Message/Author 


Hi, I have the following Model, using the WLMSV estimator. Categorical are all. C_pi_bin is the IV (binary) C_K by vn167Ar vn167Br vn167Cr; C_S by c_iss1 c_iss2 c_iss3; c_wahl on c_pi_bin; C_K on c_pi_bin; C_S on c_pi_bin; c_wahl on C_S; c_wahl on C_K; C_K on C_S; MODEL INDIRECT: c_wahl ind c_pi_bin; c_wahl ind C_S; When estimating this model, I only get the estimates in the STDYX, but no s.e. and pvalues. Why is this so? When I rewrite it, so that c_pi_bin is a latent variable with only 1 indicator, that looks like this: C_PID by c_pi_bin@1; c_pi_bin@0; I get all the results, but the warning that my IV is treated as continious, but is binary. Can I interpret the results nevertheless, because it is an IV? Thanks for your help. 


I would not do C_PID by c_pi_bin@1; c_pi_bin@0; because you add the assumption of underlying normality for your binary covariate. When you have a binary covariate you don't want to use STDYX for the slopes on this covariate, but STDY. 


Hello, I have the same problem as Martin Schultze. When I add a certain construct with 3 indicators to my model and add more than one path from this construct the pvalues and s.e. would disappear in the output. I am a newbee in Mplus and may overlook something obvious but could you tell me what is the reason for that? Thanks for your help! 


With WLSMV, standard errors and pvalues for standardized parameters are not available for conditional models. 


Thanks Dr. Muthen, but what does "conditional" mean in this context. I am wondering why just this construct would make a difference while all others won't. Could you give me a hint where I can find this issue in the user manual? Thanks for your help! 


A conditional model is a model with covariates. 


Thanks for the answer! Sorry to ask again but what does this mean? I tried to find out with the help of the Users Guide, Google etc. but could not find a hint. Does it mean: 1. Something is wrong with my dataset? 2. Some constellation which makes the model not computable? 3. Do I have to leave the construct out of my model in order to get pvalues and fit indices or can I make this work somehow? 


Please send input, data, output and license number to support so we can see exactly your situation. 

RuoShui posted on Wednesday, April 02, 2014  4:55 pm



Dear Dr. Muthen, You said in the above posting "With WLSMV, standard errors and pvalues for standardized parameters are not available for conditional models". Can I be reasonably confident in applying the pvalues for unstandardized parameters to the standardized parameters? I am hoping to use the standardized parameters to compare the relative predictive value of each covaraite. Thank you very much! 


Their pvalues usually agree, but not always. 

Back to top 