version 0.4.0

DESCRIPTION

@@ -1,10 +1,10 @@
 Package: CoTiMA
 Type: Package
 Title: Continuous Time Meta-Analysis ('CoTiMA')
-Version: 0.3.9
-Date: 2021-04-13
+Version: 0.4.0
+Date: 2021-05-20
 Authors@R: c(person("Christian", "Dormann", role = c("aut","cph")),
-            person("Markus", "Homberg", email = "cotima@uni-mainz.de", role = c("ctb", "com", "cre")),
+            person("Markus", "Homberg", email = "cotima@uni-mainz.de", role = c("aut", "com", "cre")),
             person("Christina", "Guthier", role = c("ctb")),
             person("Manuel", "Voelkle", role = c("ctb")))    
 Description: The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from 
@@ -33,11 +33,11 @@ Suggests: R.rsp
 VignetteBuilder: R.rsp
 RoxygenNote: 7.1.1
 NeedsCompilation: no
-Packaged: 2021-04-13 15:39:43 UTC; comst
+Packaged: 2021-05-20 07:31:48 UTC; comst
 Author: Christian Dormann [aut, cph],
-  Markus Homberg [ctb, com, cre],
+  Markus Homberg [aut, com, cre],
   Christina Guthier [ctb],
   Manuel Voelkle [ctb]
 Maintainer: Markus Homberg <cotima@uni-mainz.de>
 Repository: CRAN
-Date/Publication: 2021-04-18 22:20:03 UTC
+Date/Publication: 2021-05-20 08:00:02 UTC

MD5

@@ -1,5 +1,5 @@
-5d6730ffff795da3297a22cd4bcdf850 *DESCRIPTION
-d03f6925e8140e70591d4915573c3823 *NAMESPACE
+ec8ef334d1c3b376780171cf008b5f06 *DESCRIPTION
+70024c23cd14e0c1d09c53e1a32fe029 *NAMESPACE
 8a681462471b608df8446d764c0e86ac *R/ctmaAllInvFit.R
 4b960c39da71171498b77ed259a949e8 *R/ctmaBiG.R
 dd1068a4812cc472605ecc3d134b3f02 *R/ctmaBiGOMX.R
@@ -8,17 +8,17 @@ dd1068a4812cc472605ecc3d134b3f02 *R/ctmaBiGOMX.R
 7597c3b8fa3e12874317b9d983d89dbe *R/ctmaCorRel.R
 ae33cf01b7839e1b759859acd50425ff *R/ctmaEmpCov.R
 6ef4089ad65f5f27d8ec3485d8ee68c4 *R/ctmaEqual.R
-cb702cdb970f430d1c2109c5f8a3644c *R/ctmaFit.R
+2c6889ed985abc00d0b775f0363c7e86 *R/ctmaFit.R
 f052499cdac481712d1fc2db52fa7f7f *R/ctmaFitList.R
 12e3ed7e0c4111fdc006c7af32c8f929 *R/ctmaFitToPrep.R
 efe9bee8980b4fe926c818eaf5b1aa97 *R/ctmaGetPub.R
-722047cbb7f989452dc0f6146f915b76 *R/ctmaInit.R
+a77223028673e38daa3fef356f24a24d *R/ctmaInit.R
 8e31bd47084b97cacce6b4820cac176f *R/ctmaLabels.R
 8e46da39489c6088aee7982a09a7939f *R/ctmaOptimizeInit.R
 f513abc4f046737c291b7250473828bb *R/ctmaPRaw.R
-8fc58a984295f1dcec035ecef55921f0 *R/ctmaPlot.R
+2b6d084b6b0dd6459339bd9c98428fef *R/ctmaPlot.R
 1a921a678410343cae4d625402cb3c7f *R/ctmaPlotContainer.R
-fa6a540b7874a5a59bb1cce9ed923ebc *R/ctmaPower.R
+d582ef7d217f6752ec1f807b33081870 *R/ctmaPower.R
 a9025a6b75fee47b1bc1f1e69bef5289 *R/ctmaPrep.R
 a7f9ad94b9f8f6c6f5cf99855f9eca8d *R/ctmaPub.R
 0dc04e18e0d3b4d0293346545e63fc97 *R/ctmaSV.R
@@ -27,7 +27,7 @@ a7f9ad94b9f8f6c6f5cf99855f9eca8d *R/ctmaPub.R
 998813c1d95739e25d2bf46f5f536ad4 *R/ctmaStanctArgs.R
 fafedd712fa9bfeeeb583b88dab43c01 *R/ctmaSummary.R
 3d93add62d15dacffbb51a852dfe9012 *R/data.R
-85a6d7f4ad8a8b559b4dc4ad8830d9ff *build/vignette.rds
+1d6ade7c2ac2e2b92aeaa6ef76f9eb9e *build/vignette.rds
 12a85c31602b913b0cc7796d0ddb8e00 *data/A128.rda
 7df6a0b7c34a85e13b4c187fb86d4d51 *data/A313.rda
 048088c12b67eabfbf0a8036ebd8c230 *data/CoTiMABiG_D_BO.rda
@@ -197,16 +197,16 @@ b02691caf57eaaded2884f7ae65cb188 *man/ctmaCompFit.Rd
 e57802650c898ce006bf5b65030a61b4 *man/ctmaCorRel.Rd
 a70e5bf9d1d595be2786aef21e3bd9dd *man/ctmaEmpCov.Rd
 29a94897f13980460cb11618b04e4306 *man/ctmaEqual.Rd
-8ef455722250f669423f6c70ccf2d968 *man/ctmaFit.Rd
+5f89f3d09f5af40681f0bb02bc138212 *man/ctmaFit.Rd
 9d66ae7375a4a5c9b1f36fd26ebff3c8 *man/ctmaFitList.Rd
 afda4a4aa921a31f6a009553df44a2d7 *man/ctmaFitToPrep.Rd
 92fa93ca54da95140cd79705122d2c2f *man/ctmaGetPub.Rd
-1d51c08a2d09804cfed5d1eddfbc317b *man/ctmaInit.Rd
+3b39ed05671fbdd24fe38635b1a344dd *man/ctmaInit.Rd
 f2186637377091d2c388d3c6e5c55204 *man/ctmaLabels.Rd
 849ce070379a0ba42c26c2030009d207 *man/ctmaOptimizeInit.Rd
 3fd3eb32bcbf50353fdadc5f60f9b9f8 *man/ctmaPRaw.Rd
 e9c4cddf39f84ae56b1cb02e174c5445 *man/ctmaPlot.Rd
-0e74fd5318b92eea62aa5763a4a2f0f4 *man/ctmaPower.Rd
+7894b84fcc0bb2dc0a4bccf4bddce3a1 *man/ctmaPower.Rd
 340d745f79bd36f5ef7106ad069d4a84 *man/ctmaPrep.Rd
 a6a1d65625f290f4324c5bdf5727586a *man/ctmaPub.Rd
 3ce95fecce6a370751ed014c070f9b13 *man/ctmaSV.Rd

