> omegaSem(r9,n.obs=198)
Error in parse(text = x, keep.source = FALSE) :
<text>:2:0: unexpected end of input
This error probably comes from calling factor("~") and
psych::omegaSem(data) will do that if all the columns in data are very
highly correlated with one another. In that case omega(data, nfactor=n)
will not be able to find n factors in the data but it returns "~" in place
of the factors that it could not find. E.g.,
> fakeData <- data.frame(A=1/(1:40), B=1/(2:41), C=1/(3:42), D=1/(4:43),
E=1/(5:44))
> cor(fakeData)
A B C D E
A 1.0000000 0.9782320 0.9481293 0.9215071 0.8988962
B 0.9782320 1.0000000 0.9932037 0.9811287 0.9684658
C 0.9481293 0.9932037 1.0000000 0.9969157 0.9906838
D 0.9215071 0.9811287 0.9969157 1.0000000 0.9983014
E 0.8988962 0.9684658 0.9906838 0.9983014 1.0000000
> psych::omegaSem(fakeData)
Loading required namespace: lavaan
Loading required namespace: GPArotation
In factor.stats, I could not find the RMSEA upper bound . Sorry about that
Error in parse(text = x, keep.source = FALSE) :
<text>:2:0: unexpected end of input
1: ~
^
In addition: Warning message:
In cov2cor(t(w) %*% r %*% w) :
diag(.) had 0 or NA entries; non-finite result is doubtful
> psych::omega(fakeData)$model$lavaan
In factor.stats, I could not find the RMSEA upper bound . Sorry about that
[1] g =~ +A+B+C+D+E F1=~ + B + C + D + E F2=~ + A
[4] F3=~
Warning message:
In cov2cor(t(w) %*% r %*% w) :
diag(.) had 0 or NA entries; non-finite result is doubtful
You can get a result if you use nfactors=n where n is the number of the
good F<n> entries in psych::omega()$model$lavaan:
> psych::omegaSem(fakeData, nfactors=2)
...
Measures of factor score adequacy
g F1* F2*
Correlation of scores with factors 11.35 12.42 84.45
Multiple R square of scores with factors 128.93 154.32 7131.98
Minimum correlation of factor score estimates 256.86 307.64 14262.96
...
Does that work with your data?
This is a problem that the maintainer of psych,
> maintainer("psych")
[1] "William Revelle <reve...@northwestern.edu>"
would like to know about.
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Thu, Aug 29, 2019 at 9:03 AM Danilo Esteban Rodriguez Zapata via R-help <
r-help@r-project.org> wrote:
> This is a problem related to my last question referred to the omegaSem()
> function in the psych package (that is already solved because I realized
> that I was missing a variable assignment and because of that I had an
> 'object not found' error:
>
>
> https://stackoverflow.com/questions/57661750/one-of-the-omegasem-function-arguments-is-an-object-not-found
>
> I was trying to use that function following the guide to find McDonald's
> hierarchical Omega by Dr William Revelle:
>
> http://personality-project.org/r/psych/HowTo/omega.pdf
>
> So now, with the variable error corrected, I'm having a different error
> that does not occur when I use the same function with the example database
> (Thurstone) provided in the tutorial that comes with the psych package. I
> mean, I'm able to use the function succesfully using the Thurstone data
> (with no other action, I have the expected result) but the function doesn't
> work when I use my own data.
>
> I searched over other posted questions, and the actions that they perform
> are not even similar to what I'm trying to do. I have almost two weeks
> using R, so I'm not able to identify yet how can I extrapolate the
> solutions for that error message to my procedure (because it seems to be
> frequent), although I have basic code knowledge. However related questions
> give no anwer by now.
>
> Additionally, I decided to look over more documentation about the package,
> and when I was testing other functions, I was able to use the omegaSem()
> function with another example database, BUT after and only after I did the
> schmid transformation. So with that, I discovered that when I tried to use
> the omegaSem() function before the schmid tranformation I had the same
> error message, but not after that tranformation with this second example
> database.
