Hi - I would need help another time. I would the model and wire the correlation matrix into the sem() method. I got the system is exactly singular? Is my model underidentified? Here I have my model below along with the result from traceback() funciton. Any help would be really appreciated. Thank you again!

    Average_Daily_Traffic -> Lat_Env,                     gam1_1,           NA
    Average_Daily_Truck_Traffic -> Lat_Env,               gam1_2,           NA
    BridgeAges -> Lat_Env,                                gam1_3,           NA
    
    Design_Load -> Lat_Specs,                             gam2_1,           NA
    Type_of_Service_On_Bridge -> Lat_Specs,               gam2_2,           NA
    Railroad_Beneath -> Lat_Specs,                        gam2_3,           NA
    BridgeAges -> Lat_Specs,                              gam2_4,           NA
    Highway_Beneath -> Lat_Specs,                         gam2_5,           NA
    
    Main_Structure_Material -> Lat_Design,                gam3_1,           NA
    Main_Structure_Design -> Lat_Design,                  gam3_2,           NA
    Length_of_Maximum_Span -> Lat_Design,                 gam3_4,           NA
    Number_of_Spans_In_Main_Unit -> Lat_Design,           gam3_5,           NA
    BridgeAges -> Lat_Design,                             gam3_6,           NA
    
    Lat_Env -> Lat_Specs,                                 beta2_1,          NA
    Lat_Env -> Lat_Design,                                beta3_1,          NA
    Lat_Specs -> Lat_Env,                                 beta1_2,          NA
    Lat_Specs -> Lat_Design,                              beta3_2,          NA
    Lat_Design -> Lat_Env,                                beta1_3,          NA
    Lat_Design -> Lat_Specs,                              beta1_2,          NA
    
    Lat_Env -> Operating_Rating,                          NA,               1
    Lat_Env -> Deck_Cond_Rating,                          lamy2_1,          NA
    Lat_Env -> Superstructure_Cond_Rating,                lamy3_1,          NA
    Lat_Env -> Substructure_Cond_Rating,                  lamy4_1,          NA
    Lat_Specs -> Operating_Rating,                        NA,               1
    Lat_Specs -> Deck_Cond_Rating,                        lamy2_2,          NA
    Lat_Specs -> Superstructure_Cond_Rating,              lamy3_2,          NA
    Lat_Specs -> Substructure_Cond_Rating,                lamy4_2,          NA
    Lat_Design -> Operating_Rating,                       NA,               1
    Lat_Design -> Deck_Cond_Rating,                       lamy2_3,          NA
    Lat_Design -> Superstructure_Cond_Rating,             lamy3_3,          NA
    Lat_Design -> Substructure_Cond_Rating,               lamy4_3,          NA
    
    Lat_Env <-> Lat_Specs,                                psi2_1,           NA
    Lat_Env <-> Lat_Design,                               psi3_1,           NA
    Lat_Specs <-> Lat_Design,                             psi3_2,           NA
    Lat_Env <-> Lat_Env,                                  psi1_1,           NA
    Lat_Specs <-> Lat_Specs,                              psi2_2,           NA
    Lat_Design <-> Lat_Design,                            psi3_3,           NA
    
    Operating_Rating <-> Operating_Rating,                thesp1,           NA
    Deck_Cond_Rating <-> Deck_Cond_Rating,                thesp2,           NA
    Superstructure_Cond_Rating <-> Superstructure_Cond_Rating,  thesp3,     NA
    Substructure_Cond_Rating <-> Substructure_Cond_Rating, thesp4,           NA
    
    Average_Daily_Traffic <-> Average_Daily_Traffic,      theps5,           NA
    Average_Daily_Truck_Traffic <-> Average_Daily_Truck_Traffic, thesp6,    NA
    Design_Load <-> Design_Load,                          thesp7,           NA
    Type_of_Service_On_Bridge <-> Type_of_Service_On_Bridge, thesp8,        NA
    Railroad_Beneath <-> Railroad_Beneath,                thesp9,           NA
    Highway_Beneath <-> Highway_Beneath,                  thesp10,           NA
    Main_Structure_Material <-> Main_Structure_Material,  thesp11,           NA
    Main_Structure_Design <-> Main_Structure_Design,      thesp12,           NA
    Number_of_Spans_In_Main_Unit <-> Number_of_Spans_In_Main_Unit, thesp13,  NA
    BridgeAges <-> BridgeAges,                            thesp14,          NA
    Length_of_Maximum_Span <-> Length_of_Maximum_Span,    thesp15,          NA

