R code follows
#Data with added effect codes
ScaledData <- read.table(
"C:/Users/woodph/OneDrive - University of Missouri/Documents/bartholow/Jan142026/BeverageScreened.csv",quote = "",header = T,sep=',')
data.frame(Column_Number = seq_along(ScaledData), Column_Name = names(ScaledData))
## Column_Number Column_Name
## 1 1 subid
## 2 2 ISD
## 3 3 Drink
## 4 4 ISA
## 5 5 ISC
## 6 6 ISP
## 7 7 ISE1
## 8 8 ISE2
## 9 9 ISE3
## 10 10 exp
## 11 11 Antisac1
## 12 12 Antisac2
## 13 13 Antisac3
## 14 14 PerSSRT1
## 15 15 PerSSRT2
## 16 16 PerSSRT3
## 17 17 Stroop1
## 18 18 Stroop2
## 19 19 Stroop3
## 20 20 Keeptrk1
## 21 21 Keeptrk2
## 22 22 Keeptrk3
## 23 23 Letmem1
## 24 24 Letmem2
## 25 25 Letmem3
## 26 26 Nback1
## 27 27 Nback2
## 28 28 Nback3
## 29 29 Catswt1
## 30 30 Catswt2
## 31 31 Catswt3
## 32 32 Colswt1
## 33 33 Colswt2
## 34 34 Colswt3
## 35 35 Numswt1
## 36 36 Numswt2
## 37 37 Numswt3
summary(ScaledData)
## subid ISD Drink ISA
## Min. :8001 Min. :0.0000 Min. : 1.0 Min. :0.0000
## 1st Qu.:8203 1st Qu.:0.0000 1st Qu.: 1.0 1st Qu.:0.0000
## Median :8404 Median :0.0000 Median : 10.0 Median :0.0000
## Mean :8403 Mean :0.4928 Mean : 37.3 Mean :0.3357
## 3rd Qu.:8601 3rd Qu.:1.0000 3rd Qu.:100.0 3rd Qu.:1.0000
## Max. :8801 Max. :1.0000 Max. :100.0 Max. :1.0000
##
## ISC ISP ISE1 ISE2
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.3401 Mean :0.3242 Mean :0.3256 Mean :0.3372
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
##
## ISE3 exp Antisac1 Antisac2
## Min. :0.0000 Min. :1.000 Min. :0.2143 Min. :0.2738
## 1st Qu.:0.0000 1st Qu.:1.000 1st Qu.:0.5476 1st Qu.:0.5595
## Median :0.0000 Median :2.000 Median :0.6548 Median :0.7143
## Mean :0.3372 Mean :2.012 Mean :0.6416 Mean :0.6905
## 3rd Qu.:1.0000 3rd Qu.:3.000 3rd Qu.:0.7619 3rd Qu.:0.8095
## Max. :1.0000 Max. :3.000 Max. :0.9643 Max. :0.9762
## NA's :5 NA's :502
## Antisac3 PerSSRT1 PerSSRT2 PerSSRT3
## Min. :0.2772 Min. :130.7 Min. :132.0 Min. :154.0
## 1st Qu.:0.6306 1st Qu.:228.5 1st Qu.:231.6 1st Qu.:236.2
## Median :0.7381 Median :250.8 Median :260.9 Median :259.6
## Mean :0.7220 Mean :249.8 Mean :257.6 Mean :259.7
## 3rd Qu.:0.8333 3rd Qu.:275.3 3rd Qu.:284.1 3rd Qu.:282.9
## Max. :0.9762 Max. :368.7 Max. :368.0 Max. :378.1
## NA's :314 NA's :21 NA's :508 NA's :323
## Stroop1 Stroop2 Stroop3 Keeptrk1
## Min. :-76.73 Min. :-35.92 Min. :-20.18 Min. :0.4140
## 1st Qu.: 94.39 1st Qu.: 80.00 1st Qu.: 77.65 1st Qu.:0.6593
## Median :130.91 Median :113.85 Median :114.01 Median :0.7250
## Mean :137.93 Mean :119.15 Mean :120.28 Mean :0.7245
## 3rd Qu.:174.68 3rd Qu.:154.27 3rd Qu.:157.39 3rd Qu.:0.8019
## Max. :352.56 Max. :293.51 Max. :379.07 Max. :0.9556
## NA's :3 NA's :499 NA's :315
## Keeptrk2 Keeptrk3 Letmem1 Letmem2
## Min. :0.4256 Min. :0.4566 Min. :0.06685 Min. :0.1674
## 1st Qu.:0.6801 1st Qu.:0.7111 1st Qu.:0.69305 1st Qu.:0.7297
## Median :0.7500 Median :0.7778 Median :0.84806 Median :0.9366
## Mean :0.7421 Mean :0.7690 Mean :0.85302 Mean :0.9487
## 3rd Qu.:0.8097 3rd Qu.:0.8333 3rd Qu.:1.00016 3rd Qu.:1.1597
## Max. :0.9556 Max. :1.0000 Max. :1.57080 Max. :1.5708
## NA's :500 NA's :311 NA's :497
## Letmem3 Nback1 Nback2 Nback3
## Min. :0.1957 Min. :0.6111 Min. :0.6667 Min. :0.6250
## 1st Qu.:0.7676 1st Qu.:0.7604 1st Qu.:0.7917 1st Qu.:0.7917
## Median :0.9851 Median :0.8021 Median :0.8438 Median :0.8542
## Mean :1.0046 Mean :0.8120 Mean :0.8433 Mean :0.8520
## 3rd Qu.:1.1597 3rd Qu.:0.8646 3rd Qu.:0.9036 3rd Qu.:0.9167
## Max. :1.5708 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :308 NA's :14 NA's :496 NA's :311
## Catswt1 Catswt2 Catswt3 Colswt1
## Min. :-563.77 Min. :-529.15 Min. :-526.0 Min. :-800.6
## 1st Qu.:-232.14 1st Qu.:-208.57 1st Qu.:-190.0 1st Qu.:-307.4
## Median :-135.80 Median :-106.53 Median :-101.1 Median :-193.1
## Mean :-160.51 Mean :-143.52 Mean :-133.7 Mean :-224.6
## 3rd Qu.: -67.46 3rd Qu.: -53.99 3rd Qu.: -49.5 3rd Qu.:-104.1
## Max. : 80.48 Max. : 76.08 Max. : 127.0 Max. : 330.9
## NA's :3 NA's :500 NA's :309 NA's :3
## Colswt2 Colswt3 Numswt1 Numswt2
## Min. :-676.76 Min. :-643.66 Min. :-945.256 Min. :-774.276
## 1st Qu.:-251.83 1st Qu.:-232.07 1st Qu.:-416.061 1st Qu.:-327.174
## Median :-151.24 Median :-140.23 Median :-297.420 Median :-230.136
## Mean :-189.34 Mean :-165.42 Mean :-320.391 Mean :-251.412
## 3rd Qu.: -84.09 3rd Qu.: -69.31 3rd Qu.:-187.909 3rd Qu.:-141.804
## Max. : 132.93 Max. : 285.16 Max. : 3.105 Max. : -9.713
## NA's :497 NA's :302 NA's :5 NA's :504
## Numswt3
## Min. :-820.4
## 1st Qu.:-305.2
## Median :-195.9
## Mean :-234.8
## 3rd Qu.:-121.5
## Max. : 107.3
## NA's :313
#drink coded off of dummy vectors of beverage
#100 is alcohol 10 is control 1 is placebo
#grouping is drink (100 = a 10=c 1=p);
#create group dummy codes
ScaledData$A <- 0
ScaledData$A <- 1*(ScaledData$Drink==100)
ScaledData$P <- 0
ScaledData$P <- 1*(ScaledData$Drink==1)
#ISD is zero if they did both arms, 1 if they did just descending
ScaledData$Both <- 0
ScaledData$Both <- 1*(ScaledData$ISD==0)
ScaledData$IX <- ScaledData$A*ScaledData$Both
library(lavaan);
## Warning: package 'lavaan' was built under R version 4.5.2
## This is lavaan 0.6-21
## lavaan is FREE software! Please report any bugs.
require(lavaan);
library(semTools)
