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From |
John Antonakis <John.Antonakis@unil.ch> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Tue, 15 Jan 2013 22:04:35 +0100 |

Glad it works.

Best, J. __________________________________________ Prof. John Antonakis Faculty of Business and Economics Department of Organizational Behavior University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 http://www.hec.unil.ch/people/jantonakis Associate Editor The Leadership Quarterly __________________________________________ On 15.01.2013 21:11, Johannes Kotte wrote:

Hi John,magnificent, this helps a lot! I already tried setting the constraint@1 and to use the reliability-option but never used the two together.However, two questions remain:(i) Previous answers said that I could simply include the observedvariables instead of using latent covariates. Which approach would bemore appropriate? (any literature on that?)(ii) Lets's assume that "(x16 <- CV1@1)" defines CV1 as the latentvariable for gender (x16). Why would I set the reliability to anythingbelow 1.0, if x16 is perfectly reliable (which is a reasonableassumption, I guess)?Best JohannesFor those who are interested in this thread, my model now looks likethe following: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@1) /// (x17 <- CV2@1) /// (x18 <- CV3@1) /// (x19 <- CV4@1) /// (BKA PRAXREL <- KVSENIOR KVL CV1 CV2 CV3 CV4) /// (PRAXREL <- BKA) /// , standardized method(mlmv) reliability (x16 0.8 x17 0.8 x18 0.8 x19 0.8) Zitat von John Antonakis <John.Antonakis@unil.ch>:Hi:The model is undefined. You need to set constraints linking thesingle indicator (e.g,. x1) of the latent (X), as follows:sem (y <- X) (X ->x1@1), reliability(x1 .80)Where reliability < 1 > 0, is your theoretical constraint of how muchtrue variance x1 captures.See "help sem reliability"If course, if you set x1 = 1 you are assuming that x1 is perfectindicator of X.HTH, J. __________________________________________ Prof. John Antonakis Faculty of Business and Economics Department of Organizational Behavior University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 http://www.hec.unil.ch/people/jantonakis Associate Editor The Leadership Quarterly __________________________________________ On 15.01.2013 15:21, Johannes Kotte wrote:Dear fellow researchers,I would be grateful for advice with the following problem: I havecreated a very simple SEM (let's call it 'model 1') that works fine(see below for code). It contains a latent dependent variable calledPRAXREL and a latent independent variable called BKA. Moreover, itcontains latent control variables called KVSENIOR and KVL. As Isaid, model 1 works fine (identified, good fit).However, the model becomes problematic when I introduce single-itemlatent 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 settingthe reliability of the CV to 0.9 or 0.5) but none of them reallyworked unless I delete at least some of the CVs.The following might be interesting: (i) If I let Stata iterate 15times and take a look at the output, I find that sometimes thestandard errors of CV1, CV2, CV3 and CV4 are extremely high. (ii)Moreover, I found that pairwise correlation of the variables showsthat 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)* * 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:*John Antonakis <John.Antonakis@unil.ch>

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

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