added 'BucherEtAl1997' data

DESCRIPTION

@@ -2,7 +2,7 @@ Package: bayesmeta
 Type: Package
 Title: Bayesian Random-Effects Meta-Analysis and Meta-Regression
 Version: 2.8
-Date: 2021-08-23
+Date: 2021-08-31
 Authors@R: c(person(given="Christian", family="Roever", role=c("aut","cre"), 
                     email="christian.roever@med.uni-goettingen.de",
                     comment=c(ORCID="0000-0002-6911-698X")),

data/BucherEtAl1997.R

+# Data from:
+#
+#   H. C. Bucher et al.
+#   The results of direct and indirect treatment comparisons 
+#   in meta-analysis of randomized controlled trials
+#   Journal of Clinical Epidemiology, 50(6):683-691, 1997.
+#   https://doi.org/10.1016/S0895-4356(97)00049-8
+#
+#   Table 1
+#
+
+BucherEtAl1997 <- cbind.data.frame("study"   =c("Antinori (1992)", "Mallolas (1992)", "Tocchetti (1994)",
+                                                "Bozzette (1995)", "Blum (1995)", "Podzamczer (1993)",
+                                                "Podzamczer (1995)", "Sirera (1995)",
+                                                "Slavin (1992)", "Girard (1993)", "Torres (1993)",
+                                                "Opravil (1995)", "Salmon (1995)",
+                                                "Rozenbaum (1991)", "Hardy (1992)", "Schneider (1992)",
+                                                "Smith (1992)", "Michelet (1993)", "May (1993)",
+                                                "Stellini (1994)", "Nielsen (1995)", "Rizzardi (1995)"),
+                                   "treat.A" =factor(rep(c("TMP-SMX", "AP",  "TMP-SMX"), c(8,5,9)),
+                                                     levels=c("TMP-SMX", "D/P", "AP")),
+                                   "treat.B" =factor(rep(c("D/P",     "D/P", "AP"),      c(8,5,9)),
+                                                    levels=c("TMP-SMX", "D/P", "AP")),
+                                   "events.A"=c(1, 3, 0, 42, 1, 3, 0, 6,
+                                                8, 10, 15, 13, 12,
+                                                0, 14, 0, 3, 1, 2, 0, 1, 5),
+                                   "total.A" =c(66, 107, 15, 276, 39, 81, 104, 115,
+                                                46, 176, 152, 242, 102,
+                                                29, 154, 142, 27, 53, 108, 26, 47, 95),
+                                   "events.B"=c(9, 8, 1, 41, 1, 13, 6, 9,
+                                                9, 10, 15, 12, 5,
+                                                1, 36, 6, 6, 4, 5, 2, 8, 6),
+                                   "total.B" =c(63, 116, 15, 288, 47, 85, 96, 105,
+                                                50, 173, 126, 291, 92,
+                                                27, 156, 71, 26, 55, 106, 23, 48, 101),
+                                   stringsAsFactors=FALSE)