##
## ###############################################################################
## This is semTools 0.5-7
## All users of R (or SEM) are invited to submit functions or ideas for functions.
## ###############################################################################
summary(ScaledData)
## subid ISD Drink ISA
## Min. :8001 Min. :0.0000 Min. : 1.0 Min. :0.0000
## 1st Qu.:8203 1st Qu.:0.0000 1st Qu.: 1.0 1st Qu.:0.0000
## Median :8404 Median :0.0000 Median : 10.0 Median :0.0000
## Mean :8403 Mean :0.4928 Mean : 37.3 Mean :0.3357
## 3rd Qu.:8601 3rd Qu.:1.0000 3rd Qu.:100.0 3rd Qu.:1.0000
## Max. :8801 Max. :1.0000 Max. :100.0 Max. :1.0000
##
## ISC ISP ISE1 ISE2
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.3401 Mean :0.3242 Mean :0.3256 Mean :0.3372
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
##
## ISE3 exp Antisac1 Antisac2
## Min. :0.0000 Min. :1.000 Min. :0.2143 Min. :0.2738
## 1st Qu.:0.0000 1st Qu.:1.000 1st Qu.:0.5476 1st Qu.:0.5595
## Median :0.0000 Median :2.000 Median :0.6548 Median :0.7143
## Mean :0.3372 Mean :2.012 Mean :0.6416 Mean :0.6905
## 3rd Qu.:1.0000 3rd Qu.:3.000 3rd Qu.:0.7619 3rd Qu.:0.8095
## Max. :1.0000 Max. :3.000 Max. :0.9643 Max. :0.9762
## NA's :5 NA's :502
## Antisac3 PerSSRT1 PerSSRT2 PerSSRT3
## Min. :0.2772 Min. :130.7 Min. :132.0 Min. :154.0
## 1st Qu.:0.6306 1st Qu.:228.5 1st Qu.:231.6 1st Qu.:236.2
## Median :0.7381 Median :250.8 Median :260.9 Median :259.6
## Mean :0.7220 Mean :249.8 Mean :257.6 Mean :259.7
## 3rd Qu.:0.8333 3rd Qu.:275.3 3rd Qu.:284.1 3rd Qu.:282.9
## Max. :0.9762 Max. :368.7 Max. :368.0 Max. :378.1
## NA's :314 NA's :21 NA's :508 NA's :323
## Stroop1 Stroop2 Stroop3 Keeptrk1
## Min. :-76.73 Min. :-35.92 Min. :-20.18 Min. :0.4140
## 1st Qu.: 94.39 1st Qu.: 80.00 1st Qu.: 77.65 1st Qu.:0.6593
## Median :130.91 Median :113.85 Median :114.01 Median :0.7250
## Mean :137.93 Mean :119.15 Mean :120.28 Mean :0.7245
## 3rd Qu.:174.68 3rd Qu.:154.27 3rd Qu.:157.39 3rd Qu.:0.8019
## Max. :352.56 Max. :293.51 Max. :379.07 Max. :0.9556
## NA's :3 NA's :499 NA's :315
## Keeptrk2 Keeptrk3 Letmem1 Letmem2
## Min. :0.4256 Min. :0.4566 Min. :0.06685 Min. :0.1674
## 1st Qu.:0.6801 1st Qu.:0.7111 1st Qu.:0.69305 1st Qu.:0.7297
## Median :0.7500 Median :0.7778 Median :0.84806 Median :0.9366
## Mean :0.7421 Mean :0.7690 Mean :0.85302 Mean :0.9487
## 3rd Qu.:0.8097 3rd Qu.:0.8333 3rd Qu.:1.00016 3rd Qu.:1.1597
## Max. :0.9556 Max. :1.0000 Max. :1.57080 Max. :1.5708
## NA's :500 NA's :311 NA's :497
## Letmem3 Nback1 Nback2 Nback3
## Min. :0.1957 Min. :0.6111 Min. :0.6667 Min. :0.6250
## 1st Qu.:0.7676 1st Qu.:0.7604 1st Qu.:0.7917 1st Qu.:0.7917
## Median :0.9851 Median :0.8021 Median :0.8438 Median :0.8542
## Mean :1.0046 Mean :0.8120 Mean :0.8433 Mean :0.8520
## 3rd Qu.:1.1597 3rd Qu.:0.8646 3rd Qu.:0.9036 3rd Qu.:0.9167
## Max. :1.5708 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :308 NA's :14 NA's :496 NA's :311
## Catswt1 Catswt2 Catswt3 Colswt1
## Min. :-563.77 Min. :-529.15 Min. :-526.0 Min. :-800.6
## 1st Qu.:-232.14 1st Qu.:-208.57 1st Qu.:-190.0 1st Qu.:-307.4
## Median :-135.80 Median :-106.53 Median :-101.1 Median :-193.1
## Mean :-160.51 Mean :-143.52 Mean :-133.7 Mean :-224.6
## 3rd Qu.: -67.46 3rd Qu.: -53.99 3rd Qu.: -49.5 3rd Qu.:-104.1
## Max. : 80.48 Max. : 76.08 Max. : 127.0 Max. : 330.9
## NA's :3 NA's :500 NA's :309 NA's :3
## Colswt2 Colswt3 Numswt1 Numswt2
## Min. :-676.76 Min. :-643.66 Min. :-945.256 Min. :-774.276
## 1st Qu.:-251.83 1st Qu.:-232.07 1st Qu.:-416.061 1st Qu.:-327.174
## Median :-151.24 Median :-140.23 Median :-297.420 Median :-230.136
## Mean :-189.34 Mean :-165.42 Mean :-320.391 Mean :-251.412
## 3rd Qu.: -84.09 3rd Qu.: -69.31 3rd Qu.:-187.909 3rd Qu.:-141.804
## Max. : 132.93 Max. : 285.16 Max. : 3.105 Max. : -9.713
## NA's :497 NA's :302 NA's :5 NA's :504
## Numswt3 A P Both
## Min. :-820.4 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:-305.2 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :-195.9 Median :0.0000 Median :0.0000 Median :1.0000
## Mean :-234.8 Mean :0.3357 Mean :0.3242 Mean :0.5072
## 3rd Qu.:-121.5 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. : 107.3 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :313
## IX
## Min. :0.0000
## 1st Qu.:0.0000
## Median :0.0000
## Mean :0.1758
## 3rd Qu.:0.0000
## Max. :1.0000
##
# Column index numbers for ScaledData (name -> position)
setNames(seq_along(names(ScaledData)), names(ScaledData))
## subid ISD Drink ISA ISC ISP ISE1 ISE2
## 1 2 3 4 5 6 7 8
## ISE3 exp Antisac1 Antisac2 Antisac3 PerSSRT1 PerSSRT2 PerSSRT3
## 9 10 11 12 13 14 15 16
## Stroop1 Stroop2 Stroop3 Keeptrk1 Keeptrk2 Keeptrk3 Letmem1 Letmem2
## 17 18 19 20 21 22 23 24
## Letmem3 Nback1 Nback2 Nback3 Catswt1 Catswt2 Catswt3 Colswt1
## 25 26 27 28 29 30 31 32
## Colswt2 Colswt3 Numswt1 Numswt2 Numswt3 A P Both
## 33 34 35 36 37 38 39 40
## IX
## 41
# (Optional) cleaner table view: position + variable name
data.frame(
col_index = seq_along(names(ScaledData)),
variable = names(ScaledData),
row.names = NULL
)
## col_index variable
## 1 1 subid
## 2 2 ISD
## 3 3 Drink
## 4 4 ISA
## 5 5 ISC
## 6 6 ISP
## 7 7 ISE1
## 8 8 ISE2
## 9 9 ISE3
## 10 10 exp
## 11 11 Antisac1
## 12 12 Antisac2
## 13 13 Antisac3
## 14 14 PerSSRT1
## 15 15 PerSSRT2
## 16 16 PerSSRT3
## 17 17 Stroop1
## 18 18 Stroop2
## 19 19 Stroop3
## 20 20 Keeptrk1
## 21 21 Keeptrk2
## 22 22 Keeptrk3
## 23 23 Letmem1
## 24 24 Letmem2
## 25 25 Letmem3
## 26 26 Nback1
## 27 27 Nback2
## 28 28 Nback3
## 29 29 Catswt1
## 30 30 Catswt2
## 31 31 Catswt3
## 32 32 Colswt1
## 33 33 Colswt2
## 34 34 Colswt3
## 35 35 Numswt1
## 36 36 Numswt2
## 37 37 Numswt3
## 38 38 A
## 39 39 P
## 40 40 Both
## 41 41 IX
summary(ScaledData)
## subid ISD Drink ISA
## Min. :8001 Min. :0.0000 Min. : 1.0 Min. :0.0000
## 1st Qu.:8203 1st Qu.:0.0000 1st Qu.: 1.0 1st Qu.:0.0000
## Median :8404 Median :0.0000 Median : 10.0 Median :0.0000
## Mean :8403 Mean :0.4928 Mean : 37.3 Mean :0.3357
## 3rd Qu.:8601 3rd Qu.:1.0000 3rd Qu.:100.0 3rd Qu.:1.0000
## Max. :8801 Max. :1.0000 Max. :100.0 Max. :1.0000
##
## ISC ISP ISE1 ISE2
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.3401 Mean :0.3242 Mean :0.3256 Mean :0.3372
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
##
## ISE3 exp Antisac1 Antisac2
## Min. :0.0000 Min. :1.000 Min. :0.2143 Min. :0.2738
## 1st Qu.:0.0000 1st Qu.:1.000 1st Qu.:0.5476 1st Qu.:0.5595
## Median :0.0000 Median :2.000 Median :0.6548 Median :0.7143
## Mean :0.3372 Mean :2.012 Mean :0.6416 Mean :0.6905
## 3rd Qu.:1.0000 3rd Qu.:3.000 3rd Qu.:0.7619 3rd Qu.:0.8095
## Max. :1.0000 Max. :3.000 Max. :0.9643 Max. :0.9762
## NA's :5 NA's :502
## Antisac3 PerSSRT1 PerSSRT2 PerSSRT3
## Min. :0.2772 Min. :130.7 Min. :132.0 Min. :154.0
## 1st Qu.:0.6306 1st Qu.:228.5 1st Qu.:231.6 1st Qu.:236.2
## Median :0.7381 Median :250.8 Median :260.9 Median :259.6
## Mean :0.7220 Mean :249.8 Mean :257.6 Mean :259.7
## 3rd Qu.:0.8333 3rd Qu.:275.3 3rd Qu.:284.1 3rd Qu.:282.9
## Max. :0.9762 Max. :368.7 Max. :368.0 Max. :378.1
## NA's :314 NA's :21 NA's :508 NA's :323
## Stroop1 Stroop2 Stroop3 Keeptrk1
## Min. :-76.73 Min. :-35.92 Min. :-20.18 Min. :0.4140
## 1st Qu.: 94.39 1st Qu.: 80.00 1st Qu.: 77.65 1st Qu.:0.6593
## Median :130.91 Median :113.85 Median :114.01 Median :0.7250
## Mean :137.93 Mean :119.15 Mean :120.28 Mean :0.7245
## 3rd Qu.:174.68 3rd Qu.:154.27 3rd Qu.:157.39 3rd Qu.:0.8019
## Max. :352.56 Max. :293.51 Max. :379.07 Max. :0.9556
## NA's :3 NA's :499 NA's :315
## Keeptrk2 Keeptrk3 Letmem1 Letmem2
## Min. :0.4256 Min. :0.4566 Min. :0.06685 Min. :0.1674
## 1st Qu.:0.6801 1st Qu.:0.7111 1st Qu.:0.69305 1st Qu.:0.7297
## Median :0.7500 Median :0.7778 Median :0.84806 Median :0.9366
## Mean :0.7421 Mean :0.7690 Mean :0.85302 Mean :0.9487
## 3rd Qu.:0.8097 3rd Qu.:0.8333 3rd Qu.:1.00016 3rd Qu.:1.1597
## Max. :0.9556 Max. :1.0000 Max. :1.57080 Max. :1.5708
## NA's :500 NA's :311 NA's :497
## Letmem3 Nback1 Nback2 