+-------+ ----+ Title +------------------------------------------------------------
lmnsem: Overall System Non Normality Tests after (SEM) Regressions
+--------+ ----+ Syntax +-----------------------------------------------------------
lmnsem
+-------------+ ----+ Description +------------------------------------------------------
lmnsem computes overall system Non Normality Tests, after: - (SEM) Structural Equation Modeling Regressions sem for system of simultaneous equations.
+---------------+ ----+ Saved Results +----------------------------------------------------
lmnsem saves the following in r():
Scalars
r(lmnjb_#) Jarque-Bera LM Test for eq.# r(lmnjbp_#) Jarque-Bera LM Test for eq.# P-Value
r(lmnjb) Jarque-Bera LM Test r(lmnjbp) Jarque-Bera LM Test P-Value r(lmndh) Doornik-Hansen LM Test r(lmndhp) Doornik-Hansen LM Test P-Value r(lmng) Geary LM Test r(lmngp) Geary LM Test P-Value r(lmnad) Anderson-Darling Z Test r(lmnadp) Anderson-Darling Z Test P-Value r(lmndp) D'Agostino-Pearson LM Test r(lmndpp) D'Agostino-Pearson LM Test P-Value r(lmnsvs) Srivastava LM Skewness Test r(lmnsvsp) Srivastava LM Skewness Test P-Value r(lmnsms1) Small LM Skewness Test r(lmnsms1p) Small LM Skewness Test P-Value r(lmnsms2) Skewness Z Test r(lmnsms2p) Skewness Z Test P-Value r(lmnsvk) Srivastava Z Kurtosis Test r(lmnsvkp) Srivastava Z Kurtosis Test P-Value r(lmnsmk1) Small LM Kurtosis Test r(lmnsmk1p) Small LM Kurtosis Test P-Value r(lmnsmk2) Kurtosis Z Test r(lmnsmk2p) Kurtosis Z Test P-Value r(sk) Skewness Coefficient r(sksd) Skewness Standard Deviation r(ku) Kurtosis Coefficient r(kusd) Kurtosis Standard Deviation r(sn) Standard Deviation Runs Sig(k) r(en) Mean Runs E(k) r(lower) Lower 95% Conf. Interval [E(k)- 1.96* Sig(k)] r(upper) Upper 95% Conf. Interval [E(k)+ 1.96* Sig(k)]
+------------+ ----+ References +-------------------------------------------------------
Anderson T.W., Darling D.A. (1954) "A Test of Goodness of Fit", Journal of the American Statisical Association, 49; 765–69.
C.M. Jarque & A.K. Bera (1987) "A Test for Normality of Observations and Regression Residuals" International Statistical Review , Vol. 55; 163-172.
D'Agostino, R. B., & Rosman, B. (1974) "The Power of Geary’s Test of Normality", Biometrika, 61(1); 181-184.
Damodar Gujarati (1995) "Basic Econometrics" 3rd Edition, McGraw Hill, New York, USA.
Geary R.C. (1947) "Testing for Normality" Biometrika, Vol. 34; 209-242.
Geary R.C. (1970) "Relative Efficiency of Count of Sign Changes for Assessing Residuals Autoregression in Least Squares Regression" Biometrika, Vol. 57; 123-127.
Pearson, E. S., D'Agostino, R. B., & Bowman, K. O. (1977) "Tests for Departure from Normality: Comparison of Powers", Biometrika, 64(2); 231-246.