>
> This make sense with the actual procedure of the omegaSem() procedure, but
> I'm suposing that it must be done completely and automatically by the
> omegaSem() function as it is explained in the guide and I have understood
> until now, as it follows:
>
> 1. omegaSem() applies factor analysis
> 2. omegaSem() rotate factors obliquely
> 3. omegaSem() transform data with Schmid Leiman (schmid)
>
> -------necessary steps to print output-------------------
>
> 4. omegaSem() print McDonald's hierarchical Omega
>
> So here, another questions appears: - Why the omegaSem() function works
> with the Thurstone database without any other action and only works for the
> second example database after performing the schmid transformation? - Why
> with other databases I dont have the same output applying the omegaSem()
> function directly? - How is this related to the error message that the
> compiler shows when I try to apply the function directly to the database?
>
>
> This is the code that I'm using now: (example of the succesfull omegaSem()
> done after schmid tranformation not included)
>
> ```
> > library(psych)
> > library(ctv, lavaan)
> > library(GPArotation)
> > my.data <- read.file()
> Data from the .csv file
> D:\Users\Admon\Documents\prueba_export_1563806208742.csv has been loaded.
> > describe(my.data)
> vars n mean sd median trimmed mad min max range skew
> kurtosis
> AUT_10_04 1 195 4.11 0.90 4 4.23 1.48 1 5 4 -0.92
> 0.33
> AUN_07_01 2 195 3.79 1.14 4 3.90 1.48 1 5 4 -0.59
> -0.71
> AUN_07_02 3 195 3.58 1.08 4 3.65 1.48 1 5 4 -0.39
> -0.56
> AUN_09_01 4 195 4.15 0.80 4 4.23 1.48 1 5 4 -0.76
> 0.51
> AUN_10_01 5 195 4.25 0.79 4 4.34 1.48 1 5 4 -0.91
> 0.74
> AUT_11_01 6 195 4.43 0.77 5 4.56 0.00 1 5 4 -1.69
> 3.77
> AUT_17_01 7 195 4.46 0.67 5 4.55 0.00 1 5 4 -1.34
> 2.96
> AUT_20_03 8 195 4.44 0.65 5 4.53 0.00 2 5 3 -0.84
> 0.12
> CRE_05_02 9 195 2.47 1.01 2 2.43 1.48 1 5 4 0.35
> -0.46
> CRE_07_04 10 195 2.42 1.08 2 2.34 1.48 1 5 4 0.51
> -0.43
> CRE_10_01 11 195 4.41 0.68 5 4.51 0.00 2 5 3 -0.79
> -0.12
> CRE_16_02 12 195 2.75 1.23 3 2.69 1.48 1 5 4 0.29
> -0.96
> EFEC_03_07 13 195 4.35 0.69 4 4.45 1.48 1 5 4 -0.95
> 1.59
> EFEC_05 14 195 4.53 0.59 5 4.60 0.00 3 5 2 -0.82
> -0.34
> EFEC_09_02 15 195 2.19 0.91 2 2.11 1.48 1 5 4 0.57
> -0.03
> EFEC_16_03 16 195 4.21 0.77 4 4.29 1.48 2 5 3 -0.71
> -0.04
> EVA_02_01 17 195 4.47 0.61 5 4.54 0.00 3 5 2 -0.70
> -0.50
> EVA_07_01 18 195 4.38 0.60 4 4.43 1.48 3 5 2 -0.40
> -0.70
> EVA_12_02 19 195 2.64 1.22 2 2.59 1.48 1 5 4 0.30
> -1.00
> EVA_15_06 20 195 4.19 0.74 4 4.26 1.48 2 5 3 -0.55
> -0.29
> FLX_04_01 21 195 4.32 0.69 4 4.41 1.48 2 5 3 -0.71
> 0.05
> FLX_04_05 22 195 4.23 0.74 4 4.32 0.00 1 5 4 -0.99
> 1.69