Nback3
## Min. :0.1957 Min. :0.6111 Min. :0.6667 Min. :0.6250
## 1st Qu.:0.7676 1st Qu.:0.7604 1st Qu.:0.7917 1st Qu.:0.7917
## Median :0.9851 Median :0.8021 Median :0.8438 Median :0.8542
## Mean :1.0046 Mean :0.8120 Mean :0.8433 Mean :0.8520
## 3rd Qu.:1.1597 3rd Qu.:0.8646 3rd Qu.:0.9036 3rd Qu.:0.9167
## Max. :1.5708 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :308 NA's :14 NA's :496 NA's :311
## Catswt1 Catswt2 Catswt3 Colswt1
## Min. :-563.77 Min. :-529.15 Min. :-526.0 Min. :-800.6
## 1st Qu.:-232.14 1st Qu.:-208.57 1st Qu.:-190.0 1st Qu.:-307.4
## Median :-135.80 Median :-106.53 Median :-101.1 Median :-193.1
## Mean :-160.51 Mean :-143.52 Mean :-133.7 Mean :-224.6
## 3rd Qu.: -67.46 3rd Qu.: -53.99 3rd Qu.: -49.5 3rd Qu.:-104.1
## Max. : 80.48 Max. : 76.08 Max. : 127.0 Max. : 330.9
## NA's :3 NA's :500 NA's :309 NA's :3
## Colswt2 Colswt3 Numswt1 Numswt2
## Min. :-676.76 Min. :-643.66 Min. :-945.256 Min. :-774.276
## 1st Qu.:-251.83 1st Qu.:-232.07 1st Qu.:-416.061 1st Qu.:-327.174
## Median :-151.24 Median :-140.23 Median :-297.420 Median :-230.136
## Mean :-189.34 Mean :-165.42 Mean :-320.391 Mean :-251.412
## 3rd Qu.: -84.09 3rd Qu.: -69.31 3rd Qu.:-187.909 3rd Qu.:-141.804
## Max. : 132.93 Max. : 285.16 Max. : 3.105 Max. : -9.713
## NA's :497 NA's :302 NA's :5 NA's :504
## Numswt3 A P Both
## Min. :-820.4 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:-305.2 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :-195.9 Median :0.0000 Median :0.0000 Median :1.0000
## Mean :-234.8 Mean :0.3357 Mean :0.3242 Mean :0.5072
## 3rd Qu.:-121.5 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. : 107.3 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :313
## IX
## Min. :0.0000
## 1st Qu.:0.0000
## Median :0.0000
## Mean :0.1758
## 3rd Qu.:0.0000
## Max. :1.0000
##
sapply(ScaledData, sd, na.rm = TRUE)
## subid ISD Drink ISA ISC ISP
## 231.12403873 0.50030867 44.75940586 0.47258733 0.47406991 0.46841558
## ISE1 ISE2 ISE3 exp Antisac1 Antisac2
## 0.46895459 0.47308643 0.47308643 0.81464568 0.14782653 0.15490328
## Antisac3 PerSSRT1 PerSSRT2 PerSSRT3 Stroop1 Stroop2
## 0.14399087 38.81340647 40.69860180 36.94516737 68.08136456 57.43430266
## Stroop3 Keeptrk1 Keeptrk2 Keeptrk3 Letmem1 Letmem2
## 63.10335348 0.10300227 0.10399835 0.10224915 0.26186468 0.31125017
## Letmem3 Nback1 Nback2 Nback3 Catswt1 Catswt2
## 0.30673490 0.07643322 0.07992473 0.08655473 124.78434007 122.42138929
## Catswt3 Colswt1 Colswt2 Colswt3 Numswt1 Numswt2
## 118.20424759 174.65768176 156.95714175 146.66270920 178.83496446 154.85244855
## Numswt3 A P Both IX
## 164.53179997 0.47258733 0.46841558 0.50030867 0.38091807
rmat <- cor(ScaledData[ , 11:37], use = "pairwise.complete.obs")
round(rmat, 2)
## Antisac1 Antisac2 Antisac3 PerSSRT1 PerSSRT2 PerSSRT3 Stroop1 Stroop2
## Antisac1 1.00 0.74 0.68 -0.12 0.00 -0.18 -0.19 -0.16
## Antisac2 0.74 1.00 0.85 -0.09 -0.31 -0.27 -0.08 -0.18
## Antisac3 0.68 0.85 1.00 -0.16 -0.36 -0.14 -0.14 -0.17
## PerSSRT1 -0.12 -0.09 -0.16 1.00 0.27 0.19 0.10 -0.01
## PerSSRT2 0.00 -0.31 -0.36 0.27 1.00 0.31 0.06 0.17
## PerSSRT3 -0.18 -0.27 -0.14 0.19 0.31 1.00 0.02 -0.06
## Stroop1 -0.19 -0.08 -0.14 0.10 0.06 0.02 1.00 0.51
## Stroop2 -0.16 -0.18 -0.17 -0.01 0.17 -0.06 0.51 1.00
## Stroop3 -0.24 -0.18 -0.20 0.03 0.15 0.07 0.46 0.49
## Keeptrk1 0.10 0.08 0.14 -0.04 -0.09 0.01 -0.06 -0.24
## Keeptrk2 0.20 0.39 0.35 0.10 -0.17 0.06 -0.13 -0.29
## Keeptrk3 0.20 0.36 0.38 0.01 -0.16 0.03 -0.08 -0.20
## Letmem1 0.22 0.31 0.25 -0.06 -0.12 -0.01 -0.13 -0.11
## Letmem2 0.20 0.32 0.28 -0.04 -0.09 -0.22 -0.22 -0.12
## Letmem3 0.22 0.27 0.21 -0.06 -0.02 -0.16 -0.15 -0.02
## Nback1 0.25 0.18 0.22 -0.03 -0.04 -0.03 -0.08 0.04
## Nback2 0.21 0.36 0.35 0.01 -0.02 -0.22 -0.04 -0.05
## Nback3 0.22 0.27 0.36 0.04 -0.02 -0.04 -0.07 -0.03
## Catswt1 0.20 0.13 0.18 -0.09 -0.06 -0.01 -0.15 -0.10
## Catswt2 0.20 0.27 0.21 0.06 -0.06 -0.04 -0.20 -0.26
## Catswt3 0.24 0.34 0.36 -0.14 -0.13 -0.17 -0.23 -0.15
## Colswt1 0.16 0.13 0.15 0.05 -0.05 -0.01 -0.11 -0.13
## Colswt2 0.25 0.19 0.23 0.08 -0.03 -0.02 -0.12 -0.11
## Colswt3 0.15 0.18 0.24 -0.01 -0.17 0.06 -0.18 -0.18
## Numswt1 0.19 0.10 0.13 -0.04 0.05 -0.04 -0.19 -0.11
## Numswt2 0.30 0.40 0.40 -0.02 0.00 -0.10 -0.15 -0.16
## Numswt3 0.23 0.42 0.31 -0.03 0.05 -0.12 -0.19 0.03
## Stroop3 Keeptrk1 Keeptrk2 Keeptrk3 Letmem1 Letmem2 Letmem3 Nback1
## Antisac1 -0.24 0.10 0.20 0.20 0.22 0.20 0.22 0.25
## Antisac2 -0.18 0.08 0.39 0.36 0.31 0.32 0.27 0.18
## Antisac3 -0.20 0.14 0.35 0.38 0.25 0.28 0.21 0.22
## PerSSRT1 0.03 -0.04 0.10 0.01 -0.06 -0.04 -0.06 -0.03
## PerSSRT2 0.15 -0.09 -0.17 -0.16 -0.12 -0.09 -0.02 -0.04
## PerSSRT3 0.07 0.01 0.06 0.03 -0.01 -0.22 -0.16 -0.03
## Stroop1 0.46 -0.06 -0.13 -0.08 -0.13 -0.22 -0.15 -0.08
## Stroop2 0.49 -0.24 -0.29 -0.20 -0.11 -0.12 -0.02 0.04
## Stroop3 1.00 -0.17 -0.22 -0.14 -0.14 -0.19 -0.09 -0.07
## Keeptrk1 -0.17 1.00 0.60 0.48 0.31 0.30 0.25 0.19
## Keeptrk2 -0.22 0.60 1.00 0.69 0.36 0.39 0.35 0.17
## Keeptrk3 -0.14 0.48 0.69 1.00 0.31 0.39 0.29 0.14
## Letmem1 -0.14 0.31 0.36 0.31 1.00 0.60 0.50 0.30
## Letmem2 -0.19 0.30 0.39 0.39 0.60 1.00 0.66 0.30
## Letmem3 -0.09 0.25 0.35 0.29 0.50 0.66 1.00 0.26
## Nback1 -0.07 0.19 0.17 0.14 0.30 0.30 0.26 1.00
## Nback2 -0.12 0.23 0.37 0.23 0.35 0.28 0.27 0.63
## Nback3 -0.15 0.21 0.23 0.22 0.26 0.35 0.24 0.64
## Catswt1 -0.19 0.08 0.10 0.11 0.07 0.04 0.09 0.07
## Catswt2 -0.32 0.02 0.10 0.12 0.03 0.02 0.13 0.03
## Catswt3 -0.20 0.07 -0.03 0.10 0.05 0.01 0.08 0.10
## Colswt1 -0.07 0.06 0.06 0.06 -0.01 0.06 0.01 0.02
## Colswt2 -0.26 0.02 0.07 0.04 0.00 0.04 0.08 0.05
## Colswt3 -0.09 0.06 0.08 0.14 -0.02 0.10 0.06 0.08
## Numswt1 -0.15 0.05 0.12 0.17 0.01 0.03 0.07 0.09
## Numswt2 -0.31 0.04 0.15 0.19 0.02 0.04 0.12 0.16
## Numswt3 -0.11 0.01 0.14 0.22 -0.01 -0.01 0.01 0.07
## Nback2 Nback3 Catswt1 Catswt2 Catswt3 Colswt1 Colswt2 Colswt3 Numswt1
## Antisac1 0.21 0.22 0.20 0.20 0.24 0.16 0.25 0.15 0.19
## Antisac2 0.36 0.27 0.13 0.27 0.34 0.13 0.19 0.18 0.10
## Antisac3 0.35 0.36 0.18 0.21 0.36 0.15 0.23 0.24 0.13
## PerSSRT1 0.01 0.04 -0.09 0.06 -0.14 0.05 0.08 -0.01 -0.04
## PerSSRT2 -0.02 -0.02 -0.06 -0.06 -0.13 -0.05 -0.03 -0.17 0.05
## PerSSRT3 -0.22 -0.04 -0.01 -0.04 -0.17 -0.01 -0.02 0.06 -0.04
## Stroop1 -0.04 -0.07 -0.15 -0.20 -0.23 -0.11 -0.12 -0.18 -0.19
## Stroop2 -0.05 -0.03 -0.10 -0.26 -0.15 -0.13 -0.11 -0.18 -0.11
## Stroop3 -0.12 -0.15 -0.19 -0.32 -0.20 -0.07 -0.26 -0.09 -0.15
## Keeptrk1 0.23 0.21 0.08 0.02 0.07 0.06 0.02 0.06 0.05
## Keeptrk2 0.37 0.23 0.10 0.10 -0.03 0.06 0.07 0.08 0.12
## Keeptrk3 0.23 0.22 0.11 0.12 0.10 0.06 0.04 0.14 0.17
## Letmem1 0.35 0.26 0.07 0.03 0.05 -0.01 0.00 -0.02 0.01
## Letmem2 0.28 0.35 0.04 0.02 0.01 0.06 0.04 0.10 0.03
## Letmem3 0.27 0.24 0.09 0.13 0.08 0.01 0.08 0.06 0.07
## Nback1 0.63 0.64 0.07 0.03 0.10 0.02 0.05 0.08 0.09
## Nback2 1.00 0.77 0.12 0.22 0.23 0.02 0.17 0.21 0.08
## Nback3 0.77 1.00 0.04 0.05 0.18 0.05 0.12 0.01 -0.02
## Catswt1 0.12 0.04 1.00 0.61 0.59 0.41 0.30 0.35 0.45
## Catswt2 0.22 0.05 0.61 1.00 0.55 0.44 0.42 0.45 0.41
## Catswt3 0.23 0.18 0.59 0.55 1.00 0.42 0.24 0.35 0.47
## Colswt1 0.02 0.05 0.41 0.44 0.42 1.00 0.49 0.50 0.39
## Colswt2 0.17 0.12 0.30 0.42 0.24 0.49 1.00 0.64 0.43
## Colswt3 0.21 0.01 0.35 0.45 0.35 0.50 0.64 1.00 0.49
## Numswt1 0.08 -0.02 0.45 0.41 0.47 0.39 0.43 0.49 1.00
## Numswt2 0.18 0.14 0.53 0.48 0.47 0.28 0.41 0.39 0.67
## Numswt3 0.10 0.00 0.41 0.49 0.48 0.34 0.45 0.56 0.71
## Numswt2 Numswt3
## Antisac1 0.30 0.23
## Antisac2 0.40 0.42
## Antisac3 0.40 0.31
## PerSSRT1 -0.02 -0.03
## PerSSRT2 0.00 0.05
## PerSSRT3 -0.10 -0.12
## Stroop1 -0.15 -0.19
## Stroop2 -0.16 0.03
## Stroop3 -0.31 -0.11
## Keeptrk1 0.04 0.01
## Keeptrk2 0.15 0.14
## Keeptrk3 0.19 0.22
## Letmem1 0.02 -0.01
## Letmem2 0.04 -0.01
## Letmem3 0.12 0.01
## Nback1 0.16 0.07
## Nback2 0.18 0.10
## Nback3 0.14 0.00
## Catswt1 0.53 0.41
## Catswt2 0.48 0.49
## Catswt3 0.47 0.48
## Colswt1 0.28 0.34
## Colswt2 0.41 0.45
## Colswt3 0.39 0.56
## Numswt1 0.67 0.71
## Numswt2 1.00 0.73
## Numswt3 0.73 1.00
print(rmat)
