Thank you so much, I'll wait until then. The good thing is that we can make
sure now what is the actual problem. I wish you have a good rest.
El jue., 29 ago. 2019 a las 14:55, William R Revelle (<
reve...@northwestern.edu>) escribió:
> Hi all.
>
> I am taking a brief vacation and will look at this next week.
>
> Bill
>
>
> > On Aug 29, 2019, at 2:53 PM, William Dunlap <wdun...@tibco.com> wrote:
> >
> > Element #2 of that output, the empty fomula " F1=~ ", triggers the bug
> in omegaSem.
> > omegaSem needs to ignore such entries in omega's output. psych's author
> should be able to fix things up.
> >
> > Bill Dunlap
> > TIBCO Software
> > wdunlap tibco.com
> >
> >
> > On Thu, Aug 29, 2019 at 12:31 PM Danilo Esteban Rodriguez Zapata <
> danilo_rodrig...@cun.edu.co> wrote:
> > well the output with the code that you refer is the following:
> >
> > > psych::omega(my.data)$model$lavaan
> > [1] g =~
> +AUT_10_04+AUN_07_01+AUN_07_02+AUN_09_01+AUN_10_01+AUT_11_01+AUT_17_01+AUT_20_03+CRE_05_02+CRE_07_04+CRE_10_01+CRE_16_02+EFEC_03_07+EFEC_05+EFEC_09_02+EFEC_16_03+EVA_02_01+EVA_07_01+EVA_12_02+EVA_15_06+FLX_04_01+FLX_04_05+FLX_08_02+FLX_10_03+IDO_01_06+IDO_05_02+IDO_09_03+IDO_17_01+IE_01_03+IE_10_03+IE_13_03+IE_15_01+LC_07_03+LC_08_02+LC_11_03+LC_11_05+ME_02_03+ME_07_06+ME_09_01+ME_09_06+NEG_01_03+NEG_05_04+NEG_07_03+NEG_08_01+OP_03_05+OP_12_01+OP_14_01+OP_14_02+ORL_01_03+ORL_03_01+ORL_03_05+ORL_10_05+PER_08_02+PER_16_01+PER_19_06+PER_22_06+PLA_01_03+PLA_05_01+PLA_07_02+PLA_10_01+PLA_12_02+PLA_18_01+PR_06_02+PR_15_03+PR_25_01+PR_25_06+REL_09_05+REL_14_03+REL_14_06+REL_16_04+RS_02_03+RS_07_05+RS_08_05+RS_13_03+TF_03_01+TF_04_01+TF_10_03+TF_12_01+TRE_09_05+TRE_09_06+TRE_26_04+TRE_26_05
> > [2] F1=~
>
>
>
>
>
>
>
>
>
>
> > [3] F2=~ + AUN_07_02 + CRE_05_02 + CRE_07_04 + CRE_16_02 + EFEC_09_02 +
> EVA_12_02 + FLX_08_02 + IDO_01_06 + IDO_05_02 + LC_08_02 + LC_11_03 +
> LC_11_05 + ME_02_03 + ME_07_06 + ME_09_06 + NEG_07_03 + OP_03_05 + OP_14_01
> + OP_14_02 + ORL_01_03 + ORL_03_01 + PER_08_02 + PER_19_06 + PLA_05_01 +
> PLA_07_02 + PLA_10_01 + PLA_12_02 + PLA_18_01 + PR_06_02 + PR_15_03 +
> PR_25_01 + PR_25_06 + REL_14_06 + REL_16_04 + TF_04_01 + TF_10_03 +
> TRE_26_04 + TRE_26_05
>
>
>
>
> > [4] F3=~ + AUT_10_04 + AUN_07_01 + AUN_09_01 + AUN_10_01 + AUT_11_01 +
> AUT_17_01 + AUT_20_03 + CRE_10_01 + EFEC_03_07 + EFEC_05 + EFEC_16_03 +
> EVA_02_01 + EVA_07_01 + EVA_15_06 + FLX_04_01 + FLX_04_05 + FLX_10_03 +
> IDO_09_03 + IDO_17_01 + IE_01_03 + IE_10_03 + IE_13_03 + IE_15_01 +
> LC_07_03 + ME_09_01 + NEG_01_03 + NEG_05_04 + NEG_08_01 + OP_12_01 +
> ORL_03_05 + ORL_10_05 + PER_16_01 + PER_22_06 + PLA_01_03 + REL_09_05 +
> REL_14_03 + RS_02_03 + RS_07_05 + RS_08_05 + RS_13_03 + TF_03_01 + TF_12_01
> + TRE_09_05 + TRE_09_06
>
>
>
> > >
> >
> > El jue., 29 ago. 2019 a las 14:29, Danilo Esteban Rodriguez Zapata (<
> danilo_rodrig...@cun.edu.co>) escribió:
> > Dear William,
> >
> > Thank you for your answer, I would like to add some information that I
> just obtained looking in different sites and forums. Someone there ask me
> to create a fake data file, so I did that from my original data file. What
> I did was open the .csv file with notepad and replace all the 4 for 5 and
> the 2 for 1, then I saved the file again with no other changes. I also
> searched for the "~" in the file and I found nothing. Now with that file I
> did the omegaSem() function and it worked succesfully, so the weird thing
> here is that the omegaSem() function works with the fake data file, wich is
> exactly the same as the original file, but recoding some answers as I said.
> >
> > It seems to be an issue with the file. When I replace, lets say, the 5
> for 6 and make the omegaSem() again, it works. Then I replace back again
> the 6 for 5 in all the data and the function doesn't works anymore.
> >
> >
> > El jue., 29 ago. 2019 a las 12:33, William Dunlap (<wdun...@tibco.com>)
> escribió:
> > > 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. Rodríguez Zapata
> > Analista en Psicometría
> > CEBIAC
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> >
> > --
> > Danilo E. Rodríguez Zapata
> > Analista en Psicometría
> > CEBIAC
> >
> >
> > --
> > Danilo E. Rodríguez Zapata
> > Analista en Psicometría
> > CEBIAC
>
> William Revelle personality-project.org/revelle.html
> Professor personality-project.org
> Department of Psychology www.wcas.northwestern.edu/psych/
> Northwestern University www.northwestern.edu/
> Use R for psychology personality-project.org/r
> It is 2 minutes to midnight www.thebulletin.org
>
>
>
>
>
>
>
>
--
Danilo E. Rodríguez Zapata
Analista en Psicometría
CEBIAC
[[alternative HTML version deleted]]
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