
Message/Author 

Mahima Hada posted on Monday, August 23, 2010  11:46 am



I am estimating a twolevel model. I want to test hypotheses that the total effect of one variable is greater than the other (testing for tradeoffs). I am using MODEL TEST to run Wald Tests, but the test results don't match with my graphed results. I am wondering if I am using the wald test appropriately. Would appreciate your help (Mplus ver 6). Code: DEFINE: rep_sf = sf_fam*Rep; hom_sf = sf_fam*Homoph; nsm_sf = sf_fam*Needs_sim; RintE_sf = sf_fam*R_intenE; RintB_sf = sf_fam*R_intenB; ANALYSIS: TYPE=TWOLEVEL; ALGORITHM = INTEGRATION; MODEL: %WITHIN% Lcons_av on Rep(rp1) R_intenB (RgB) R_intenE (RgE) Needs_sim (ns1) Homoph (hm1) sf_fam (sf1) hom_sf (hm1_sf) nsm_sf (ns1_sf) rep_sf (rp1_sf) RintB_sf (RgB_sf) RintE_sf (RgE_sf) RI_good RI_ex RI_bal; %BETWEEN% Lcons_av on Block(rb) Order(ro); model test: rp1 + rp1_sf = hm1 + hm1_sf; !(tests if effect of Rep > Hm when sf=1) Thanks! Mahima 


In MODEL TEST, I don't see that the specification shows a greater then relationship. I don't see any indication that sf=1. And I don't think the total effect is the sum of two regression coefficients. 

Mahima Hada posted on Monday, August 23, 2010  2:15 pm



Thanks, Linda 1) I tried a "greater than" relationship test and got the error message that I cannot use <or> in model test. Hence, the equality test as a first step. And then I figured I can calculate the correct pvalue for a onesided test. 2) SF is manipulated as 0 or 1. 0 is the base, so including hm1_sf includes the effect of Hm on the DV when sf=1. 3)Thanks for the third point  this is where I am struggling with calculating the effect using wald tests. I want to test that when sf=1, what is more important Rep or Hm for my sample. Say, Y= b0 + b1*Rep + b2*Rep*sf + b3*Hm + b4*Hm*sf then for calculating relative effects for the wald tets: dY/dRep = b1 + b2 dY/dHm = b3 + b4 hence my equations. Appreciate your advice. thanks. 

Mahima posted on Monday, August 23, 2010  4:48 pm



I think I figured out the problem. The below specification of the test gives results that make sense substantively. Add adding random effects, intercepts etc. does not change the result: modeltest 0=(rp1 + rp1_sf)  (hm1 + hm1_sf); 

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