## Antisac1 Antisac2 Antisac3 PerSSRT1 PerSSRT2
## Antisac1 1.000000000 0.74391961 0.6788301 -0.116100061 0.0021221065
## Antisac2 0.743919608 1.00000000 0.8505980 -0.090942232 -0.3121318836
## Antisac3 0.678830145 0.85059804 1.0000000 -0.155967100 -0.3620352334
## PerSSRT1 -0.116100061 -0.09094223 -0.1559671 1.000000000 0.2703588846
## PerSSRT2 0.002122107 -0.31213188 -0.3620352 0.270358885 1.0000000000
## PerSSRT3 -0.179051608 -0.27068430 -0.1412094 0.191504874 0.3067238922
## Stroop1 -0.192057273 -0.08099529 -0.1419741 0.097472244 0.0609721985
## Stroop2 -0.161828433 -0.17543498 -0.1707210 -0.011253019 0.1665460899
## Stroop3 -0.239111833 -0.18114787 -0.1964236 0.026482415 0.1493728315
## Keeptrk1 0.095902401 0.08392529 0.1423281 -0.035058293 -0.0857928688
## Keeptrk2 0.204211468 0.38534910 0.3488817 0.101020854 -0.1667068500
## Keeptrk3 0.200649411 0.36358999 0.3814530 0.008152295 -0.1551906297
## Letmem1 0.219268073 0.30755378 0.2473597 -0.060967883 -0.1245760262
## Letmem2 0.202448325 0.32269310 0.2751378 -0.044880602 -0.0891852727
## Letmem3 0.218571159 0.26910162 0.2124632 -0.063655990 -0.0150576215
## Nback1 0.254497206 0.17841281 0.2205098 -0.026291045 -0.0354717906
## Nback2 0.208033633 0.35846665 0.3486684 0.012019431 -0.0190049560
## Nback3 0.223303112 0.27170163 0.3571890 0.037567413 -0.0156619433
## Catswt1 0.199407491 0.12893591 0.1805713 -0.090560890 -0.0557012342
## Catswt2 0.201876016 0.27135772 0.2145965 0.063791253 -0.0600146501
## Catswt3 0.244808105 0.33818076 0.3614304 -0.139027833 -0.1341306141
## Colswt1 0.162969810 0.12982593 0.1514312 0.048370390 -0.0543566639
## Colswt2 0.248607236 0.19445793 0.2316960 0.079583261 -0.0271623151
## Colswt3 0.149763771 0.18303757 0.2405414 -0.012549712 -0.1657463075
## Numswt1 0.185272367 0.10225677 0.1264999 -0.036330248 0.0549851709
## Numswt2 0.301834569 0.39887065 0.3988542 -0.019504383 -0.0004981972
## Numswt3 0.233141790 0.41517616 0.3101382 -0.030268327 0.0476704435
## PerSSRT3 Stroop1 Stroop2 Stroop3 Keeptrk1
## Antisac1 -0.179051608 -0.19205727 -0.16182843 -0.23911183 0.095902401
## Antisac2 -0.270684299 -0.08099529 -0.17543498 -0.18114787 0.083925292
## Antisac3 -0.141209382 -0.14197408 -0.17072099 -0.19642362 0.142328077
## PerSSRT1 0.191504874 0.09747224 -0.01125302 0.02648241 -0.035058293
## PerSSRT2 0.306723892 0.06097220 0.16654609 0.14937283 -0.085792869
## PerSSRT3 1.000000000 0.02085029 -0.06261441 0.06837149 0.006238173
## Stroop1 0.020850289 1.00000000 0.51355730 0.45780809 -0.055045789
## Stroop2 -0.062614407 0.51355730 1.00000000 0.48764340 -0.241068219
## Stroop3 0.068371487 0.45780809 0.48764340 1.00000000 -0.167592500
## Keeptrk1 0.006238173 -0.05504579 -0.24106822 -0.16759250 1.000000000
## Keeptrk2 0.060085131 -0.12897541 -0.29464011 -0.21803949 0.602775792
## Keeptrk3 0.025491719 -0.08111108 -0.20115008 -0.14251431 0.484139912
## Letmem1 -0.013230451 -0.12798672 -0.10945253 -0.13533987 0.309470288
## Letmem2 -0.223983448 -0.21609554 -0.12261652 -0.18646544 0.300925623
## Letmem3 -0.155498464 -0.14898145 -0.02328405 -0.08909035 0.254963016
## Nback1 -0.031314820 -0.08180357 0.03760695 -0.06701946 0.190419577
## Nback2 -0.220637104 -0.04394208 -0.04648467 -0.12074790 0.233129719
## Nback3 -0.039485270 -0.06963892 -0.02791751 -0.14857317 0.214384614
## Catswt1 -0.011705131 -0.15404381 -0.10245774 -0.18765170 0.083662947
## Catswt2 -0.035344833 -0.19695392 -0.25950024 -0.32193493 0.019493656
## Catswt3 -0.171330466 -0.22504289 -0.15296196 -0.20242567 0.065833220
## Colswt1 -0.007754999 -0.10920756 -0.13373069 -0.07462849 0.058633543
## Colswt2 -0.020279320 -0.12467028 -0.11108797 -0.25946418 0.017841861
## Colswt3 0.056970887 -0.18183264 -0.18018461 -0.09395503 0.063185643
## Numswt1 -0.042907570 -0.19038216 -0.10877315 -0.14573830 0.050937965
## Numswt2 -0.097919355 -0.15237340 -0.16322360 -0.30712628 0.035283250
## Numswt3 -0.116170627 -0.19224439 0.02943070 -0.10922793 0.009482892
## Keeptrk2 Keeptrk3 Letmem1 Letmem2 Letmem3
## Antisac1 0.20421147 0.200649411 0.219268073 0.202448325 0.218571159
## Antisac2 0.38534910 0.363589990 0.307553781 0.322693097 0.269101619
## Antisac3 0.34888173 0.381452975 0.247359688 0.275137757 0.212463161
## PerSSRT1 0.10102085 0.008152295 -0.060967883 -0.044880602 -0.063655990
## PerSSRT2 -0.16670685 -0.155190630 -0.124576026 -0.089185273 -0.015057622
## PerSSRT3 0.06008513 0.025491719 -0.013230451 -0.223983448 -0.155498464
## Stroop1 -0.12897541 -0.081111078 -0.127986720 -0.216095543 -0.148981455
## Stroop2 -0.29464011 -0.201150084 -0.109452530 -0.122616523 -0.023284051
## Stroop3 -0.21803949 -0.142514308 -0.135339874 -0.186465439 -0.089090348
## Keeptrk1 0.60277579 0.484139912 0.309470288 0.300925623 0.254963016
## Keeptrk2 1.00000000 0.693354418 0.364157346 0.390157453 0.346782016
## Keeptrk3 0.69335442 1.000000000 0.313960124 0.387417535 0.285428578
## Letmem1 0.36415735 0.313960124 1.000000000 0.602643545 0.497720398
## Letmem2 0.39015745 0.387417535 0.602643545 1.000000000 0.657945337
## Letmem3 0.34678202 0.285428578 0.497720398 0.657945337 1.000000000
## Nback1 0.17490692 0.141894475 0.295661661 0.301695179 0.255960014
## Nback2 0.36676192 0.233611699 0.347252056 0.282834623 0.272740788
## Nback3 0.23293064 0.220990151 0.263700465 0.353149100 0.238309687
## Catswt1 0.09622364 0.113945140 0.070066552 0.041435727 0.091932595
## Catswt2 0.09844831 0.120449692 0.025022730 0.016304483 0.133501073
## Catswt3 -0.03387565 0.104580713 0.052431387 0.011283507 0.075319912
## Colswt1 0.06460274 0.058937693 -0.008283719 0.055671085 0.007979003
## Colswt2 0.06528612 0.035318171 0.004930345 0.038846228 0.075047438
## Colswt3 0.08465626 0.136729994 -0.022029084 0.103314549 0.063454816
## Numswt1 0.11594717 0.174094558 0.006528441 0.033483266 0.072362712
## Numswt2 0.15185915 0.185441255 0.019237201 0.036544717 0.116694550
## Numswt3 0.14406380 0.222001647 -0.005771993 -0.005600785 0.010112642
## Nback1 Nback2 Nback3 Catswt1 Catswt2
## Antisac1 0.25449721 0.20803363 0.223303112 0.19940749 0.20187602
## Antisac2 0.17841281 0.35846665 0.271701629 0.12893591 0.27135772
## Antisac3 0.22050982 0.34866843 0.357188988 0.18057127 0.21459654
## PerSSRT1 -0.02629105 0.01201943 0.037567413 -0.09056089 0.06379125
## PerSSRT2 -0.03547179 -0.01900496 -0.015661943 -0.05570123 -0.06001465
## PerSSRT3 -0.03131482 -0.22063710 -0.039485270 -0.01170513 -0.03534483
## Stroop1 -0.08180357 -0.04394208 -0.069638922 -0.15404381 -0.19695392
## Stroop2 0.03760695 -0.04648467 -0.027917509 -0.10245774 -0.25950024
## Stroop3 -0.06701946 -0.12074790 -0.148573170 -0.18765170 -0.32193493
## Keeptrk1 0.19041958 0.23312972 0.214384614 0.08366295 0.01949366
## Keeptrk2 0.17490692 0.36676192 0.232930640 0.09622364 0.09844831
## Keeptrk3 0.14189448 0.23361170 0.220990151 0.11394514 0.12044969
## Letmem1 0.29566166 0.34725206 0.263700465 0.07006655 0.02502273
## Letmem2 0.30169518 0.28283462 0.353149100 0.04143573 0.01630448
## Letmem3 0.25596001 0.27274079 0.238309687 0.09193260 0.13350107
## Nback1 1.00000000 0.63141550 0.639382638 0.06800507 0.02928285
## Nback2 0.63141550 1.00000000 0.765289965 0.11578242 0.21755340
## Nback3 0.63938264 0.76528997 1.000000000 0.04084436 0.04805456
## Catswt1 0.06800507 0.11578242 0.040844358 1.00000000 0.60698879
## Catswt2 0.02928285 0.21755340 0.048054558 0.60698879 1.00000000
## Catswt3 0.10347510 0.22706228 0.177170509 0.59170453 0.55090443
## Colswt1 0.01511064 0.02094440 0.047077831 0.41049273 0.43687260
## Colswt2 0.05240629 0.16532982 0.118527405 0.30166747 0.42072012
## Colswt3 0.07708710 0.20562404 0.008330784 0.35423127 0.45061601
## Numswt1 0.09475154 0.07517768 -0.022146718 0.44578688 0.40847901
## Numswt2 0.15578271 0.18360375 0.142912084 0.53146047 0.47582659
## Numswt3 0.07096910 0.09661057 0.002952774 0.40616581 0.49287292
## Catswt3 Colswt1 Colswt2 Colswt3 Numswt1