> FLX_08_02 23 195 2.87 1.19 3 2.86 1.48 1 5 4 0.07
> -1.05
> FLX_10_03 24 195 4.30 0.71 4 4.39 1.48 2 5 3 -0.84
> 0.66
> IDO_01_06 25 195 3.10 1.26 3 3.13 1.48 1 5 4 -0.19
> -1.08
> IDO_05_02 26 195 2.89 1.26 3 2.87 1.48 1 5 4 -0.03
> -1.16
> IDO_09_03 27 195 3.87 0.97 4 3.99 1.48 1 5 4 -0.84
> 0.47
> IDO_17_01 28 195 3.94 0.88 4 4.02 0.00 1 5 4 -0.93
> 1.23
> IE_01_03 29 195 4.01 0.88 4 4.10 1.48 1 5 4 -0.91
> 0.94
> IE_10_03 30 195 4.15 1.00 4 4.34 1.48 1 5 4 -1.31
> 1.28
> IE_13_03 31 195 4.16 0.91 4 4.30 1.48 1 5 4 -1.26
> 1.74
> IE_15_01 32 195 4.26 0.85 4 4.39 1.48 1 5 4 -1.16
> 1.08
> LC_07_03 33 195 4.25 0.72 4 4.34 0.00 1 5 4 -1.07
> 2.64
> LC_08_02 34 195 3.25 1.22 4 3.31 1.48 1 5 4 -0.41
> -0.90
> LC_11_03 35 195 3.50 1.14 4 3.56 1.48 1 5 4 -0.38
> -0.68
> LC_11_05 36 195 4.42 0.69 5 4.52 0.00 1 5 4 -1.14
> 1.97
> ME_02_03 37 195 4.11 0.92 4 4.25 1.48 1 5 4 -1.18
> 1.29
> ME_07_06 38 195 3.19 1.28 3 3.24 1.48 1 5 4 -0.28
> -1.03
> ME_09_01 39 195 4.24 0.77 4 4.34 1.48 1 5 4 -1.12
> 2.19
> ME_09_06 40 195 3.23 1.33 4 3.29 1.48 1 5 4 -0.31
> -1.14
> NEG_01_03 41 195 4.18 0.76 4 4.27 0.00 1 5 4 -1.28
> 3.33
> NEG_05_04 42 195 4.27 0.69 4 4.35 0.00 1 5 4 -0.87
> 1.75
> NEG_07_03 43 195 4.32 0.73 4 4.43 1.48 1 5 4 -1.05
> 1.55
> NEG_08_01 44 195 3.95 0.88 4 4.02 1.48 1 5 4 -0.67
> 0.29
> OP_03_05 45 195 4.32 0.66 4 4.39 0.00 1 5 4 -0.99
> 2.54
> OP_12_01 46 195 4.16 0.80 4 4.25 1.48 1 5 4 -1.02
> 1.57
> OP_14_01 47 195 4.27 0.78 4 4.38 1.48 1 5 4 -1.15
> 1.67
> OP_14_02 48 195 4.36 0.68 4 4.44 1.48 1 5 4 -1.07
> 2.35
> ORL_01_03 49 195 4.36 0.77 4 4.49 1.48 1 5 4 -1.31
> 2.08
> ORL_03_01 50 195 4.41 0.69 4 4.50 1.48 1 5 4 -1.28
> 2.77
> ORL_03_05 51 195 4.36 0.74 4 4.48 1.48 2 5 3 -1.13
> 1.28
> ORL_10_05 52 195 4.40 0.68 4 4.48 1.48 1 5 4 -1.18
> 2.57
> PER_08_02 53 195 3.23 1.29 4 3.29 1.48 1 5 4 -0.26
> -1.17
> PER_16_01 54 195 4.29 0.70 4 4.38 1.48 2 5 3 -0.74
> 0.27
> PER_19_06 55 195 3.19 1.25 3 3.24 1.48 1 5 4 -0.20
> -1.06
> PER_22_06 56 195 4.21 0.73 4 4.29 0.00 1 5 4 -0.89
> 1.46
> PLA_01_03 57 195 4.23 0.68 4 4.31 0.00 2 5 3 -0.81
> 1.18
> PLA_05_01 58 195 4.06 0.77 4 4.13 0.00 1 5 4 -0.89
> 1.29
> PLA_07_02 59 195 2.94 1.19 3 2.94 1.48 1 5 4 0.00
> -1.02
> PLA_10_01 60 195 4.03 0.76 4 4.08 0.00 1 5 4 -0.68
> 0.87
> PLA_12_02 61 195 2.67 1.11 2 2.62 1.48 1 5 4 0.41
> -0.61
> PLA_18_01 62 195 4.01 0.85 4 4.09 1.48 1 5 4 -0.82
> 0.78
> PR_06_02 63 195 3.02 1.27 3 3.02 1.48 1 5 4 -0.01
> -1.13
> PR_15_03 64 195 3.55 1.07 4 3.62 1.48 1 5 4 -0.46
> -0.22
> PR_25_01 65 195 2.36 1.04 2 2.27 1.48 1 5 4 0.73
> 0.06
> PR_25_06 66 195 2.95 1.17 3 2.94 1.48 1 5 4 0.04
> -0.86
> REL_09_05 67 195 3.81 0.95 4 3.89 1.48 1 5 4 -0.51
> -0.31
> REL_14_03 68 195 3.99 0.88 4 4.08 1.48 1 5 4 -0.75
