grfpsim
2025-11-05
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library(mlVAR)## Warning: package 'mlVAR' was built under R version 4.4.3library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionIncluding Plots
You can also embed plots, for example:
## Estimating temporal and between-subjects effects## | | | 0% | |============== | 20% | |============================ | 40% | |========================================== | 60% | |======================================================== | 80% | |======================================================================| 100%## Warning in lmer_mlVAR(PredModel, augData, idvar, verbose = verbose,
## contemporaneous = contemporaneous, : Zero SD found in mean of following
## variables: suppression - Between-subject effects could not be estimated## Estimating contemporaneous effects## | | | 0% | |============== | 20% | |============================ | 40% | |========================================== | 60% | |======================================================== | 80% | |======================================================================| 100%## Computing random effects## | | | 0% | |==== | 6% | |======== | 11% | |============ | 17% | |================ | 22% | |=================== | 28% | |======================= | 33% | |=========================== | 39% | |=============================== | 44% | |=================================== | 50% | |======================================= | 56% | |=========================================== | 61% | |=============================================== | 67% | |=================================================== | 72% | |====================================================== | 78% | |========================================================== | 83% | |============================================================== | 89% | |================================================================== | 94% | |======================================================================| 100%## List of 7
## $ results:List of 6
## ..$ mu :List of 7
## .. ..- attr(*, "class")= chr [1:2] "mlVARarray" "list"
## ..$ Gamma_Omega_mu:List of 6
## .. ..- attr(*, "class")= chr [1:2] "mlVARarray" "list"
## ..$ Omega_mu :List of 4
## .. ..- attr(*, "class")= chr [1:2] "mlVarCov" "list"
## ..$ Beta :List of 7
## .. ..- attr(*, "class")= chr [1:2] "mlVARarray" "list"
## ..$ Theta :List of 4
## .. ..- attr(*, "class")= chr [1:2] "mlVarCov" "list"
## ..$ Gamma_Theta :List of 7
## .. ..- attr(*, "class")= chr [1:2] "mlVARarray" "list"
## $ output :List of 2
## ..$ temporal :List of 5
## ..$ contemporaneous:List of 5
## $ fit :'data.frame': 5 obs. of 3 variables:
## ..$ var: chr [1:5] "cortisol" "affect_neg" "stress" "reappraisal" ...
## ..$ aic: num [1:5] 1287 1331 1372 1399 1464
## ..$ bic: num [1:5] 1422 1466 1508 1535 1600
## $ data : tibble [504 × 18] (S3: tbl_df/tbl/data.frame)
## ..- attr(*, "na.action")= 'omit' Named int [1:126] 1 6 11 16 21 26 31 36 41 46 ...
## .. ..- attr(*, "names")= chr [1:126] "1" "6" "11" "16" ...
## $ model :'data.frame': 45 obs. of 5 variables:
## ..$ dep : chr [1:45] "cortisol" "affect_neg" "stress" "reappraisal" ...
## ..$ pred : chr [1:45] "cortisol" "cortisol" "cortisol" "cortisol" ...
## ..$ lag : num [1:45] 1 1 1 1 1 1 1 1 1 1 ...
## ..$ type : chr [1:45] "within" "within" "within" "within" ...
## ..$ predID: chr [1:45] "Predictor__1" "Predictor__1" "Predictor__1" "Predictor__1" ...
## ..- attr(*, "out.attrs")=List of 2
## $ input :List of 6
## ..$ vars : chr [1:5] "cortisol" "affect_neg" "stress" "reappraisal" ...
## ..$ lags : num 1
## ..$ compareToLags: num 1
## ..$ estimator : chr "lmer"
## ..$ temporal : chr "correlated"
## ..$ AR : logi FALSE
## $ IDs : chr [1:18] "1" "2" "3" "4" ...
## - attr(*, "class")= chr "mlVAR"## [1] "mean" "SD" "lower" "upper" "SE" "P" "subject"## NULL## List of 7
## $ mean : num [1:5, 1:5, 1] -0.0353 0.0552 0.025 -0.1036 0.069 ...
## ..- attr(*, "dimnames")=List of 3
## $ SD : num [1:5, 1:5, 1] 0.106 0.183 0.199 0.114 0.226 ...
## ..- attr(*, "dimnames")=List of 3
## $ lower : num [1:5, 1:5, 1] -0.1366 -0.0704 -0.1088 -0.216 -0.0802 ...