## Antisac1 0.24480811 0.162969810 0.248607236 0.149763771 0.185272367
## Antisac2 0.33818076 0.129825930 0.194457934 0.183037575 0.102256772
## Antisac3 0.36143043 0.151431241 0.231695978 0.240541372 0.126499902
## PerSSRT1 -0.13902783 0.048370390 0.079583261 -0.012549712 -0.036330248
## PerSSRT2 -0.13413061 -0.054356664 -0.027162315 -0.165746307 0.054985171
## PerSSRT3 -0.17133047 -0.007754999 -0.020279320 0.056970887 -0.042907570
## Stroop1 -0.22504289 -0.109207562 -0.124670277 -0.181832643 -0.190382158
## Stroop2 -0.15296196 -0.133730691 -0.111087967 -0.180184609 -0.108773154
## Stroop3 -0.20242567 -0.074628490 -0.259464176 -0.093955035 -0.145738302
## Keeptrk1 0.06583322 0.058633543 0.017841861 0.063185643 0.050937965
## Keeptrk2 -0.03387565 0.064602740 0.065286118 0.084656256 0.115947166
## Keeptrk3 0.10458071 0.058937693 0.035318171 0.136729994 0.174094558
## Letmem1 0.05243139 -0.008283719 0.004930345 -0.022029084 0.006528441
## Letmem2 0.01128351 0.055671085 0.038846228 0.103314549 0.033483266
## Letmem3 0.07531991 0.007979003 0.075047438 0.063454816 0.072362712
## Nback1 0.10347510 0.015110636 0.052406292 0.077087104 0.094751539
## Nback2 0.22706228 0.020944396 0.165329823 0.205624040 0.075177679
## Nback3 0.17717051 0.047077831 0.118527405 0.008330784 -0.022146718
## Catswt1 0.59170453 0.410492731 0.301667469 0.354231268 0.445786879
## Catswt2 0.55090443 0.436872604 0.420720121 0.450616013 0.408479010
## Catswt3 1.00000000 0.421721459 0.238974939 0.353793151 0.466243395
## Colswt1 0.42172146 1.000000000 0.487234627 0.503440116 0.391765036
## Colswt2 0.23897494 0.487234627 1.000000000 0.639799313 0.425439140
## Colswt3 0.35379315 0.503440116 0.639799313 1.000000000 0.489078984
## Numswt1 0.46624339 0.391765036 0.425439140 0.489078984 1.000000000
## Numswt2 0.47203017 0.277358901 0.408500440 0.388019706 0.669532216
## Numswt3 0.48410947 0.342125187 0.447873088 0.564276975 0.710641248
## Numswt2 Numswt3
## Antisac1 0.3018345687 0.233141790
## Antisac2 0.3988706539 0.415176161
## Antisac3 0.3988542026 0.310138246
## PerSSRT1 -0.0195043827 -0.030268327
## PerSSRT2 -0.0004981972 0.047670444
## PerSSRT3 -0.0979193548 -0.116170627
## Stroop1 -0.1523734028 -0.192244386
## Stroop2 -0.1632236002 0.029430697
## Stroop3 -0.3071262847 -0.109227934
## Keeptrk1 0.0352832505 0.009482892
## Keeptrk2 0.1518591546 0.144063800
## Keeptrk3 0.1854412553 0.222001647
## Letmem1 0.0192372014 -0.005771993
## Letmem2 0.0365447167 -0.005600785
## Letmem3 0.1166945500 0.010112642
## Nback1 0.1557827052 0.070969098
## Nback2 0.1836037525 0.096610573
## Nback3 0.1429120836 0.002952774
## Catswt1 0.5314604750 0.406165807
## Catswt2 0.4758265872 0.492872916
## Catswt3 0.4720301696 0.484109465
## Colswt1 0.2773589013 0.342125187
## Colswt2 0.4085004404 0.447873088
## Colswt3 0.3880197062 0.564276975
## Numswt1 0.6695322160 0.710641248
## Numswt2 1.0000000000 0.729655205
## Numswt3 0.7296552051 1.000000000
library(corrplot)
## corrplot 0.95 loaded
library(psych)
## Warning: package 'psych' was built under R version 4.5.1
##
## Attaching package: 'psych'
## The following objects are masked from 'package:semTools':
##
## reliability, skew
## The following object is masked from 'package:lavaan':
##
## cor2cov
corrplot(rmat, method = "circle")
ct <- corr.test(ScaledData)
## Warning in cor(x, use = use, method = method): the standard deviation is zero
r_mat <- ct$r
p_mat <- ct$p
# Step 2: Plot correlations, only showing significant ones
corrplot(r_mat,
method = "circle",
type = "upper",
p.mat = p_mat, # p-values matrix
sig.level = 0.05, # significance threshold
insig = "blank") # options: "blank", "pch", "n"
BevScreenData <- read.csv(
"C:/Users/woodph/OneDrive - University of Missouri/Documents/bartholow/Jan142026/BeverageScreened.csv",quote = "",header = T,sep=',')
#rescale variables
#rescale variables
BevScreenData$Antisac1= BevScreenData$Antisac1/.15;
BevScreenData$Antisac2= BevScreenData$Antisac2/.15;
BevScreenData$Antisac3= BevScreenData$Antisac3/.15;
BevScreenData$PerSSRT1 = -1*BevScreenData$PerSSRT1/40;
BevScreenData$PerSSRT2 = -1*BevScreenData$PerSSRT2/40;
BevScreenData$PerSSRT3 = -1*BevScreenData$PerSSRT3/40;
BevScreenData$Stroop1 = -1*BevScreenData$Stroop1/60;
BevScreenData$Stroop2 = -1*BevScreenData$Stroop2/60;
BevScreenData$Stroop3 = -1*BevScreenData$Stroop3/60;
BevScreenData$Keeptrk1= BevScreenData$Keeptrk1/.1;
BevScreenData$Keeptrk2= BevScreenData$Keeptrk2/.1;
BevScreenData$Keeptrk3= BevScreenData$Keeptrk3/.1;
BevScreenData$Letmem1= BevScreenData$Letmem1/.3;
BevScreenData$Letmem2= BevScreenData$Letmem2/.3;
BevScreenData$Letmem3= BevScreenData$Letmem3/.3;
BevScreenData$Nback1= BevScreenData$Nback1/.08;
BevScreenData$Nback2= BevScreenData$Nback2/.08;
BevScreenData$Nback3= BevScreenData$Nback3/.08;
BevScreenData$Catswt1= BevScreenData$Catswt1/120;
BevScreenData$Catswt2= BevScreenData$Catswt2/120;
BevScreenData$Catswt3= BevScreenData$Catswt3/120;
BevScreenData$Colswt1= BevScreenData$Colswt1/150;
BevScreenData$Colswt2= BevScreenData$Colswt2/150;
BevScreenData$Colswt3= BevScreenData$Colswt3/150;
BevScreenData$Numswt1= BevScreenData$Numswt1/160;
BevScreenData$Numswt2= BevScreenData$Numswt2/160;
BevScreenData$Numswt3= BevScreenData$Numswt3/160;
#drink coded off of dummy vectors of beverage
#100 is alcohol 10 is control 1 is placebo
#grouping is drink (100 = a 10=c 1=p);
#create group dummy codes
BevScreenData$A <- 0
BevScreenData$A <- 1*(BevScreenData$Drink==100)
BevScreenData$P <- 0
BevScreenData$P <- 1*(BevScreenData$Drink==1)
#ISD is zero if they did both arms, 1 if they did just descending
BevScreenData$Both <- 0
BevScreenData$Both <- 1*(BevScreenData$ISD==0)
BevScreenData$IX <- BevScreenData$A*BevScreenData$Both
#cor_mat <- cor(BevScreenData)
#p_mat <- cor.mtest(BevScreenData) # from earlier example
summary(BevScreenData)
## subid ISD Drink ISA
## Min. :8001 Min. :0.0000 Min. : 1.0 Min. :0.0000
## 1st Qu.:8203 1st Qu.:0.0000 1st Qu.: 1.0 1st Qu.:0.0000
## Median :8404 Median :0.0000 Median : 10.0 Median :0.0000
## Mean :8403 Mean :0.4928 Mean : 37.3 Mean :0.3357
## 3rd Qu.:8601 3rd Qu.:1.0000 3rd Qu.:100.0 3rd Qu.:1.0000
## Max. :8801 Max. :1.0000 Max. :100.0 Max. :1.0000
##
## ISC ISP ISE1 ISE2
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.3401 Mean :0.3242 Mean :0.3256 Mean :0.3372
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
##
## ISE3 exp Antisac1 Antisac2
## Min. :0.0000 Min. :1.000 Min. :1.429 Min. :1.825
## 1st Qu.:0.0000 1st Qu.:1.000 1st Qu.:3.651 1st Qu.:3.730
## Median :0.0000 Median :2.000 Median :4.365 Median :4.762
## Mean :0.3372 Mean :2.012 Mean :4.278 Mean :4.603
## 3rd Qu.:1.0000 3rd Qu.:3.000 3rd Qu.:5.079 3rd Qu.:5.397
## Max. :1.0000 Max. :3.000 Max. :6.429 Max. :6.508
## NA's :5 NA's :502
## Antisac3 PerSSRT1 PerSSRT2 PerSSRT3
## Min. :1.848 Min. :-9.217 Min. :-9.200 Min. :-9.452
## 1st Qu.:4.204 1st Qu.:-6.883 1st Qu.:-7.103 1st Qu.:-7.072
## Median :4.921 Median :-6.271 Median :-6.522 Median :-6.491
## Mean :4.814 Mean :-6.246 Mean :-6.440 Mean :-6.492
## 3rd Qu.:5.556 3rd Qu.:-5.713 3rd Qu.:-5.791 3rd Qu.:-5.906
## Max. :6.508 Max. :-3.268 Max. :-3.300 Max. :-3.850
## NA's :314 NA's :21 NA's :508 NA's :323
## Stroop1 Stroop2 Stroop3 Keeptrk1
## Min. :-5.876 Min. :-4.8918 Min. :-6.3179 Min. :4.140
## 1st Qu.:-2.911 1st Qu.:-2.5711 1st Qu.:-2.6232 1st Qu.:6.593
## Median :-2.182 Median :-1.8974 Median :-1.9002 Median :7.250
## Mean :-2.299 Mean :-1.9859 Mean :-2.0046 Mean :7.245
## 3rd Qu.:-1.573 3rd Qu.:-1.3334 3rd Qu.:-1.2941 3rd Qu.:8.019
## Max. : 1.279 Max. : 0.5987 Max. : 0.3363 Max. :9.556
## NA's :3 NA's :499 NA's :315
## Keeptrk2 Keeptrk3 Letmem1 Letmem2
## Min. :4.256 Min. : 4.566 Min. :0.2228 Min. :0.5582
## 1st Qu.:6.801 1st Qu.: 7.111 1st Qu.:2.3102 1st Qu.:2.4324
## Median :7.500 Median : 7.778 Median :2.8269 Median :3.1220
## Mean :7.421 Mean : 7.690 Mean :2.8434 Mean :3.1625
## 3rd Qu.:8.097 3rd Qu.: 8.333 3rd Qu.:3.3339 3rd Qu.:3.8655
## Max. :9.556 Max. :10.000 Max. :5.2360 