man/BucherEtAl1997.Rd

+\name{BucherEtAl1997}
+\docType{data}
+\alias{BucherEtAl1997}
+\title{Direct and indirect comparison example data}
+\description{Numbers of subjects and events in the different treatment arms of 22 studies.}
+\usage{data("BucherEtAl1997")}
+\format{The data frame contains the following columns:
+  \tabular{lll}{
+    \bold{study}        \tab \code{character} \tab publication identifier (first author and publication year) \cr
+    \bold{treat.A}      \tab \code{factor}    \tab treatment in first study arm (\dQuote{TMP-SMX} or \dQuote{AP}) \cr
+    \bold{treat.B}      \tab \code{factor}    \tab treatment in second study arm (\dQuote{D/P} or \dQuote{AP}) \cr
+    \bold{events.A}     \tab \code{numeric}   \tab number of events in first study arm \cr
+    \bold{events.B}     \tab \code{numeric}   \tab number of events in second study arm \cr
+    \bold{total.A}      \tab \code{numeric}   \tab total number of patients in first study arm \cr
+    \bold{total.B}      \tab \code{numeric}   \tab total number of patients in second study arm \cr
+  }
+}
+\details{Bucher \emph{et al.} (1997) discussed the example case of the
+  comparison of \emph{sulphametoxazole-trimethoprim (TMP-SMX)} versus
+  \emph{dapsone/pyrimethamine (D/P)} for the prophylaxis of
+  \emph{Pneumocystis carinii} pneumonia in HIV patients. Eight
+  studies had undertaken a head-to-head comparison of both medications,
+  but an additional 14 studies were available investigating one of the
+  two medications with \emph{aerosolized pentamidine (AP)} as a
+  comparator. Nine studies compared TMP-SMX vs. AP, and five studies
+  compared D/P vs. AP. Together these provide \emph{indirect} evidence
+  on the effect of TMP-SMX compared to D/P.
+
+  The example constitutes a simple case of a \emph{network meta-analysis
+  (NMA)} setup, where only two-armed studies are considered, and
+  analysis is based on pairwise comparisons of treatments (or
+  \emph{contrasts}). In this case, the joint analysis of \emph{direct}
+  and \emph{indirect} evidence may be implemented as a special case of a
+  meta-regression (Higgins \emph{et al.}, 2019; Sec. 11.4.2).
+  The original data in fact included some three-armed studies, in which
+  case one of the arms was deliberately omitted (Bucher \emph{et al.}; 1997).
+}
+\source{H.C. Bucher, G.H. Guyatt, L.E. Griffith, S.D. Walter.
+  The results of direct and indirect treatment comparisons 
+  in meta-analysis of randomized controlled trials.
+  \emph{Journal of Clinical Epidemiology}, \bold{50}(6):683-691, 1997.
+  \doi{10.1016/S0895-4356(97)00049-8}.
+}
+\references{J.P.T. Higgins, J. Thomas, J. Chandler, M. Cumpston, T. Li,
+  M.J. Page, V.A. Welch (eds.).
+  \emph{Cochrane handbook for systematic reviews of interventions}.
+  Wiley and Sons, 2nd edition, 2019.
+  \doi{10.1002/9781119536604}.
+  \url{http://handbook.cochrane.org/}.
+}
+\examples{
+# load data:
+data("BucherEtAl1997")
+
+# show data:
+head(BucherEtAl1997)
+
+\dontrun{
+# compute effect sizes (log-ORs for pairwise comparisons)
+# from the count data:
+es <- escalc(measure="OR",
+             ai=events.A, n1i=total.A,   # "exposure group"
+             ci=events.B, n2i=total.B,   # "control group"
+             slab=study, data=BucherEtAl1997)
+
+# specify regressor matrix:
+X <- cbind("TMP.DP" = rep(c(1, 0, 1), c(8,5,9)),
+           "AP.DP"  = rep(c(0, 1,-1), c(8,5,9)))
+
+# perform Bayesian meta-regression:
+bmr01 <- bmr(es, X=X)
+
+# show default output:
+print(bmr01)
+
+# specify contrast matrix:
+contrastX <- rbind("TMP-SMX vs. D/P"=c(1,0),
+                   "AP vs. D/P"     =c(0,1),
+                   "TMP-SMX vs. AP" =c(1,-1))
+# show summary including contrast estimates:
+summary(bmr01, X.mean=contrastX)
+# show forest plot including contrast estimates:
+forestplot(bmr01, X.mean=contrastX, xlab="log-OR")
+
+
+# perform frequentist meta-regression:
+fmr01 <- rma(es, mods=X, intercept=FALSE)
+print(fmr01)
+
+# compare Bayesian and frequentist results;
+# estimated log-OR for "TMP-SMX" vs. "D/P"
+rbind("bayesmeta"=bmr01$summary[c("mean","sd"),"TMP.DP"],
+      "rma"      =c(fmr01$beta["TMP.DP",], fmr01$se[1]))
+
+# estimated log-OR for "AP" vs. "D/P"
+rbind("bayesmeta"=bmr01$summary[c("mean","sd"),"AP.DP"],
+      "rma"      =c(fmr01$beta["AP.DP",], fmr01$se[2]))
+
+# estimated heterogeneity:
+rbind("bayesmeta"=bmr01$summary["median","tau"],
+      "rma"      =sqrt(fmr01$tau2))
+}
+}
+\keyword{datasets}

man/bayesmeta-package.Rd

@@ -17,7 +17,7 @@
     Package: \tab bayesmeta\cr
     Type:    \tab Package\cr
     Version: \tab 2.8\cr
-    Date:    \tab 2021-08-23\cr
+    Date:    \tab 2021-08-31\cr
     License: \tab GPL (>=2)
   }
   The main functionality is provided by the \code{\link{bayesmeta}()}