> 0.39
> REL_14_06 69 195 2.93 1.26 3 2.92 1.48 1 5 4 0.06
> -1.11
> REL_16_04 70 195 3.16 1.27 3 3.20 1.48 1 5 4 -0.13
> -1.11
> RS_02_03 71 195 4.14 0.75 4 4.22 0.00 1 5 4 -0.82
> 1.14
> RS_07_05 72 195 4.29 0.67 4 4.38 0.00 2 5 3 -0.72
> 0.59
> RS_08_05 73 195 4.04 0.88 4 4.13 1.48 1 5 4 -0.97
> 1.26
> RS_13_03 74 195 4.19 0.69 4 4.25 0.00 2 5 3 -0.46
> -0.17
> TF_03_01 75 195 4.01 0.82 4 4.06 1.48 1 5 4 -0.63
> 0.32
> TF_04_01 76 195 4.09 0.76 4 4.15 0.00 1 5 4 -0.70
> 0.76
> TF_10_03 77 195 4.11 0.85 4 4.21 1.48 1 5 4 -0.96
> 0.99
> TF_12_01 78 195 4.11 0.85 4 4.21 1.48 1 5 4 -1.10
> 1.66
> TRE_09_05 79 195 4.29 0.79 4 4.39 1.48 1 5 4 -1.12
> 1.74
> TRE_09_06 80 195 4.33 0.69 4 4.42 1.48 1 5 4 -1.10
> 2.36
> TRE_26_04 81 195 2.97 1.20 3 2.96 1.48 1 5 4 0.08
> -1.01
> TRE_26_05 82 195 3.99 0.84 4 4.03 1.48 1 5 4 -0.41
> -0.37
>
> ```
>
> Until now, I have charged the libraries, import the my own database and did
> some simple descriptive statistics.
>
> ```
>
> > r9 <- my.data
> > omega(r9)
> Omega
> Call: omega(m = r9)
> Alpha: 0.95
> G.6: 0.98
> Omega Hierarchical: 0.85
> Omega H asymptotic: 0.89
> Omega Total 0.96
>
> Schmid Leiman Factor loadings greater than 0.2
> g F1* F2* F3* h2 u2 p2
> AUT_10_04 0.43 0.30 0.27 0.73 0.68
> AUN_07_01 0.05 0.95 0.53
> AUN_07_02 0.06 0.94 0.26
> AUN_09_01 0.38 0.30 0.24 0.76 0.59
> AUN_10_01 0.35 0.55 0.44 0.56 0.29
> AUT_11_01 0.42 0.30 0.27 0.73 0.66
> AUT_17_01 0.32 0.40 0.28 0.72 0.37
> AUT_20_03 0.41 0.25 0.24 0.76 0.73
> CRE_05_02- 0.24 -0.53 0.34 0.66 0.17
> CRE_07_04- 0.37 -0.51 0.39 0.61 0.35
> CRE_10_01 0.46 0.48 0.46 0.54 0.47
> CRE_16_02- -0.70 0.48 0.52 0.01
> EFEC_03_07 0.46 0.31 0.31 0.69 0.68
> EFEC_05 0.43 0.32 0.29 0.71 0.64
> EFEC_09_02- 0.29 -0.46 0.29 0.71 0.28
> EFEC_16_03 0.49 0.26 0.31 0.69 0.77
> EVA_02_01 0.55 0.21 0.36 0.64 0.85
> EVA_07_01 0.57 0.37 0.63 0.89
> EVA_12_02- -0.61 0.39 0.61 0.06
> EVA_15_06 0.50 0.37 0.39 0.61 0.65
> FLX_04_01 0.57 0.30 0.42 0.58 0.78
> FLX_04_05 0.52 0.26 0.34 0.66 0.80
> FLX_08_02- -0.78 0.60 0.40 0.00
> FLX_10_03 0.39 0.29 0.24 0.76 0.63
> IDO_01_06- -0.80 0.64 0.36 0.00
> IDO_05_02- -0.78 0.62 0.38 0.00
> IDO_09_03 0.41 0.49 0.42 0.58 0.40
> IDO_17_01 0.51 0.51 0.54 0.46 0.49
> IE_01_03 0.44 0.60 0.56 0.44 0.35
> IE_10_03 0.41 0.53 0.44 0.56 0.37
> IE_13_03 0.39 0.48 0.38 0.62 0.40
> IE_15_01 0.39 0.40 0.31 0.69 0.49
> LC_07_03 0.50 0.27 0.73 0.91
> LC_08_02 0.83 0.69 0.31 0.00
> LC_11_03 0.25 0.10 0.90 0.60
> LC_11_05 0.45 0.24 0.27 0.73 0.75
> ME_02_03 0.55 0.31 0.69 0.99
> ME_07_06 0.85 0.75 0.25 0.02
> ME_09_01 0.64 0.45 0.55 0.93
> ME_09_06 0.81 0.69 0.31 0.02
> NEG_01_03 0.58 0.20 0.38 0.62 0.88
> NEG_05_04 0.70 0.50 0.50 0.98