Max. :5.2360
## NA's :500 NA's :311 NA's :497
## Letmem3 Nback1 Nback2 Nback3
## Min. :0.6523 Min. : 7.639 Min. : 8.333 Min. : 7.812
## 1st Qu.:2.5588 1st Qu.: 9.505 1st Qu.: 9.896 1st Qu.: 9.896
## Median :3.2837 Median :10.026 Median :10.547 Median :10.677
## Mean :3.3488 Mean :10.150 Mean :10.542 Mean :10.650
## 3rd Qu.:3.8655 3rd Qu.:10.807 3rd Qu.:11.296 3rd Qu.:11.458
## Max. :5.2360 Max. :12.500 Max. :12.500 Max. :12.500
## NA's :308 NA's :14 NA's :496 NA's :311
## Catswt1 Catswt2 Catswt3 Colswt1
## Min. :-4.6981 Min. :-4.4096 Min. :-4.3835 Min. :-5.3375
## 1st Qu.:-1.9345 1st Qu.:-1.7380 1st Qu.:-1.5834 1st Qu.:-2.0493
## Median :-1.1317 Median :-0.8877 Median :-0.8429 Median :-1.2872
## Mean :-1.3376 Mean :-1.1960 Mean :-1.1145 Mean :-1.4975
## 3rd Qu.:-0.5621 3rd Qu.:-0.4499 3rd Qu.:-0.4125 3rd Qu.:-0.6937
## Max. : 0.6707 Max. : 0.6340 Max. : 1.0581 Max. : 2.2062
## NA's :3 NA's :500 NA's :309 NA's :3
## Colswt2 Colswt3 Numswt1 Numswt2
## Min. :-4.5118 Min. :-4.2911 Min. :-5.9078 Min. :-4.8392
## 1st Qu.:-1.6789 1st Qu.:-1.5471 1st Qu.:-2.6004 1st Qu.:-2.0448
## Median :-1.0083 Median :-0.9349 Median :-1.8589 Median :-1.4384
## Mean :-1.2623 Mean :-1.1028 Mean :-2.0024 Mean :-1.5713
## 3rd Qu.:-0.5606 3rd Qu.:-0.4621 3rd Qu.:-1.1744 3rd Qu.:-0.8863
## Max. : 0.8862 Max. : 1.9011 Max. : 0.0194 Max. :-0.0607
## NA's :497 NA's :302 NA's :5 NA's :504
## Numswt3 A P Both
## Min. :-5.1276 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:-1.9073 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :-1.2244 Median :0.0000 Median :0.0000 Median :1.0000
## Mean :-1.4678 Mean :0.3357 Mean :0.3242 Mean :0.5072
## 3rd Qu.:-0.7596 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. : 0.6707 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :313
## IX
## Min. :0.0000
## 1st Qu.:0.0000
## Median :0.0000
## Mean :0.1758
## 3rd Qu.:0.0000
## Max. :1.0000
##
sapply(BevScreenData, sd, na.rm = TRUE)
## subid ISD Drink ISA ISC ISP
## 231.1240387 0.5003087 44.7594059 0.4725873 0.4740699 0.4684156
## ISE1 ISE2 ISE3 exp Antisac1 Antisac2
## 0.4689546 0.4730864 0.4730864 0.8146457 0.9855102 1.0326885
## Antisac3 PerSSRT1 PerSSRT2 PerSSRT3 Stroop1 Stroop2
## 0.9599391 0.9703352 1.0174650 0.9236292 1.1346894 0.9572384
## Stroop3 Keeptrk1 Keeptrk2 Keeptrk3 Letmem1 Letmem2
## 1.0517226 1.0300227 1.0399835 1.0224915 0.8728823 1.0375006
## Letmem3 Nback1 Nback2 Nback3 Catswt1 Catswt2
## 1.0224497 0.9554153 0.9990591 1.0819341 1.0398695 1.0201782
## Catswt3 Colswt1 Colswt2 Colswt3 Numswt1 Numswt2
## 0.9850354 1.1643845 1.0463809 0.9777514 1.1177185 0.9678278
## Numswt3 A P Both IX
## 1.0283237 0.4725873 0.4684156 0.5003087 0.3809181
df_subset <- BevScreenData[, 11:37]
setNames(seq_along(names(BevScreenData)), names(ScaledData))
## subid ISD Drink ISA ISC ISP ISE1 ISE2
## 1 2 3 4 5 6 7 8
## ISE3 exp Antisac1 Antisac2 Antisac3 PerSSRT1 PerSSRT2 PerSSRT3
## 9 10 11 12 13 14 15 16
## Stroop1 Stroop2 Stroop3 Keeptrk1 Keeptrk2 Keeptrk3 Letmem1 Letmem2
## 17 18 19 20 21 22 23 24
## Letmem3 Nback1 Nback2 Nback3 Catswt1 Catswt2 Catswt3 Colswt1
## 25 26 27 28 29 30 31 32
## Colswt2 Colswt3 Numswt1 Numswt2 Numswt3 A P Both
## 33 34 35 36 37 38 39 40
## IX
## 41
#ct <- corr.test(df_subset)
#r_mat <- ct$r
#p_mat <- ct$p
# Step 2: Plot correlations, only showing significant ones
#corrplot(r_mat,
# method = "circle",
# type = "upper",
# p.mat = p_mat, # p-values matrix
# sig.level = 0.05, # significance threshold
# insig = "blank") # options: "blank", "pch", "n"
#Implicit covariates "CFASuperFactorModel"
GrowthModel<-"
! regressions
AS=~1.0*Antisac1+AN2*Antisac2+AN3*Antisac3
SSRT=~1.0*PerSSRT1+SSRT2*PerSSRT2+SSRT3*PerSSRT3
STR=~1.0*Stroop1+S2*Stroop2+S3*Stroop3
Keep=~1.0*Keeptrk1+K2*Keeptrk2+K3*Keeptrk3
Let=~1.0*Letmem1+L2*Letmem2+L3*Letmem3
NB=~1.0*Nback1+N2*Nback2+N3*Nback3
cat=~1.0*Catswt1+A2*Catswt2+A3*Catswt3
col=~1.0*Colswt1+O2*Colswt2+O3*Colswt3
Num=~1.0*Numswt1+U2*Numswt2+U3*Numswt3
EF1=~EFAntisac*Antisac1+EFSSRT*PerSSRT1+EFStroop*Stroop1+EFKeeptrk*Keeptrk1+EFLetmem*Letmem1+EFNback*Nback1+
EFCatswt*Catswt1+EFColswt*Colswt1+EFNumswt*Numswt1
EF2=~EFAntisac*Antisac2+EFSSRT*PerSSRT2+EFStroop*Stroop2+EFKeeptrk*Keeptrk2+EFLetmem*Letmem2+EFNback*Nback2+
EFCatswt*Catswt2+EFColswt*Colswt2+EFNumswt*Numswt2
EF3=~EFAntisac*Antisac3+EFSSRT*PerSSRT3+EFStroop*Stroop3+EFKeeptrk*Keeptrk3+EFLetmem*Letmem3+EFNback*Nback3+
EFCatswt*Catswt3+EFColswt*Colswt3+EFNumswt*Numswt3
UP1=~UPKeeptrk*Keeptrk1+start(0.38)*Keeptrk1+UPLetmem*Letmem1+UPNback*Nback1
UP2=~UPKeeptrk*Keeptrk2+start(0.65)*Keeptrk2+UPLetmem*Letmem2+UPNback*Nback2
UP3=~UPKeeptrk*Keeptrk3+UPLetmem*Letmem3+UPNback*Nback3
SW1=~SWCatswt*Catswt1+SWColswt*Colswt1+SWNumswt*Numswt1
SW2=~SWCatswt*Catswt2+SWColswt*Colswt2+SWNumswt*Numswt2
SW3=~SWCatswt*Catswt3+SWColswt*Colswt3+SWNumswt*Numswt3
EF1 ~ A__EF1*A
EF2 ~ A__EF2*A
EF3 ~ A__EF3*A
EF1 ~ P__EF1*P
EF2 ~ P__EF2*P
EF3 ~ P__EF3*P
EF3 ~ Both__EF3*Both
EF3 ~ IX__EF3*IX
UP1 ~ A__UP1*A
UP1 ~ P__UP1*P
UP2 ~ A__UP2*A
UP2 ~ P__UP2*P
UP3 ~ A__UP3*A
UP3 ~ P__UP3*P
UP3 ~ Both__UP3*Both
UP3 ~ IX__UP3*IX
SW1 ~ A__SW1*A
SW1 ~ P__SW1*P
SW2 ~ A__SW2*A
SW3 ~ P__SW3*P
SW2 ~ P__SW2*P
SW3 ~ A__SW3*A
SW3 ~ IX__SW3*IX
SW3 ~ Both__SW3*Both
# Adjust each observed variable for predictors A, P, Both, and IX
Antisac1 ~ A + P
PerSSRT1 ~ A + P
Stroop1 ~ A + P
Keeptrk1 ~ A + P
Letmem1 ~ A + P
Nback1 ~ A + P
Catswt1 ~ A + P
Colswt1 ~ A + P
Numswt1 ~ A + P
! residuals, variances and covariances
!manifest variances
Antisac1 ~~ VAR_Antisac1*Antisac1
Antisac2 ~~ VAR_Antisac2*Antisac2
Antisac3 ~~ VAR_Antisac3*Antisac3
PerSSRT1 ~~ VAR_PerSSRT1*PerSSRT1
PerSSRT2 ~~ VAR_PerSSRT2*PerSSRT2
PerSSRT3 ~~ VAR_PerSSRT3*PerSSRT3
Stroop1 ~~ VAR_Stroop1*Stroop1
Stroop2 ~~ VAR_Stroop2*Stroop2
Stroop3 ~~ VAR_Stroop3*Stroop3
Keeptrk1 ~~ VAR_Keeptrk1*Keeptrk1
Keeptrk2 ~~ VAR_Keeptrk2*Keeptrk2
Keeptrk3 ~~ VAR_Keeptrk3*Keeptrk3
Letmem1 ~~ VAR_Letmem1*Letmem1
Letmem2 ~~ VAR_Letmem2*Letmem2
Letmem3 ~~ VAR_Letmem3*Letmem3
!Covariances of Letmem
!Letmem1 ~~ C_Letmem1_Letmem2*Letmem2
!Letmem1 ~~ C_Letmem1_Letmem3*Letmem3
!Letmem2 ~~ C_Letmem2_Letmem3*Letmem3
Nback1 ~~ VAR_Nback1*Nback1
Nback2 ~~ VAR_Nback2*Nback2
Nback3 ~~ VAR_Nback3*Nback3
Catswt1 ~~ VAR_Catswt1*Catswt1
Catswt2 ~~ VAR_Catswt2*Catswt2
Catswt3 ~~ VAR_Catswt3*Catswt3
Colswt1 ~~ VAR_Colswt1*Colswt1
Colswt2 ~~ VAR_Colswt2*Colswt2
Colswt3 ~~ VAR_Colswt3*Colswt3
Numswt1 ~~ VAR_Numswt1*Numswt1
Numswt2 ~~ VAR_Numswt2*Numswt2
Numswt3 ~~ VAR_Numswt3*Numswt3
!Task variances
AS ~~ VAR_AS*AS
SSRT ~~ VAR_SSRT*SSRT
STR ~~ VAR_STR*STR
Keep ~~ VAR_Keep*Keep
Let ~~ VAR_Let*Let
NB ~~ VAR_NB*NB
cat ~~ VAR_cat*cat
col ~~ VAR_col*col
Num ~~ VAR_Num*Num
!Superfactor Variances & Covariances
EF1 ~~ 1.0*EF1
EF2 ~~ 1.0*EF2
EF3 ~~ 1.0*EF3
EF1 ~~ 1*EF2
EF1 ~~ 1*EF3
EF2 ~~ 1*EF3
UP1 ~~ 1.0*UP1
UP2 ~~ 1.0*UP2
UP3 ~~ 1.0*UP3
UP1 ~~ 1*UP2
UP2 ~~ 1*UP3
UP1 ~~ 1*UP3
SW1 ~~ 1.0*SW1
SW2 ~~ 1.0*SW2
SW3 ~~ 1.0*SW3
SW1 ~~ 1*SW2
SW1 ~~ 1*SW3
SW2 ~~ 1*SW3
!Covariances of Updating with Switch
UP1 ~~ 0*SW1
UP2 ~~ 0*SW2
UP3 ~~ 0*SW3
! means
!Superfactor means for Ascending and Descending
!EF2~const__EF2*1
!EF3~const__EF3*1
!UP2~const__UP2*1
!UP3~const__UP3*1
!SW2~const__SW2*1
!SW3~const__SW3*1
!Task factor means
AS~NA*1
SSRT~NA*1
STR~NA*1
Keep~NA*1
Let~NA*1
NB~NA*1
cat~NA*1
col~NA*1
Num~NA*1
!First manifest variable free, others fixed to equality
Antisac1~IAntisac1*1;
Antisac2~0*1;
Antisac3~0*1;
PerSSRT1~IPerSSRT1*1;
PerSSRT2~0*1;
PerSSRT3~0*1;
Stroop1~IStroop1*1;
Stroop2~0*1;
Stroop3~0*1;
Keeptrk1~IKeeptrk1*1;
Keeptrk2~0*1;
Keeptrk3~0*1;
Letmem1~ILetmem1*1;
Letmem2~0*1;
Letmem3~0*1;
Nback1~INback1*1;
Nback2~0*1;
Nback3~0*1;
Catswt1~ICatswt1*1;
Catswt2~0*1;
Catswt3~0*1;
Colswt1~IColswt1*1;
Colswt2~0*1;
Colswt3~0*1;
Numswt1~INumswt1*1;
Numswt2~0*1;
Numswt3~0*1;
!Baseline superfactor means zeroed out
EF1~0*1;
EF2~0*1;
EF3~0*1;
UP1~0*1;
UP2~0*1;
UP3~0*1;
SW1~0*1;
SW2~0*1;
SW3~0*1;
";
GrowthModelResult<-lavaan(GrowthModel, data=BevScreenData, fixed.x=TRUE, missing="FIML")
