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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 19:45:06 +0100 |

Hi:

sem (y <- X) (X ->x1@1), reliability(x1 .80)

See "help sem reliability"

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 I said,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, sometimeseven 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)

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

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

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