\title{studies on anti-tnf-alpha inhibitors in rheumatoid arthritis}
\description{results from 16 studies evaluating anti-tnf-alpha inhibitors in patients with rheumatoid arthritis.}
\bold{author}    \tab \code{character} \tab first author \cr
\bold{year}      \tab \code{integer} \tab publication year \cr
\bold{mean.das}  \tab \code{numeric} \tab mean for outcome das-28 \cr
\bold{lower.das} \tab \code{numeric} \tab lower limit for outcome das-28 \cr
\bold{upper.das} \tab \code{numeric} \tab upper limit for outcome das-28 \cr
\bold{mean.haq}  \tab \code{numeric} \tab mean for outcome haq \cr
\bold{lower.haq} \tab \code{numeric} \tab lower limit for outcome haq \cr
\bold{upper.haq} \tab \code{numeric} \tab upper limit for outcome haq \cr
\bold{n}         \tab \code{integer} \tab sample size
lloyd et al. (2010) report results of a systematic review evaluating the effectiveness of anti-tnf-alpha inhibitors in the treatment of rheumatoid arthritis. the authors conducted separate meta-analyses for haq and das-28.
lloyd, s., bujkiewicz, s., wailoo, a. j., sutton, a. j., & scott, d. (2010). the effectiveness of anti-tnf-\eqn{\alpha} therapies when used sequentially in rheumatoid arthritis patients: a systematic review and meta-analysis. \emph{rheumatology}, \bold{49}(12), 2313--2321. \verb{https://doi.org/10.1093/rheumatology/keq169}
### only consider studies providing data for both outcomes
lloyd5 <- subset(dat.lloyd2010, !is.na(mean.haq) & !is.na(mean.das))
### univariate meta-analysis of the das-28 outcome
### univariate meta-analysis of the haq outcome
forest(m.das, test.overall = true, hetstat = false,
forest(m.haq, test.overall = true, hetstat = false,
medicine, rheumatology, raw mean differences

\title{studies on the effectiveness of cbt for depression}
\description{results from 76 studies examining the effectiveness of cognitive behavioral therapy (cbt) for depression in adults.}
\bold{study}     \tab \code{character} \tab (first) author and year of study \cr
\bold{treatment} \tab \code{character} \tab treatment provided (see \squote{details}) \cr
\bold{scale}     \tab \code{character} \tab scale used to measure depression symptoms \cr
\bold{n}         \tab \code{numeric}   \tab group size \cr
\bold{diff}      \tab \code{numeric}   \tab standardized mean change \cr
\bold{se}        \tab \code{numeric}   \tab corresponding standard error \cr
\bold{group}     \tab \code{numeric}   \tab type of therapy (0 = individual, 1 = group therapy) \cr
\bold{tailored}  \tab \code{numeric}   \tab whether the intervention was tailored to each patient (0 = no, 1 = yes) \cr
\bold{sessions}  \tab \code{numeric}   \tab number of sessions \cr
\bold{length}    \tab \code{numeric}   \tab average session length (in minutes) \cr
\bold{intensity} \tab \code{numeric}   \tab product of sessions and length \cr
\bold{multi}     \tab \code{numeric}   \tab intervention included multimedia elements (0 = no, 1 = yes) \cr
\bold{cog}       \tab \code{numeric}   \tab intervention included cognitive techniques (0 = no, 1 = yes) \cr
\bold{ba}        \tab \code{numeric}   \tab intervention included behavioral activation (0 = no, 1 = yes) \cr
\bold{psed}      \tab \code{numeric}   \tab intervention included psychoeducation (0 = no, 1 = yes) \cr
\bold{home}      \tab \code{numeric}   \tab intervention included homework (0 = no, 1 = yes) \cr
\bold{prob}      \tab \code{numeric}   \tab intervention included problem solving (0 = no, 1 = yes) \cr
\bold{soc}       \tab \code{numeric}   \tab intervention included social skills training (0 = no, 1 = yes) \cr
\bold{relax}     \tab \code{numeric}   \tab intervention included relaxation (0 = no, 1 = yes) \cr
\bold{goal}      \tab \code{numeric}   \tab intervention included goal setting (0 = no, 1 = yes) \cr
\bold{final}     \tab \code{numeric}   \tab intervention included a final session (0 = no, 1 = yes) \cr
\bold{mind}      \tab \code{numeric}   \tab intervention included mindfulness (0 = no, 1 = yes) \cr
\bold{act}       \tab \code{numeric}   \tab intervention included acceptance and commitment therapy (0 = no, 1 = yes)
the dataset includes the results from 76 studies examining the effectiveness of cognitive behavioral therapy (cbt) for treating depression in adults. studies included two or more of the following treatments/conditions:
\item psychological or attention placebo,
\item hybrid cbt (i.e., multimedia cbt with one or more face-to-face sessions).
multimedia cbt was defined as cbt delivered via self-help books, audio/video recordings, telephone, computer programs, apps, e-mail, or text messages.
variable \code{diff} is the standardized mean change within each group, with negative values indicating a decrease in depression symptoms.
lópez-lópez, j. a., davies, s. r., caldwell, d. m., churchill, r., peters, t. j., tallon, d., dawson, s., wu, q., li, j., taylor, a., lewis, g., kessler, d. s., wiles, n., & welton, n. j. (2019). the process and delivery of cbt for depression in adults: a systematic review and network meta-analysis. \emph{psychological medicine}, \bold{49}(12), 1937--1947. \verb{https://doi.org/10.1017/s003329171900120x}
sapply(split(dat$treatment, dat$study), function(x) t(combn(x,2)))), stringsasfactors=false)
layout=layout_in_circle(g, order=c("wait list", "no treatment", "tau", "multimedia cbt",
dat <- to.wide(dat, study="study", grp="treatment", ref="tau",
### compute contrasts between treatment pairs and corresponding sampling variances
### calculate the variance-covariance matrix for multitreatment studies
v <- matrix(x$se2[1]^2, nrow=nrow(x), ncol=nrow(x))
dat <- contrmat(dat, grp1="treatment1", grp2="treatment2")
### the treatment left out (tau) becomes the reference level for the treatment comparisons
mods = ~ 0 + no.treatment + wait.list + placebo + f2f.cbt + hybrid.cbt + multimedia.cbt,
### forest plot of the contrast estimates (treatments versus tau)
forest(coef(res1), diag(vcov(res1)), slab=sub(".", " ", names(coef(res1)), fixed=true),
xlab="difference in standardized mean change (compared to tau)")
### fit random inconsistency effects model (might have to switch optimizer to get convergence)
random = list(~ comp | study, ~ comp | design), rho=1/2, phi=1/2,
### likelihood ratio test comparing the two models
### collapse the different cbt forms into a single category
dat$cbt <- with(dat, ifelse(f2f.cbt + hybrid.cbt + multimedia.cbt > 0, 1, 0))
### fit the model with this treatment indicator
mods = ~ 0 + no.treatment + wait.list + placebo + cbt,
### component network meta-analysis (effect of cbt may be larger/smaller depending on
### the presence of various components; leaving out 'mind' and 'act' as in the paper)
mods = ~ 0 + no.treatment + wait.list + placebo + cbt +
cbt:(multi + cog + ba + psed + home + prob + soc + relax + goal + final),
rownames <- sub(".", " ", rownames, fixed=true)
rownames[5:14] <- c("multimedia", "cognitive techniques", "behavioral activiation",
"psycheducation", "homework", "problem solving", "social skills training",
"relaxation", "goal setting", "final session")
psychiatry, standardized mean changes, network meta-analysis