## Warning: lavaan->lav_model_vcov():
## The variance-covariance matrix of the estimated parameters (vcov) does not
## appear to be positive definite! The smallest eigenvalue (= 1.135732e-12)
## is close to zero. This may be a symptom that the model is not identified.
summary(GrowthModelResult, fit.measures=TRUE,standardized=TRUE);
## lavaan 0.6-21 ended normally after 448 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 159
## Number of equality constraints 30
##
## Number of observations 694
## Number of missing patterns 130
##
## Model Test User Model:
##
## Test statistic 494.438
## Degrees of freedom 384
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 4226.737
## Degrees of freedom 459
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.971
## Tucker-Lewis Index (TLI) 0.965
##
## Robust Comparative Fit Index (CFI) 1.000
## Robust Tucker-Lewis Index (TLI) -0.196
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -14477.928
## Loglikelihood unrestricted model (H1) -14230.709
##
## Akaike (AIC) 29213.856
## Bayesian (BIC) 29799.835
## Sample-size adjusted Bayesian (SABIC) 29390.238
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.020
## 90 Percent confidence interval - lower 0.015
## 90 Percent confidence interval - upper 0.025
## P-value H_0: RMSEA <= 0.050 1.000
## P-value H_0: RMSEA >= 0.080 0.000
##
## Robust RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.000
## P-value H_0: Robust RMSEA <= 0.050 1.000
## P-value H_0: Robust RMSEA >= 0.080 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.055
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## AS =~
## Antsc1 1.000 0.334 0.337
## Antsc2 (AN2) 1.380 0.286 4.830 0.000 0.460 0.474
## Antsc3 (AN3) 1.423 0.295 4.818 0.000 0.475 0.480
## SSRT =~
## PSSRT1 1.000 0.347 0.357
## PSSRT2 (SSRT2) 1.381 0.475 2.907 0.004 0.479 0.481
## PSSRT3 (SSRT3) 1.398 0.482 2.902 0.004 0.485 0.525
## STR =~
## Strop1 1.000 0.692 0.614
## Strop2 (S2) 0.878 0.131 6.715 0.000 0.608 0.640
## Strop3 (S3) 0.903 0.137 6.605 0.000 0.625 0.603
## Keep =~
## Kptrk1 1.000 0.541 0.523
## Kptrk2 (K2) 1.213 0.143 8.482 0.000 0.656 0.673
## Kptrk3 (K3) 1.220 0.144 8.488 0.000 0.659 0.639
## Let =~
## Letmm1 1.000 0.054 0.062
## Letmm2 (L2) 6.572 23.834 0.276 0.783 0.356 0.364
## Letmm3 (L3) 6.367 23.019 0.277 0.782 0.344 0.333
## NB =~
## Nback1 1.000 0.606 0.632
## Nback2 (N2) 1.314 0.090 14.596 0.000 0.797 0.783
## Nback3 (N3) 1.302 0.089 14.707 0.000 0.790 0.734
## cat =~
## Ctswt1 1.000 0.562 0.545
## Ctswt2 (A2) 0.509 0.236 2.155 0.031 0.286 0.284
## Ctswt3 (A3) 0.549 0.255 2.149 0.032 0.308 0.312
## col =~
## Clswt1 1.000 0.314 0.272
## Clswt2 (O2) 1.606 0.421 3.811 0.000 0.505 0.478
## Clswt3 (O3) 1.582 0.429 3.690 0.000 0.497 0.505
## Num =~
## Nmswt1 1.000 0.509 0.459
## Nmswt2 (U2) 0.950 0.146 6.510 0.000 0.484 0.467
## Nmswt3 (U3) 1.001 0.147 6.803 0.000 0.510 0.490
## EF1 =~
## Antsc1 (EFAn) 0.730 0.060 12.077 0.000 0.736 0.742
## PSSRT1 (EFSS) 0.195 0.036 5.366 0.000 0.196 0.201
## Strop1 (EFSt) 0.267 0.046 5.842 0.000 0.269 0.239
## Kptrk1 (EFKp) 0.214 0.048 4.436 0.000 0.215 0.208
## Letmm1 (EFLt) 0.272 0.040 6.839 0.000 0.274 0.313
## Nback1 (EFNb) 0.330 0.043 7.620 0.000 0.333 0.347
## Ctswt1 (EFCt) 0.316 0.044 7.153 0.000 0.319 0.309
## Clswt1 (EFCl) 0.211 0.045 4.690 0.000 0.213 0.184
## Nmswt1 (EFNm) 0.299 0.050 5.961 0.000 0.301 0.271
## EF2 =~
## Antsc2 (EFAn) 0.730 0.060 12.077 0.000 0.767 0.790
## PSSRT2 (EFSS) 0.195 0.036 5.366 0.000 0.204 0.205
## Strop2 (EFSt) 0.267 0.046 5.842 0.000 0.281 0.296
## Kptrk2 (EFKp) 0.214 0.048 4.436 0.000 0.224 0.230
## Letmm2 (EFLt) 0.272 0.040 6.839 0.000 0.286 0.292
## Nback2 (EFNb) 0.330 0.043 7.620 0.000 0.347 0.341
## Ctswt2 (EFCt) 0.316 0.044 7.153 0.000 0.332 0.330
## Clswt2 (EFCl) 0.211 0.045 4.690 0.000 0.221 0.210
## Nmswt2 (EFNm) 0.299 0.050 5.961 0.000 0.314 0.303
## EF3 =~
## Antsc3 (EFAn) 0.730 0.060 12.077 0.000 0.776 0.784
## PSSRT3 (EFSS) 0.195 0.036 5.366 0.000 0.207 0.223
## Strop3 (EFSt) 0.267 0.046 5.842 0.000 0.284 0.274
## Kptrk3 (EFKp) 0.214 0.048 4.436 0.000 0.227 0.220
## Letmm3 (EFLt) 0.272 0.040 6.839 0.000 0.289 0.279
## Nback3 (EFNb) 0.330 0.043 7.620 0.000 0.351 0.326
## Ctswt3 (EFCt) 0.316 0.044 7.153 0.000 0.336 0.339
## Clswt3 (EFCl) 0.211 0.045 4.690 0.000 0.224 0.227
## Nmswt3 (EFNm) 0.299 0.050 5.961 0.000 0.317 0.305
## UP1 =~
## Kptrk1 (UPKp) 0.389 0.058 6.736 0.000 0.399 0.386
## Letmm1 (UPLt) 0.615 0.067 9.239 0.000 0.631 0.720
## Nback1 (UPNb) 0.267 0.048 5.553 0.000 0.274 0.285
## UP2 =~
## Kptrk2 (UPKp) 0.389 0.058 6.736 0.000 0.409 0.420
## Letmm2 (UPLt) 0.615 0.067 9.239 0.000 0.647 0.663
## Nback2 (UPNb) 0.267 0.048 5.553 0.000 0.281 0.276
## UP3 =~
## Kptrk3 (UPKp) 0.389 0.058 6.736 0.000 0.414 0.401
## Letmm3 (UPLt) 0.615 0.067 9.239 0.000 0.655 0.632
## Nback3 (UPNb) 0.267 0.048 5.553 0.000 0.284 0.264
## SW1 =~
## Ctswt1 (SWCt) 0.570 0.039 14.606 0.000 0.573 0.555
## Clswt1 (SWCl) 0.614 0.042 14.710 0.000 0.616 0.534
## Nmswt1 (SWNm) 0.692 0.045 15.433 0.000 0.695 0.626
## SW2 =~
## Ctswt2 (SWCt) 0.570 0.039 14.606 0.000 0.575 0.572
## Clswt2 (SWCl) 0.614 0.042 14.710 0.000 0.619 0.586
## Nmswt2 (SWNm) 0.692 0.045 15.433 0.000 0.698 0.673
## SW3 =~
## Ctswt3 (SWCt) 0.570 0.039 14.606 0.000 0.583 0.590
## Clswt3 (SWCl) 0.614 0.042 14.710 0.000 0.628 0.637
## Nmswt3 (SWNm) 0.692 0.045 15.433 0.000 0.708 0.680
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## EF1 ~
## A (A__EF1) 0.237 0.058 4.109 0.000 0.235 0.111
## EF2 ~
## A (A__EF2) -0.745 0.173 -4.320 0.000 -0.710 -0.335
## EF3 ~
## A (A__EF3) -0.816 0.176 -4.646 0.000 -0.768 -0.363
## EF1 ~
## P (P__EF1) 0.292 0.058 5.025 0.000 0.290 0.136
## EF2 ~
## P (P__EF2) -0.171 0.160 -1.073 0.283 -0.163 -0.076
## EF3 ~
## P (P__EF3) -0.059 0.138 -0.424 0.672 -0.055 -0.026
## Both (B__E) 0.108 0.104 1.044 0.296 0.102 0.051
## IX (IX__E) 0.081 0.181 0.450 0.652 0.077 0.029
## UP1 ~
## A (A__UP1) 0.399 0.048 8.373 0.000 0.389 0.184
## P (P__UP1) 0.538 0.047 11.416 0.000 0.524 0.245
## UP2 ~
## A (A__UP2) -0.675 0.214 -3.151 0.002 -0.642 -0.303
## P (P__UP2) 0.030 0.204 0.146 0.884 0.028 0.013
## UP3 ~
## A (A__UP3) -0.356 0.244 -1.457 0.145 -0.334 -0.158
## P (P__UP3) 0.164 0.176 0.931 0.352 0.154 0.072
## Both (B__U) 0.587 0.154 3.823 0.000 0.552 0.276
## IX (IX__U) 0.074 0.257 0.288 0.773 0.070 0.027
## SW1 ~
## A (A__SW1) -0.168 0.063 -2.673 0.008 -0.167 -0.079
## P (P__SW1) -0.195 0.064 -3.063 0.002 -0.194 -0.091
## SW2 ~
## A (A__SW2) -0.169 0.170 -0.995 0.320 -0.168 -0.079
## SW3 ~
## P (P__SW3) -0.049 0.132 -0.369 0.712 -0.048 -0.022
## SW2 ~
## P (P__SW2) 0.135 0.159 0.853 0.394 0.134 0.063
## SW3 ~
## A (A__SW3) 0.203 0.171 1.187 0.235 0.199 0.094
## IX (IX__S) -0.292 0.172 -1.699 0.089 -0.285 -0.108
## Both (B__S) 0.496 0.100 4.978 0.000 0.485 0.242
## Antisac1 ~
## A -0.190 0.062 -3.050 0.002 -0.190 -0.091
## P -0.202 0.062 -3.276 0.001 -0.202 -0.095
## PerSSRT1 ~
## A -0.045 0.088 -0.508 0.611 -0.045 -0.022
## P -0.045 0.089 -0.502 0.615 -0.045 -0.021
## Stroop1 ~
## A -0.083 0.096 -0.865 0.387 -0.083 -0.035
## P -0.072 0.095 -0.750 0.453 -0.072 -0.030
## Keeptrk1 ~
## A -0.172 0.083 -2.077 0.038 -0.172 -0.079
## P -0.271 0.083 -3.258 0.001 -0.271 -0.123
## Letmem1 ~
## A -0.310 0.061 -5.067 0.000 -0.310 -0.167
## P -0.357 0.063 -5.638 0.000 -0.357 -0.191
## Nback1 ~
## A -0.180 0.073 -2.462 0.014 -0.180 -0.089
## P -0.223 0.073 -3.079 0.002 -0.223 -0.109
## Catswt1 ~
## A -0.097 0.069 -1.404 0.160 -0.097 -0.045
## P -0.029 0.069 -0.420 0.674 -0.029 -0.013
## Colswt1 ~
## A 0.000 0.079 0.002 0.998 0.000 0.000
## P -0.018 0.080 -0.229 0.819 -0.018 -0.007
## Numswt1 ~
## A 0.122 0.068 1.805 0.071 0.122 0.052
## P 0.053 0.068 0.782 0.434 0.053 0.022
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .EF1 ~~
## .EF2 1.000 1.000 1.000
## .EF3 1.000 1.000 1.000
## .EF2 ~~
## .EF3 1.000 1.000 1.000
## .UP1 ~~
## .UP2 1.000 1.000 1.000
## .UP2 ~~
## .UP3 1.000 1.000 1.000
## .UP1 ~~
## .UP3 1.000 1.000 1.000
## .SW1 ~~
## .SW2 1.000 1.000 1.000
## .SW3 1.000 1.000 1.000
## .SW2 ~~
## .SW3 1.000 1.000 1.000
## .UP1 ~~
## .SW1 0.000 0.000 0.000
## .UP2 ~~
## .SW2 0.000 0.000 0.000
## .UP3 ~~
## .SW3 0.000 0.000 0.000
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## AS 3.469 0.720 4.816 0.000 10.394 10.394
## SSRT -4.610 1.588 -2.902 0.004 -13.279 -13.279
## STR -2.159 0.330 -6.545 0.000 -3.119 -3.119
## Keep 6.259 0.739 8.468 0.000 11.576 11.576
## Let 0.517 1.873 0.276 0.783 9.548 9.548
## NB 8.210 0.560 14.654 0.000 13.539 13.539
## cat -2.154 1.010 -2.133 0.033 -3.836 -3.836
## col -0.768 0.208 -3.691 0.000 -2.443 -2.443
## Num -1.561 0.238 -6.559 0.000 -3.063 -3.063
## .Antisc1 (IAn1) 0.807 0.720 1.121 0.262 0.807 0.814
## .Antisc2 0.000 0.000 0.000
## .Antisc3 0.000 0.000 0.000
## .PrSSRT1 (IPSS) -1.639 1.588 -1.032 0.302 -1.639 -1.683
## .PrSSRT2 0.000 0.000 0.000
## .PrSSRT3 0.000 0.000 0.000
## .Stroop1 (ISt1) -0.135 0.335 -0.401 0.688 -0.135 -0.119
## .Stroop2 0.000 0.000 0.000
## .Stroop3 0.000 0.000 0.000
## .Keptrk1 (IKp1) 0.974 0.744 1.310 0.190 0.974 0.942
## .Keptrk2 0.000 0.000 0.000
## .Keptrk3 0.000 0.000 0.000
## .Letmem1 (ILt1) 2.309 1.868 1.236 0.216 2.309 2.633
## .Letmem2 0.000 0.000 0.000
## .Letmem3 0.000 0.000 0.000
## .Nback1 (INb1) 1.925 0.562 3.428 0.001 1.925 2.008
## .Nback2 0.000 0.000 0.000
## .Nback3 0.000 0.000 0.000
## .Catswt1 (ICt1) 0.875 1.008 0.868 0.386 0.875 0.848
## .Catswt2 0.000 0.000 0.000
## .Catswt3 0.000 0.000 0.000
## .Colswt1 (ICl1) -0.684 0.214 -3.191 0.001 -0.684 -0.593
## .Colswt2 0.000 0.000 0.000
## .Colswt3 0.000 0.000 0.000
## .Numswt1 (INm1) -0.473 0.235 -2.014 0.044 -0.473 -0.426
## .Numswt2 0.000 0.000 0.000
## .Numswt3 0.000 0.000 0.000
## .EF1 0.000 0.000 0.000
## .EF2 0.000 0.000 0.000
## .EF3 0.000 0.000 0.000
## .UP1 0.000 0.000 0.000
## .UP2 0.000 0.000 0.000
## .UP3 0.000 0.000 0.000
## .SW1 0.000 0.000 0.000
## .SW2 0.000 0.000 0.000
## .SW3 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .A (VAR_A1) 0.338 0.030 11.105 0.000 0.338 0.344
## .A (VAR_A2) 0.143 0.026 5.530 0.000 0.143 0.152
## .A (VAR_A3) 0.152 0.025 6.042 0.000 0.152 0.155
## .P (VAR_PSSRT1) 0.790 0.072 10.969 0.000 0.790 0.833
## .P (VAR_PSSRT2) 0.723 0.096 7.512 0.000 0.723 0.727
## .P (VAR_PSSRT3) 0.578 0.079 7.348 0.000 0.578 0.675
## .S (VAR_S1) 0.719 0.092 7.800 0.000 0.719 0.566
## .S (VAR_S2) 0.452 0.068 6.688 0.000 0.452 0.502
## .S (VAR_S3) 0.604 0.070 8.659 0.000 0.604 0.562
## .K (VAR_K1) 0.580 0.054 10.651 0.000 0.580 0.542
## .K (VAR_K2) 0.286 0.048 5.897 0.000 0.286 0.301
## .K (VAR_K3) 0.395 0.049 8.036 0.000 0.395 0.370
## .L (VAR_L1) 0.313 0.060 5.179 0.000 0.313 0.407
## .L (VAR_L2) 0.293 0.049 6.023 0.000 0.293 0.307
## .L (VAR_L3) 0.413 0.048 8.608 0.000 0.413 0.385
## .N (VAR_Nb1) 0.372 0.034 10.810 0.000 0.372 0.404
## .N (VAR_Nb2) 0.183 0.037 4.976 0.000 0.183 0.177
## .N (VAR_Nb3) 0.316 0.038 8.273 0.000 0.316 0.273
## .C (VAR_Ct1) 0.321 0.146 2.197 0.028 0.321 0.301
## .C (VAR_Ct2) 0.476 0.061 7.808 0.000 0.476 0.472
## .C (VAR_Ct3) 0.430 0.052 8.258 0.000 0.430 0.440
## .C (VAR_Cl1) 0.811 0.058 14.006 0.000 0.811 0.609
## .C (VAR_Cl2) 0.420 0.060 6.962 0.000 0.420 0.377
## .C (VAR_Cl3) 0.279 0.047 5.956 0.000 0.279 0.288
## .N (VAR_Nm1) 0.403 0.045 9.049 0.000 0.403 0.327
## .N (VAR_Nm2) 0.242 0.037 6.605 0.000 0.242 0.225
## .N (VAR_Nm3) 0.223 0.036 6.200 0.000 0.223 0.205
## A (VAR_AS) 0.111 0.077 1.445 0.148 1.000 1.000
## S (VAR_SS) 0.121 0.063 1.910 0.056 1.000 1.000
## S (VAR_ST) 0.479 0.101 4.725 0.000 1.000 1.000
## K (VAR_Kp) 0.292 0.065 4.474 0.000 1.000 1.000
## L (VAR_Lt) 0.003 0.023 0.127 0.899 1.000 1.000
## N (VAR_NB) 0.368 0.048 7.649 0.000 1.000 1.000
## c (VAR_ct) 0.315 0.151 2.091 0.037 1.000 1.000
## c (VAR_cl) 0.099 0.051 1.938 0.053 1.000 1.000
## N (VAR_Nm) 0.260 0.065 3.978 0.000 1.000 1.000
## .E 1.000 0.984 0.984
## .E 1.000 0.907 0.907
## .E 1.000 0.886 0.886
## .U 1.000 0.950 0.950
## .U 1.000 0.904 0.904
## .U 1.000 0.884 0.884
## .S 1.000 0.993 0.993
## .S 1.000 0.985 0.985
## .S 1.000 0.956 0.956
clipboard(GrowthModelResult)
## File saved in the clipboard; please paste it in any program you wish.
clipboard(GrowthModelResult,
what = "est", # <- estimates, not matrices
standardized = TRUE,
digits = 3, ci = TRUE)
## File saved in the clipboard; please paste it in any program you wish.
clipboard(GrowthModelResult,
what = "est", # estimates
standardized = TRUE, # include standardized columns
ci = TRUE, # optional: confidence intervals
digits = 2) # rounding
## File saved in the clipboard; please paste it in any program you wish.
clipboard(GrowthModelResult, "fit", "coef", standardized=TRUE)
## File saved in the clipboard; please paste it in any program you wish.
clipboard(GrowthModelResult, "coef", standardized=TRUE)
## File saved in the clipboard; please paste it in any program you wish.