===================================
Result from traceback():

 observed variables:
 [1] "1:Type_of_Service_On_Bridge"     "2:BridgeAges"                   
 [3] "3:Average_Daily_Traffic"         "4:Average_Daily_Truck_Traffic"  
 [5] "5:Design_Load"                   "6:Railroad_Beneath"             
 [7] "7:Highway_Beneath"               "8:Main_Structure_Material"      
 [9] "9:Main_Structure_Design"         "10:Length_of_Maximum_Span"      
[11] "11:Number_of_Spans_In_Main_Unit" "12:Operating_Rating"            
[13] "13:Deck_Cond_Rating"             "14:Superstructure_Cond_Rating"  
[15] "15:Substructure_Cond_Rating"    

 latent variables:
[1] "16:Lat_Env"    "17:Lat_Specs"  "18:Lat_Design"

 parameters:
 [1] "1:gam1_1"   "2:gam1_2"   "3:gam1_3"   "4:gam2_1"   "5:gam2_2"  
 [6] "6:gam2_3"   "7:gam2_4"   "8:gam2_5"   "9:gam3_1"   "10:gam3_2" 
[11] "11:gam3_4"  "12:gam3_5"  "13:gam3_6"  "14:beta2_1" "15:beta3_1"
[16] "16:beta1_2" "17:beta3_2" "18:beta1_3" "19:lamy2_1" "20:lamy3_1"
[21] "21:lamy4_1" "22:lamy2_2" "23:lamy3_2" "24:lamy4_2" "25:lamy2_3"
[26] "26:lamy3_3" "27:lamy4_3" "28:psi2_1"  "29:psi3_1"  "30:psi3_2" 
[31] "31:psi1_1"  "32:psi2_2"  "33:psi3_3"  "34:thesp1"  "35:thesp2" 
[36] "36:thesp3"  "37:thesp4"  "38:theps5"  "39:thesp6"  "40:thesp7" 
[41] "41:thesp8"  "42:thesp9"  "43:thesp10" "44:thesp11" "45:thesp12"
[46] "46:thesp13" "47:thesp14" "48:thesp15"

 RAM:
      heads to from parameter start
 [1,]     1 16    3         1    NA
 [2,]     1 16    4         2    NA
 [3,]     1 16    2         3    NA
 [4,]     1 17    5         4    NA
 [5,]     1 17    1         5    NA
 [6,]     1 17    6         6    NA
 [7,]     1 17    2         7    NA
 [8,]     1 17    7         8    NA
 [9,]     1 18    8         9    NA
[10,]     1 18    9        10    NA
[11,]     1 18   10        11    NA
[12,]     1 18   11        12    NA
[13,]     1 18    2        13    NA
[14,]     1 17   16        14    NA
[15,]     1 18   16        15    NA
[16,]     1 16   17        16    NA
[17,]     1 18   17        17    NA
[18,]     1 16   18        18    NA
[19,]     1 17   18        16    NA
[20,]     1 12   16         0     1
[21,]     1 13   16        19    NA
[22,]     1 14   16        20    NA
[23,]     1 15   16        21    NA
[24,]     1 12   17         0     1
[25,]     1 13   17        22    NA
[26,]     1 14   17        23    NA
[27,]     1 15   17        24    NA
[28,]     1 12   18         0     1
[29,]     1 13   18        25    NA
[30,]     1 14   18        26    NA
[31,]     1 15   18        27    NA
[32,]     2 17   16        28    NA
[33,]     2 18   16        29    NA
[34,]     2 18   17        30    NA
[35,]     2 16   16        31    NA
[36,]     2 17   17        32    NA
[37,]     2 18   18        33    NA
[38,]     2 12   12        34    NA
[39,]     2 13   13        35    NA
[40,]     2 14   14        36    NA
[41,]     2 15   15        37    NA
[42,]     2  3    3        38    NA
[43,]     2  4    4        39    NA
[44,]     2  5    5        40    NA
[45,]     2  1    1        41    NA
[46,]     2  6    6        42    NA
[47,]     2  7    7        43    NA
[48,]     2  8    8        44    NA
[49,]     2  9    9        45    NA
[50,]     2 11   11        46    NA
[51,]     2  2    2        47    NA
[52,]     2 10   10        48    NA
Error in solve.default(C[ind, ind]) : Lapack routine dgesv: system is exactly singular


 

