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From |
William Buchanan <william@williambuchanan.net> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: SEM becomes unidentified when introducing single item control variables |

Date |
Tue, 15 Jan 2013 12:26:30 -0800 |

Johannes, You also need to consider the estimator that you are using and how the parameters are being estimated when working with dichotomous/categorical variables. There is a post in the Statalist archives where Stas Kolenikov explained the commonalities between the ADF estimator and the WLS estimator from Mplus. HTH, Billy Sent from my iPhone On Jan 15, 2013, at 12:17, Johannes Kotte <johannes.kotte@st.ovgu.de> wrote: > Hi Alan, > > thanks a lot for your explanation! You addressed exactly the two questions that remained after the last answer from John. > > And thanks for writing the book "A gentle introduction to Stata". It was a survival guide for me as a Stata Novice :-) > > Best > Johannes > > > > Zitat von Alan Acock <acock@me.com>: > >> Johannes, >> >> You could use >> .sem (x1<- X1), reliability(x1 .8) >> Then, you could try other estimates of reliability to do a sensitivity analysis. If you assume there is no measurement error, then you would simply use x1 as is and not use a latent variable for it. >> >> Alan Acock >> On Jan 15, 2013, at 10:45 AM, Johannes Kotte <johannes.kotte@st.ovgu.de> wrote: >> >>> Hi Billy, >>> >>> makes complete sense what you say about the covariates - thanks for your help! >>> >>> What I meant by "I have already seen models with latent single-item variables" is that some authors use single-item latent variables isntead of the observed ones (like I tried to). What I don't understand is how this can work, considering my experience that latent single-item variables cannot be identified. >>> >>> Best >>> Johannes >>> >>> >>> Zitat von William Buchanan <william@williambuchanan.net>: >>> >>>> Hi Johannes, >>>> >>>> I'm not sure why you would use several latent variables for observed >>>> covariates. If you wanted a measurement model for your covariates it would >>>> be something more like: >>>> >>>> (x16 x17 x18 x19 <- Covariates) >>>> >>>> But given what you've mentioned about the variables, it doesn't seem like >>>> this would be a good idea (e.g., suggesting that some unobservable variable >>>> affects someone's gender, age, and what I presume would be other demographic >>>> indicators). Why is it not acceptable to include your observed variables as >>>> covariates? If you're going to mention how you've seen this done before in >>>> other articles/papers it would also be a good idea to reference those papers >>>> so others can approach helping you from the same frame of reference. And >>>> you should include the output from your command(s) as well as the syntax >>>> that you've used to produce them. Sometimes you may have just overlooked a >>>> small, but important, piece of information that could explain a lot of the >>>> problems you're running into. >>>> >>>> HTH, >>>> Billy >>>> >>>> >>>> >>>> -----Original Message----- >>>> From: owner-statalist@hsphsun2.harvard.edu >>>> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Johannes Kotte >>>> Sent: Tuesday, January 15, 2013 8:50 AM >>>> To: statalist@hsphsun2.harvard.edu; JVerkuilen (Gmail) >>>> Subject: Re: st: SEM becomes unidentified when introducing single item >>>> control variables >>>> >>>> Thanks for your reply! >>>> >>>> I looked at the model identification after letting sem iterate for a few >>>> times. The df are above 60, so I always thought that identification is no >>>> issue. >>>> >>>> Now this might sound stupid, but I always thought that "(x16 <- CV1) ... >>>> (x19 <- CV4)" IS my measurement model for the control variables. >>>> However, you are right that CV1-CV4 are unidentified if I run the >>>> measurement models alone. As they are single-item variables like gender, >>>> age, etc., I (obviously wrongly) presumed that they cannot be unidentified. >>>> >>>> Nevertheless, they don't have to be latent (I guess), even though I have >>>> already seen models with latent single-item variables. So, if I altered >>>> model 2 as follows (with x16 x17 x18 x19 being the controls), would that be >>>> correct? >>>> >>>> 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 x16 x17 x18 x19) /// >>>> (PRAXREL <- BKA) /// >>>> , standardized method(mlmv) >>>> >>>> I tried the above sem and it works. However, the estat mindices command >>>> results in missing values only, even for the latent constructs >>>> >>>> Again, thanks a lot! >>>> Johannes >>>> >>>> --------------------------------------- Original e-mail >>>> --------------------------------------- >>>> >>>> Zitat von "JVerkuilen (Gmail)" <jvverkuilen@gmail.com>: >>>> >>>>> The standard errors being crazy is a sign that the model is not >>>>> identified. I'd suspect it's because the latent variables for these >>>>> controls aren't identified, and given that it doesn't sound like you >>>>> have a measurement model for them I'm not sure how they could be. Why >>>>> are they latent anyway? >>>>> * >>>>> * For searches and help try: >>>>> * http://www.stata.com/help.cgi?search >>>>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>>>> * http://www.ats.ucla.edu/stat/stata/ >>>> >>>> ---------------------------------------------------------------------- >>>> Datum: Tue, 15 Jan 2013 15:21:36 +0100 >>>> Von: Johannes Kotte <johannes.kotte@st.ovgu.de> >>>> Betreff: SEM becomes unidentified when introducing single item control >>>> variables >>>> An: statalist@hsphsun2.harvard.edu >>>> >>>> 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: johannes.kotte@st.ovgu.de >>>> >>>> >>>> * >>>> * For searches and help try: >>>> * http://www.stata.com/help.cgi?search >>>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>>> * http://www.ats.ucla.edu/stat/stata/ >>>> >>>> >>>> * >>>> * For searches and help try: >>>> * http://www.stata.com/help.cgi?search >>>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>>> * http://www.ats.ucla.edu/stat/stata/ >>> >>> >>> >>> -- >>> Johannes Kotte >>> Otto-von-Guericke-Universität | Fakultät Wirtschaftswissenschaften | Lehrstuhl für Unternehmensführung und Organisation (Prof. Dr. Thomas Spengler) | Postfach 4120, 39016 Magdeburg | www.ufo.ovgu.de >>> >>> Telefon: +49-173-6371955 | E-Mail: johannes.kotte@st.ovgu.de >>> >>> >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>> * http://www.ats.ucla.edu/stat/stata/ >> >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/faqs/resources/statalist-faq/ >> * http://www.ats.ucla.edu/stat/stata/ > > > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: SEM becomes unidentified when introducing single item control variables***From:*Johannes Kotte <johannes.kotte@st.ovgu.de>

**Re: st: SEM becomes unidentified when introducing single item control variables***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: SEM becomes unidentified when introducing single item control variables***From:*Johannes Kotte <johannes.kotte@st.ovgu.de>

**RE: st: SEM becomes unidentified when introducing single item control variables***From:*"William Buchanan" <william@williambuchanan.net>

**RE: st: SEM becomes unidentified when introducing single item control variables***From:*Johannes Kotte <johannes.kotte@st.ovgu.de>

**Re: st: SEM becomes unidentified when introducing single item control variables***From:*Alan Acock <acock@me.com>

**Re: st: SEM becomes unidentified when introducing single item control variables***From:*Johannes Kotte <johannes.kotte@st.ovgu.de>

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