> NEG_07_03 0.64 0.43 0.57 0.96
> NEG_08_01 0.43 0.25 0.25 0.75 0.74
> OP_03_05 0.62 0.40 0.60 0.98
> OP_12_01 0.67 0.46 0.54 0.98
> OP_14_01 0.60 0.38 0.62 0.95
> OP_14_02 0.66 0.47 0.53 0.93
> ORL_01_03 0.67 0.47 0.53 0.96
> ORL_03_01 0.66 0.48 0.52 0.91
> ORL_03_05 0.64 0.46 0.54 0.90
> ORL_10_05 0.66 0.49 0.51 0.89
> PER_08_02 0.21 0.84 0.75 0.25 0.06
> PER_16_01 0.68 0.21 0.50 0.50 0.91
> PER_19_06 0.20 0.73 0.58 0.42 0.07
> PER_22_06 0.53 0.30 0.70 0.94
> PLA_01_03 0.57 0.36 0.64 0.89
> PLA_05_01 0.61 0.42 0.58 0.89
> PLA_07_02 0.75 0.61 0.39 0.04
> PLA_10_01 0.56 0.36 0.64 0.88
> PLA_12_02 0.61 0.37 0.63 0.00
> PLA_18_01 0.63 0.47 0.53 0.85
> PR_06_02 0.77 0.62 0.38 0.03
> PR_15_03 0.31 -0.39 0.24 0.31 0.69 0.31
> PR_25_01- -0.56 0.32 0.68 0.00
> PR_25_06 0.74 0.55 0.45 0.01
> REL_09_05 0.41 -0.23 0.38 0.37 0.63 0.45
> REL_14_03 0.41 -0.21 0.29 0.30 0.70 0.56
> REL_14_06 0.66 0.21 0.48 0.52 0.04
> REL_16_04 0.78 0.63 0.37 0.03
> RS_02_03 0.57 0.36 0.64 0.90
> RS_07_05 0.68 0.47 0.53 0.99
> RS_08_05 0.44 0.20 0.80 0.95
> RS_13_03 0.67 0.46 0.54 0.97
> TF_03_01 0.66 0.44 0.56 0.98
> TF_04_01 0.74 0.56 0.44 0.98
> TF_10_03 0.70 0.50 0.50 0.98
> TF_12_01 0.61 0.40 0.60 0.92
> TRE_09_05 0.70 0.23 0.55 0.45 0.89
> TRE_09_06 0.62 0.41 0.59 0.93
> TRE_26_04- -0.68 0.47 0.53 0.00
> TRE_26_05 0.55 -0.21 0.34 0.66 0.88
>
> With eigenvalues of:
> g F1* F2* F3*
> 18.06 0.04 11.47 4.32
>
> general/max 1.57 max/min = 267.1
> mean percent general = 0.58 with sd = 0.36 and cv of 0.63
> Explained Common Variance of the general factor = 0.53
>
> The degrees of freedom are 3078 and the fit is 34.62
> The number of observations was 195 with Chi Square = 5671.12 with prob
> < 2.8e-157
> The root mean square of the residuals is 0.06
> The df corrected root mean square of the residuals is 0.06
> RMSEA index = 0.078 and the 10 % confidence intervals are 0.063 NA
> BIC = -10559.18
>
> Compare this with the adequacy of just a general factor and no group
> factors
> The degrees of freedom for just the general factor are 3239 and the fit is
> 51.52
> The number of observations was 195 with Chi Square = 8509.84 with prob
> < 0
> The root mean square of the residuals is 0.16
> The df corrected root mean square of the residuals is 0.16
>
> RMSEA index = 0.104 and the 10 % confidence intervals are 0.089 NA
> BIC = -8569.4
>
> Measures of factor score adequacy
> g F1* F2* F3*
> Correlation of scores with factors 0.98 0.07 0.98 0.91
> Multiple R square of scores with factors 0.95 0.00 0.97 0.83
> Minimum correlation of factor score estimates 0.91 -0.99 0.94 0.66
>
> Total, General and Subset omega for each subset
> g F1* F2* F3*
> Omega total for total scores and subscales 0.96 NA 0.83 0.95