----- Original Message -----
From: adschai@optonline.net
Date: Sunday, April 15, 2007 1:19 pm
Subject: Re: [R] Fit sem model with intercept
To: r-help@stat.math.ethz.ch

> Thank you John. I got it now. 
> Regarding the model I specified below, I totally agree with you. 
> I listed only portions of my model the illustrate the point of 
> my questions. Therefore, I showed only the arrow part. No 
> correlations are listed here. However, I have those in my 
> complete model.
> Thank you so much for your help. It was really helpful.
> 
> - adschai
> 
> ----- Original Message -----
> From: John Fox 
> Date: Sunday, April 15, 2007 8:31 am
> Subject: RE: [R] Fit sem model with intercept
> To: adschai@optonline.net
> Cc: r-help@stat.math.ethz.ch
> 
> > Dear adschai,
> > 
> > You needn't look too far, since the last example in ?sem is 
> for 
> > a model with
> > an intercept. One would use the raw-moment matrix as input to 
> > sem(), either
> > entered directly or calculated with the raw.moments() function 
> > in the sem
> > package. The row/column of the raw-moment matrix is given a 
> name 
> > just like
> > the other columns. You could use the name "1"; in the example, 
> > the name is
> > "UNIT".
> > 
> > As you say, however, you're using polychoric and polyserial 
> > correlations as
> > input. Since the origin and scale of the latent continuous variables
> > underlying the ordinal variables are entirely arbitrary, I 
> can't 
> > imaginewhat the purpose of a model with an intercept would be, 
> > but it's possible
> > that I'm missing something. If you think that this makes some 
> > sense, then
> > you could convert the correlations to raw moments by using the 
> > means and
> > standard deviations of the observed variables along with the 
> > means and
> > standard deviations that you assign to the latent variables 
> > derived from the
> > ordinal variables (the latter on what basis I can't imagine, 
> but 
> > I suppose
> > you could fix them to 0s and 1s).
> > 
> > Finally, if the sem model that you show is meant to be a complete
> > specification, I notice that it includes no covariance 
> > components; moreover,
> > if this is the complete structural part of the model, then I 
> > think it is
> > underidentified, and the two parts of the model (those 
> involving 
> > eta1 and
> > eta2) appear entirely separate.
> > 
> > I hope this helps,
> > John
> > 
> > --------------------------------
> > John Fox
> > Department of Sociology
> > McMaster University
> > Hamilton, Ontario
> > Canada L8S 4M4
> > 905-525-9140x23604
> > http://socserv.mcmaster.ca/jfox 
> > -------------------------------- 
> > 
> > > -----Original Message-----
> > > From: r-help-bounces@stat.math.ethz.ch 
> > > [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of 
> > > adschai@optonline.net
> > > Sent: Sunday, April 15, 2007 4:28 AM
> > > To: r-help@stat.math.ethz.ch
> > > Subject: [R] Fit sem model with intercept
> > > 
> > > Hi - I am trying to fit sem model with intercepts. Here is 
> > > what I have in my model.
> > > 
> > > Exogeneous vars: x1 (continous), x2 (ordinal), x3 (ordinal), 
> > > x4(continuous) Endogeneous vars: y1 (continuous), y2 
> > > (ordinal), y3 (ordinal)
> > > 
> > > SEM model:
> > > x1 -> eta1; x2 -> eta1; x3 -> eta2; x4 -> eta2; eta1 -> 
> > > y1, eta1 -> y2, eta2 -> y2, eta2 -> y3 
> > > 
> > > However, in these arrow models, I don't know how to add 
> > > intercept onto it. I am trying to find an example code using 
> > > sem package on how to incorporate intercept but cannot find 
> > > any documents on the web. Or we can simply add something 
> like 
> > > this? '1 -> eta1'? This is my first question. 
> > > 
> > > Also, note that since my y2 and y3 are ordinal, I used the 
> > > 'hetcor' to calculate correlation of observed variables. 
> > > However, from the document, I would need to use the 
> > > covariance matrix rather then the correlation. And I need 
> > > additional column for 1. I am not sure how this matrix 
> should 
> > > look like and how I can obtain this? If there is any example 
> > > you could point me to, I would really appreciate. Thank you.
> > > 
> > > - adschai
> > > 
> > > [[alternative HTML version deleted]]
> > > 
> > > ______________________________________________
> > > R-help@stat.math.ethz.ch mailing list
> > > 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.
> > > 
> > 
> > 
> > 
> 
> [[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> 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.
> 

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