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st: SEM becomes unidentified when introducing single item control variables
From 
 
Johannes Kotte <[email protected]> 
To 
 
[email protected] 
Subject 
 
st: SEM becomes unidentified when introducing single item control variables 
Date 
 
Tue, 15 Jan 2013 15:21:36 +0100 
Dear fellow researchers,
I would be grateful for advice with the following problem: I have  
created a very simple SEM (let's call it 'model 1') that works fine  
(see below for code). It contains a latent dependent variable called  
PRAXREL and a latent independent variable called BKA. Moreover, it  
contains latent control variables called KVSENIOR and KVL. As I said,  
model 1 works fine (identified, good fit).
However, the model becomes problematic when I introduce single-item  
latent variables (CV1, CV2, CV3, CV4) as control variables ('model2').  
In this case Stata iterates forever saying ?not concave?.
WHAT COULD BE THE REASON? I tried many different setups of the model  
(incl. constraining the path coefficients of the CV to 1 or setting  
the reliability of the CV to 0.9 or 0.5) but none of them really  
worked unless I delete at least some of the CVs.
The following might be interesting: (i) If I let Stata iterate 15  
times and take a look at the output, I find that sometimes the  
standard errors of CV1, CV2, CV3 and CV4 are extremely high. (ii)  
Moreover, I found that pairwise correlation of the variables shows  
that they are mostly correlated - at least at the 10% level, sometimes  
even 1%. Might there be a collinearity problem?
Can anybody give me advice? I would greatly appreciate that!
Thanks in advance!
Johannes
CODE FOR BOTH MODELS:
/***MODEL 1***/
sem 	(y1 y2 y3 y4 		<- PRAXREL) 		///
	(x1 x2 x3 x4 x5 x6 x7 	<- BKA) 		///
	(x8 x9 x10 x11 		<- KVSENIOR)		///
	(x12 x13 x14 x15	<- KVL)			///
	(BKA PRAXREL 		<- KVSENIOR KVL) 	///
	(PRAXREL		<- BKA) 		///
	, standardized method(mlmv)
/***MODEL 2***/
sem 	(y1 y2 y3 y4 		<- PRAXREL) 	///
	(x1 x2 x3 x4 x5 x6 x7 	<- BKA) 	///
	(x8 x9 x10 x11 		<- KVSENIOR)	///
	(x12 x13 x14 x15	<- KVL)		///
	(x16			<- CV1)		///
	(x17			<- CV2)		///
	(x18			<- CV3)		///
	(x19			<- CV4)		///
	(BKA PRAXREL 	<- KVSENIOR KVL CV1 CV2 CV3 CV4) ///
	(PRAXREL		<- BKA) 	///
	, standardized method(mlmv)
--
Johannes Kotte
Otto-von-Guericke-Universität | Faculty of Business and Economics|  
Chair of Management and Organization (Prof. Thomas Spengler) |  
Postfach 4120, 39016 Magdeburg | www.ufo.ovgu.de
Telefon: +49-173-6371955  | E-Mail: [email protected]
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