> Omega general for total scores and subscales 0.85 NA 0.82 0.76
> Omega group for total scores and subscales 0.09 NA 0.01 0.19
> ```
>
> Now, until here, I apply the basic (non hierarchical) omega() function to
> my own database
>
>
> ```
> > omegaSem(r9,n.obs=198)
> Error in parse(text = x, keep.source = FALSE) :
> <text>:2:0: unexpected end of input
> 1: ~
> ```
> The previous is the error message that appears after trying to use the
> omegaSem() function directly with my own database.
>
> Now, following, I present the expected output of omegaSem() applied
> directly using the Thurstone database. It's similar to the output of the
> basic omega() function but it has certain distinctions:
>
> ```
>
> > r9 <- Thurstone
> > omegaSem(r9,n.obs=500)
>
> Call: omegaSem(m = r9, n.obs = 500)
> Omega
> Call: omega(m = m, nfactors = nfactors, fm = fm, key = key, flip = flip,
> digits = digits, title = title, sl = sl, labels = labels,
> plot = plot, n.obs = n.obs, rotate = rotate, Phi = Phi, option =
> option)
> Alpha: 0.89
> G.6: 0.91
> Omega Hierarchical: 0.74
> Omega H asymptotic: 0.79
> Omega Total 0.93
>
> Schmid Leiman Factor loadings greater than 0.2
> g F1* F2* F3* h2 u2 p2
> Sentences 0.71 0.56 0.82 0.18 0.61
> Vocabulary 0.73 0.55 0.84 0.16 0.63
> Sent.Completion 0.68 0.52 0.74 0.26 0.63
> First.Letters 0.65 0.56 0.73 0.27 0.57
> Four.Letter.Words 0.62 0.49 0.63 0.37 0.61
> Suffixes 0.56 0.41 0.50 0.50 0.63
> Letter.Series 0.59 0.62 0.73 0.27 0.48
> Pedigrees 0.58 0.24 0.34 0.51 0.49 0.66
> Letter.Group 0.54 0.46 0.52 0.48 0.56
>
> With eigenvalues of:
> g F1* F2* F3*
> 3.58 0.96 0.74 0.72
>
> general/max 3.73 max/min = 1.34
> mean percent general = 0.6 with sd = 0.05 and cv of 0.09
> Explained Common Variance of the general factor = 0.6
>
> The degrees of freedom are 12 and the fit is 0.01
> The number of observations was 500 with Chi Square = 7.12 with prob <
> 0.85
> The root mean square of the residuals is 0.01
> The df corrected root mean square of the residuals is 0.01
> RMSEA index = 0 and the 10 % confidence intervals are 0 0.026
> BIC = -67.45
>
> Compare this with the adequacy of just a general factor and no group
> factors
> The degrees of freedom for just the general factor are 27 and the fit is
> 1.48
> The number of observations was 500 with Chi Square = 730.93 with prob <
> 1.3e-136
> The root mean square of the residuals is 0.14
> The df corrected root mean square of the residuals is 0.16
>
> RMSEA index = 0.23 and the 10 % confidence intervals are 0.214 0.243
> BIC = 563.14
>
> Measures of factor score adequacy
> g F1* F2* F3*
> Correlation of scores with factors 0.86 0.73 0.72 0.75
> Multiple R square of scores with factors 0.74 0.54 0.51 0.57