## ..- attr(*, "dimnames")=List of 3
## $ upper : num [1:5, 1:5, 1] 0.06601 0.18082 0.15892 0.00867 0.21818 ...
## ..- attr(*, "dimnames")=List of 3
## $ SE : num [1:5, 1:5, 1] 0.0517 0.0641 0.0683 0.0573 0.0761 ...
## ..- attr(*, "dimnames")=List of 3
## $ P : num [1:5, 1:5, 1] 0.4945 0.3891 0.714 0.0705 0.3645 ...
## ..- attr(*, "dimnames")=List of 3
## $ subject:List of 18
## ..$ : num [1:5, 1:5, 1] 0.0554 0.0231 -0.0884 -0.111 0.0778 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.04657 -0.10753 -0.25466 0.00448 -0.32942 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0134 0.1691 0.2338 -0.0863 0.1906 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0612 0.2116 0.2004 -0.0218 0.1656 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.127425 0.005682 -0.091337 -0.089221 0.000761 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] 0.0444 -0.1526 -0.1426 -0.0266 0.1583 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.08062 0.02278 0.00364 -0.09773 0.0794 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] 0.00151 -0.0713 -0.1804 -0.14489 -0.04422 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0051 0.0927 0.1218 -0.1524 0.1938 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0333 0.2613 0.0631 -0.233 0.1808 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.1118 0.1459 0.1684 -0.0693 0.2324 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0135 0.1968 0.0801 -0.1976 0.2985 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0831 0.2405 0.1348 -0.0821 0.0148 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] 0.0539 -0.1236 0.0461 -0.2495 0.251 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0522 -0.0809 -0.057 -0.059 -0.0338 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.0915 0.2478 0.2735 -0.0869 0.1286 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] 0.0312 -0.1731 -0.1234 -0.0761 -0.2114 ...
## .. ..- attr(*, "dimnames")=List of 3
## ..$ : num [1:5, 1:5, 1] -0.1022 0.0854 0.0629 -0.0868 -0.1114 ...
## .. ..- attr(*, "dimnames")=List of 3
## - attr(*, "class")= chr [1:2] "mlVARarray" "list"## , , 1
##
## cortisol affect_neg stress reappraisal suppression
## cortisol -0.03531390 0.04903194 -0.029656760 -0.05159609 0.024678910
## affect_neg 0.05520219 0.07842568 -0.009902418 -0.10545789 0.089683186
## stress 0.02503876 0.08001153 -0.059000336 -0.07968394 0.066050348
## reappraisal -0.10364378 -0.24789123 0.082064474 0.24699320 -0.018424159
## suppression 0.06901249 0.18675764 -0.069893819 -0.13207991 0.007014656## Warning: package 'qgraph' was built under R version 4.4.3## num [1:5, 1:5, 1] -0.0353 0.0552 0.025 -0.1036 0.069 ...
## - attr(*, "dimnames")=List of 3
## ..$ : chr [1:5] "cortisol" "affect_neg" "stress" "reappraisal" ...
## ..$ : chr [1:5] "cortisol" "affect_neg" "stress" "reappraisal" ...
## ..$ : chr "1"## cortisol affect_neg stress reappraisal suppression
## cortisol -0.03531390 0.04903194 -0.029656760 -0.05159609 0.024678910
## affect_neg 0.05520219 0.07842568 -0.009902418 -0.10545789 0.089683186
## stress 0.02503876 0.08001153 -0.059000336 -0.07968394 0.066050348
## reappraisal -0.10364378 -0.24789123 0.082064474 0.24699320 -0.018424159
## suppression 0.06901249 0.18675764 -0.069893819 -0.13207991 0.007014656
Note that the echo = FALSE parameter was added to the
code chunk to prevent printing of the R code that generated the
plot.
time_labels <- paste0(rep(vars, each = 6), "_t", rep(1:6, times = length(vars)))
# Make block structure: variables at t predict variables at t+1
p <- length(vars)
Tsteps <- 6
bigmat <- matrix(0, p * Tsteps, p * Tsteps)
for (t in 1:(Tsteps - 1)) {
rows <- ((t - 1) * p + 1):(t * p)
cols <- (t * p + 1):((t + 1) * p)
bigmat[rows, cols] <- temporal_matrix
}
rownames(bigmat) <- colnames(bigmat) <- time_labels
qgraph(bigmat,
layout = "circle",
theme = "colorblind",
target = "cortisol_t6",
labels = time_labels,
title = "Temporal Dynamics Across 6 Timepoints")## Warning in qgraph(bigmat, layout = "circle", theme = "colorblind", target =
## "cortisol_t6", : The following arguments are not documented and likely not
## arguments of qgraph and thus ignored: target