[R] R code: How to correct "Error in parse(text = x, keep.source = FALSE)" output in psych package using own dataset

Danilo Esteban Rodriguez Zapata d@n||o_rodr|guez @end|ng |rom cun@edu@co
Thu Aug 29 21:31:05 CEST 2019


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_rodriguez using 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 (<wdunlap using 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 <revelle using 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 using 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 using 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

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