+----------+ ----+ Examples +---------------------------------------------------------
in this example FIML will be used as follows:
clear all
sysuse lmnsem.dta , clear
sem (y1 <- y2 x1 x2) (y2 <- y1 x3 x4), cov(e.y1*e.y2)
lmnsem
return list
* If you want to use dialog box: Press OK to compute lmnsem
db lmnsem
. clear all . sysuse lmnsem.dta , clear . sem (y1 <- y2 x1 x2) (y2 <- y1 x3 x4), cov(e.y1*e.y2)
Structural equation model Number of obs = 17 Estimation method = ml Log likelihood = -363.34588 ------------------------------------------------------------------------------ | OIM | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Structural | y1 <- | y2 | .2425937 .2106232 1.15 0.249 -.1702201 .6554075 x1 | .2568409 .462485 0.56 0.579 -.649613 1.163295 x2 | -1.037016 .3154059 -3.29 0.001 -1.6552 -.4188317 _cons | 147.0826 54.4491 2.70 0.007 40.36431 253.8009 -----------+---------------------------------------------------------------- y2 <- | y1 | -.6282929 .6148239 -1.02 0.307 -1.833326 .5767398 x3 | -.5226661 .3235637 -1.62 0.106 -1.156839 .1115071 x4 | 3.4208 1.440664 2.37 0.018 .5971513 6.244449 _cons | 62.44495 42.36071 1.47 0.140 -20.58052 145.4704 -------------+---------------------------------------------------------------- Variance | e.y1 | 80.17577 28.99122 39.46865 162.8673 e.y2 | 142.4478 80.80501 46.86006 433.0208 -------------+---------------------------------------------------------------- Covariance | e.y1 | e.y2 | 25.62619 53.75243 0.48 0.634 -79.72665 130.979 ------------------------------------------------------------------------------ LR test of model vs. saturated: chi2(2) = 0.12, Prob > chi2 = 0.9408
. lmnsem
================================================= * System Non Normality Tests (ml) ================================================= *** Single Equation Non Normality Tests: Ho: Normality - Ha: Non Normality
Eq. 1 : Jarque-Bera LM Test = 2.6232 P-Value > Chi2(2) 0.2694 Eq. 2 : Jarque-Bera LM Test = 2.2936 P-Value > Chi2(2) 0.3177 ------------------------------------------------------------------------------
*** Overall System Non Normality Tests: Ho: No Overall System Non Normality
*** Non Normality Tests: - Jarque-Bera LM Test = 5.4681 P-Value > Chi2(2) 0.0650 - Doornik-Hansen LM Test = 4.9476 P-Value > Chi2(2) 0.0843 - Geary LM Test = 0.4365 P-Value > Chi2(2) 0.8039 - Anderson-Darling Z Test = -0.4223 P-Value>Z( 1.361) 0.9133 - D'Agostino-Pearson LM Test = 7.0244 P-Value > Chi2(2) 0.0298 ------------------------------------------------------------------------------ *** Skewness Tests: - Srivastava LM Skewness Test = 4.4358 P-Value > Chi2(1) 0.0352 - Small LM Skewness Test = 4.9358 P-Value > Chi2(1) 0.0263 - Skewness Z Test = -2.2217 P-Value > Chi2(1) 0.0263 ------------------------------------------------------------------------------ *** Kurtosis Tests: - Srivastava Z Kurtosis Test = 1.0160 P-Value > Z(0,1) 0.3096 - Small LM Kurtosis Test = 2.0887 P-Value > Chi2(1) 0.1484 - Kurtosis Z Test = 1.4452 P-Value > Chi2(1) 0.0742 ------------------------------------------------------------------------------ Skewness Coefficient = -0.8848 - Standard Deviation = 0.4031 Kurtosis Coefficient = 3.8536 - Standard Deviation = 0.7879 ------------------------------------------------------------------------------ Runs Test: (19) Runs - (19) Positives - (15) Negatives Standard Deviation Runs Sig(k) = 2.8300 , Mean Runs E(k) = 17.7647 95% Conf. Interval [E(k)+/- 1.96* Sig(k)] = (12.2179 , 23.3115 ) ------------------------------------------------------------------------------
+--------+ ----+ Author +-----------------------------------------------------------
Emad Abd Elmessih Shehata Assistant Professor Agricultural Research Center - Agricultural Economics Research Institute - Eg > ypt Email: emadstat@hotmail.com WebPage: http://emadstat.110mb.com/stata.htm WebPage at IDEAS: http://ideas.repec.org/f/psh494.html WebPage at EconPapers: http://econpapers.repec.org/RAS/psh494.htm
+-----------------+ ----+ lmnsem Citation +--------------------------------------------------
Shehata, Emad Abd Elmessih (2012) LMNSEM: "Stata Module to Compute Overall System Non Normality Tests after Structural Equation Modeling (SEM) Regressions"
Online Help:
lmasem, lmhsem, lmnsem, lmcovsem, r2sem, lmareg3, lmhreg3, lmnreg3, lmcovreg3, r2reg3. (if installed).