\title{trials on single-agent purine analogues for the treatment of chronic lymphocytic leukaemia}
\description{results from 4 trials evaluating single-agent purine analogues in patients with chronic lymphocytic leukaemia.}
\bold{ne}     \tab \code{integer}   \tab number of patients (purine antagonists) \cr
\bold{nc}     \tab \code{integer}   \tab number of patients (alkylator-based) \cr
\bold{hr}     \tab \code{numeric}   \tab hazard ratio \cr
\bold{lowhr}  \tab \code{numeric}   \tab lower limit \cr
\bold{upphr}  \tab \code{numeric}   \tab upper limit \cr
\bold{lnhr}   \tab \code{numeric}   \tab log hazard ratio \cr
\bold{selnhr} \tab \code{numeric}   \tab standard error
steurer et al. (2006) conducted a cochrane review to evaluate the effect of single-agent purine analogues for the treatment of chronic lymphocytic leukaemia. this dataset contains data from the main outcome, overall survival. note, the hazard ratios and confidence limits have been reported in the cochrane review with only two significant figures and were recalculated using the reported log hazard ratios and standard errors.
steurer, m., pall, g., richards, s., schwarzer, g., bohlius, j., & greil, r. (2006). purine antagonists for chronic lymphocytic leukaemia. \emph{cochrane database of systematic reviews}, \bold{3}, cd004270. \verb{https://doi.org/10.1002/14651858.cd004270.pub2}
m1 <- metagen(lnhr, selnhr, data = dat.steurer2006,
sm = "hr", random = false, n.e = ne, n.c = nc)
### same analysis using lower and upper confidence limits
m2 <- metagen(hr, lower = lowhr, upper = upphr,

\title{studies on adjuvant treatments to levodopa therapy for parkinson disease}
\description{results from 29 trials assessing efficacy of three drug classes as adjuvant treatment to levodopa therapy in patients with parkinson disease and motor complications.}
\bold{id}    \tab \code{integer}   \tab study id \cr
\bold{t1}    \tab \code{character} \tab treatment 1 \cr
\bold{y1}    \tab \code{numeric}   \tab treatment effect arm 1 \cr
\bold{sd1}   \tab \code{numeric}   \tab standard deviation arm 1 \cr
\bold{n1}    \tab \code{integer}   \tab sample size arm 1 \cr
\bold{t2}    \tab \code{character} \tab treatment 2 \cr
\bold{y2}    \tab \code{numeric}   \tab treatment effect arm 2 \cr
\bold{sd2}   \tab \code{numeric}   \tab standard deviation arm 2 \cr
\bold{n2}    \tab \code{integer}   \tab sample size arm 2 \cr
\bold{t3}    \tab \code{character} \tab treatment 3 \cr
\bold{y3}    \tab \code{numeric}   \tab treatment effect arm 3 \cr
\bold{sd3}   \tab \code{numeric}   \tab standard deviation arm 3 \cr
\bold{n3}    \tab \code{integer}   \tab sample size arm 3
this dataset contains data from a cochrane review assessing efficacy and safety of three drug classes as adjuvant treatment to levodopa therapy in patients with parkinson disease and motor complications (stowe et al., 2010).
the authors conducted three pairwise meta-analyses comparing dopamine agonists, catechol-o-methyl transferase inhibitors (comti), and monoamine oxidase type b inhibitors (maobi) with placebo. the primary outcome was the mean reduction of the time spent in a relatively immobile \squote{off} phase (mean off-time), calculated in hours per day. relative treatment effects were expressed as mean difference. data on this outcome were available for 5,331 patients from 28 studies comparing an active treatment with placebo and one three-arm study comparing two active treatments with placebo.
stowe, r., ives, n., clarke, c. e., deane, k., hilten, v., wheatley, k., gray, r., handley, k., & furmston, a. (2010). evaluation of the efficacy and safety of adjuvant treatment to levodopa therapy in parkinson's disease patients with motor complications. \emph{cochrane database of systematic reviews}, \bold{7}, cd007166. \verb{https://doi.org/10.1002/14651858.cd007166.pub2}
### show results from three studies (including three-arm study largo)
### print mean differences with two digits and standard errors with 3
oldset <- settings.meta(digits = 2, digits.se = 3)
pw <- pairwise(treat = list(t1, t2, t3), n = list(n1, n2, n3),
mean = list(y1, y2, y3), sd = list(sd1, sd2, sd3),
studlab = study, data = dat.stowe2010, sm = "md")
### show calculated mean differences (te) for three studies
selstudy <- c("comti(e) int-oz", "largo", "comti(e) nomecomt")
subset(pw, studlab \%in\% selstudy)[, c(3:7, 10, 1)]
netgraph(net, number = true, multiarm = true,
cex.number = 1, pos.number.of.studies = 0.3)
### forest plot showing all network estimates of active treatments
forest(net, ref = c("c", "d", "m"), baseline = false, drop = true)
### rankogram with all ranking probabilities
### league table showing network and direct estimates
netleague(net, seq = netrank(net), ci = false)