NAMESPACE

@@ -46,6 +46,7 @@ importFrom(graphics,abline)
 importFrom(graphics,axis)
 importFrom(graphics,legend)
 importFrom(graphics,par)
+importFrom(graphics,plot)
 importFrom(graphics,plot.new)
 importFrom(graphics,polygon)
 importFrom(graphics,rect)

R/ctmaFit.R

@@ -111,7 +111,7 @@ ctmaFit <- function(
   chains=NULL,
   verbose=NULL,
   allInvModel=FALSE,
-  customPar=TRUE,
+  customPar=FALSE,
   inits=NULL
 )
 
@@ -973,8 +973,8 @@ ctmaFit <- function(
     startCol <- 2; startCol
     startRow <- 2; startRow
     openxlsx::writeData(wb, sheet2, startCol=startCol, startRow = startRow, colNames = FALSE,
-                        matrix(unlist(results$modelResults$DRIFT),
-                               nrow=1, ncol=n.latent^2, byrow=TRUE))
+                        c(t(matrix(unlist(results$modelResults$DRIFT),
+                               nrow=n.latent, ncol=n.latent))))
     startCol <- 1; startCol
     startRow <- 2; startRow
     openxlsx::writeData(wb, sheet2, startCol=startCol, startRow = startRow, colNames = FALSE,
@@ -987,9 +987,8 @@ ctmaFit <- function(
                         matrix(names(results$modelResults$DIFFUSION), nrow=1), colNames = FALSE)
     startCol <- 2; startCol
     startRow <- 2 + offset + 1# offset; startRow
-    results$modelResults
     openxlsx::writeData(wb, sheet2, startCol=startCol, startRow = startRow, colNames = FALSE,
-                        matrix(names(results$modelResults$DIFFUSION),
+                        matrix(results$modelResults$DIFFUSION,
                                nrow=1, byrow=TRUE))
     results$modelResults$DIFFUSION
     startCol <- 1; startCol

R/ctmaInit.R

@@ -90,7 +90,7 @@ ctmaInit <- function(
   chains=NULL,
   iter=NULL,
   verbose=NULL,
-  customPar=TRUE,
+  customPar=FALSE,
   doPar=1,
   useSV=TRUE
 )
@@ -316,6 +316,8 @@ ctmaInit <- function(
         relativeNDiff[[i]] <- tmp$relativeLostN
         lags[[i]] <- matrix(currentLags, nrow=dim(empraw[[i]])[1], ncol=currentTpoints-1, byrow=TRUE)
         empraw[[i]] <- cbind(empraw[[i]], lags[[i]]);
+        empraw[[i]]
+        currentVarnames
         colnames(empraw[[i]]) <- c(c(currentVarnames, paste0("dT", seq(1:(currentTpoints-1)))))
         empraw[[i]] <- as.data.frame(empraw[[i]])
 
@@ -442,6 +444,8 @@ ctmaInit <- function(
   } ### END Read user provided data and create list with all study information ###
 
   # Check if sample sizes specified in prep file deviate from cases provided in possible raw data files
+  N1 <- (unlist((lapply(empraw, function(extract) dim(extract)[1])))); N1
+  N2 <- (unlist(primaryStudies$sampleSizes)); N2
   N1 <- sum(unlist((lapply(empraw, function(extract) dim(extract)[1]))) , na.rm=TRUE); N1
   N2 <- sum(unlist(primaryStudies$sampleSizes), na.rm=TRUE); N2
   if (!(N1 == N2)) {

R/ctmaPlot.R

@@ -18,7 +18,7 @@
 #'
 #' @importFrom RPushbullet pbPost
 #' @importFrom crayon red
-#' @importFrom graphics plot.new polygon abline par rect axis title text legend
+#' @importFrom graphics plot plot.new polygon abline par rect axis title text legend
 #' @importFrom grDevices dev.copy png dev.off
 #' @importFrom OpenMx expm
 #' @importFrom stats quantile

R/ctmaPower.R

@@ -87,7 +87,7 @@ ctmaPower <- function(
   iter=NULL,
   chains=NULL,
   verbose=NULL,
-  customPar=TRUE
+  customPar=FALSE
 )
 
 {  # begin function definition (until end of file)