)

  Q.resam.replace <- out.resam.replace[names(out.resam.replace) == "Q"]
  names(Q.resam.replace) <- NULL
  ci.Q <- quantile(Q.resam.replace, probs = c(0.025, 0.975))

  tau2.DL <- out0$tau2.DL
  tau2.resam.replace <- out.resam.replace[names(out.resam.replace) == "tau2.DL"]
  names(tau2.resam.replace) <- NULL
  ci.tau2.DL <- quantile(tau2.resam.replace, probs = c(0.025, 0.975))

  H <- out0$H
  H.resam.replace <- out.resam.replace[names(out.resam.replace) == "H"]
  names(H.resam.replace) <- NULL
  ci.H <- quantile(H.resam.replace, probs = c(0.025, 0.975))

  I2 <- out0$I2
  I2.resam.replace <- out.resam.replace[names(out.resam.replace) == "I2"]
  names(I2.resam.replace) <- NULL
  ci.I2 <- quantile(I2.resam.replace, probs = c(0.025, 0.975))

  # absolute deviation based on weighted mean
  Qr <- out0$Qr
  Qr.resam.param <- out.resam.param[names(out.resam.param) == "Qr"]
  names(Qr.resam.param) <- NULL
  p.Qr <- (sum(Qr.resam.param > Qr) + 1)/(n.resam + 1)

  Qr.resam.replace <- out.resam.replace[names(out.resam.replace) == "Qr"]
  names(Qr.resam.replace) <- NULL
  ci.Qr <- quantile(Qr.resam.replace, probs = c(0.025, 0.975))

  tau2.r <- out0$tau2.r
  tau2.r.resam.replace <- out.resam.replace[names(out.resam.replace) == "tau2.r"]
  names(tau2.r.resam.replace) <- NULL
  ci.tau2.r <- quantile(tau2.r.resam.replace, probs = c(0.025, 0.975))

  Hr <- out0$Hr
  Hr.resam.replace <- out.resam.replace[names(out.resam.replace) == "Hr"]
  names(Hr.resam.replace) <- NULL
  ci.Hr <- quantile(Hr.resam.replace, probs = c(0.025, 0.975))

  Ir2 <- out0$Ir2
  Ir2.resam.replace <- out.resam.replace[names(out.resam.replace) == "Ir2"]
  names(Ir2.resam.replace) <- NULL
  ci.Ir2 <- quantile(Ir2.resam.replace, probs = c(0.025, 0.975))

  # absolute deviation based on weighted median
  Qm <- out0$Qm
  Qm.resam.param <- out.resam.param[names(out.resam.param) == "Qm"]
  names(Qm.resam.param) <- NULL
  p.Qm <- (sum(Qm.resam.param > Qm) + 1)/(n.resam + 1)

  Qm.resam.replace <- out.resam.replace[names(out.resam.replace) == "Qm"]
  names(Qm.resam.replace) <- NULL
  ci.Qm <- quantile(Qm.resam.replace, probs = c(0.025, 0.975))

  tau2.m <- out0$tau2.m
  tau2.m.resam.replace <- out.resam.replace[names(out.resam.replace) == "tau2.m"]
  names(tau2.m.resam.replace) <- NULL
  ci.tau2.m <- quantile(tau2.m.resam.replace, probs = c(0.025, 0.975))

  Hm <- out0$Hm
  Hm.resam.replace <- out.resam.replace[names(out.resam.replace) == "Hm"]
  names(Hm.resam.replace) <- NULL
  ci.Hm <- quantile(Hm.resam.replace, probs = c(0.025, 0.975))

  Im2 <- out0$Im2
  Im2.resam.replace <- out.resam.replace[names(out.resam.replace) == "Im2"]
  names(Im2.resam.replace) <- NULL
  ci.Im2 <- quantile(Im2.resam.replace, probs = c(0.025, 0.975))

  # output
  out <- NULL

  out$p.Q <- p.Q
  out$p.Q.theo <- p.Q.theo
  out$p.Qr <- p.Qr
  out$p.Qm <- p.Qm

  out$Q <- Q
  out$ci.Q <- ci.Q
  out$tau2.DL <- tau2.DL
  out$ci.tau2.DL <- ci.tau2.DL
  out$H <- H
  out$ci.H <- ci.H
  out$I2 <- I2
  out$ci.I2 <- ci.I2

  out$Qr <- Qr
  out$ci.Qr <- ci.Qr
  out$tau2.r <- tau2.r
  out$ci.tau2.r <- ci.tau2.r
  out$Hr <- Hr
  out$ci.Hr <- ci.Hr
  out$Ir2 <- Ir2
  out$ci.Ir2 <- ci.Ir2

  out$Qm <- Qm
  out$ci.Qm <- ci.Qm
  out$tau2.m <- tau2.m
  out$ci.tau2.m <- ci.tau2.m
  out$Hm <- Hm
  out$ci.Hm <- ci.Hm
  out$Im2 <- Im2
  out$ci.Im2 <- ci.Im2

  return(out)
}

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altmeta documentation built on Aug. 29, 2022, 9:07 a.m.