> Minimum correlation of factor score estimates 0.49 0.07 0.03 0.13
>
> Total, General and Subset omega for each subset
> g F1* F2* F3*
> Omega total for total scores and subscales 0.93 0.92 0.83 0.79
> Omega general for total scores and subscales 0.74 0.58 0.50 0.47
> Omega group for total scores and subscales 0.16 0.34 0.32 0.32
>
> The following analyses were done using the lavaan package
>
> Omega Hierarchical from a confirmatory model using sem = 0.79
> Omega Total from a confirmatory model using sem = 0.93
> With loadings of
> g F1* F2* F3* h2 u2 p2
> Sentences 0.77 0.49 0.83 0.17 0.71
> Vocabulary 0.79 0.45 0.83 0.17 0.75
> Sent.Completion 0.75 0.40 0.73 0.27 0.77
> First.Letters 0.61 0.61 0.75 0.25 0.50
> Four.Letter.Words 0.60 0.51 0.61 0.39 0.59
> Suffixes 0.57 0.39 0.48 0.52 0.68
> Letter.Series 0.57 0.73 0.85 0.15 0.38
> Pedigrees 0.66 0.25 0.50 0.50 0.87
> Letter.Group 0.53 0.41 0.45 0.55 0.62
>
> With eigenvalues of:
> g F1* F2* F3*
> 3.87 0.60 0.79 0.76
>
> The degrees of freedom of the confimatory model are 18 and the fit is
> 57.11391 with p = 5.936744e-06
> general/max 4.92 max/min = 1.3
> mean percent general = 0.65 with sd = 0.15 and cv of 0.23
> Explained Common Variance of the general factor = 0.64
>
> Measures of factor score adequacy
> g F1* F2* F3*
> Correlation of scores with factors 0.90 0.68 0.80 0.85
> Multiple R square of scores with factors 0.81 0.46 0.64 0.73
> Minimum correlation of factor score estimates 0.62 -0.08 0.27 0.45
>
> Total, General and Subset omega for each subset
> g F1* F2* F3*
> Omega total for total scores and subscales 0.93 0.92 0.82 0.80
> Omega general for total scores and subscales 0.79 0.69 0.48 0.50
> Omega group for total scores and subscales 0.14 0.23 0.35 0.31
>
> To get the standard sem fit statistics, ask for summary on the fitted
> object>
> ```
>
>
>
> I'm expecting to have the same output applying the function directly. My
> expectation is to make sure if its mandatory to make the schmid
> transformation before the omegaSem(). I'm supposing that not, because its
> not supposed to work like that as it says in the guide. Maybe this can be
> solved correcting the error message:
>
> ```
> > r9 <- my.data
> > omegaSem(r9,n.obs=198)
> Error in parse(text = x, keep.source = FALSE) :
> <text>:2:0: unexpected end of input
> 1: ~
> ^
> ```
> Hope I've been clear enough. Feel free to ask any other information that
> you might need.
>
> Thank you so much for giving me any guidance to reach the answer of this
> issue. I higly appreciate any help.
>
> Regards,
>
> Danilo
>
> --
> Danilo E. RodrÃguez Zapata
> Analista en PsicometrÃa
> CEBIAC
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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