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 Ernest Boakye-Dankwa posted on Thursday, October 20, 2016 - 10:00 pm
Dear All,

I am a new user of Mplus and currently using version 7. I am investigating the neighbourhood environment's influence people's activity patterns (walking behaviour). I have individual-level (level-1) and neighbourhood-level(level-2) factors. I read a paper by Henry and Muthen (2010)
"Multilevel Latent Class Analysis: An Application of Adolescent Smoking Typologies with Individual and Contextual Predictors" that used MLCM.

I am considering using that approach in my data analysis for this reason: to identify the homogeneous neighbourhood typologies and as well as accounting for nested structured in the data set.

Is it appropriate to use the latent classes in my analysis as the main exposure variables and walking behaviour as my outcome variable?

 Bengt O. Muthen posted on Friday, October 21, 2016 - 12:44 pm
The neighborhood typologies would be captured by cb, a between-level latent class variable.

Using cb as exposure and walking behavior as outcome is accomplished by the mean of the between-level part of the walking behavior variable varying across the cb classes.
 Ernest Boakye-Dankwa posted on Sunday, October 23, 2016 - 6:14 pm
Hello Dr. Muthen,

Thank you for your quick response and explanation! I would like to know if there is any literature other than Henry and Muthen (2010) or excerpt of a book chapter available online to familiarise myself with? That is, where the author used for example "cb" as an exposure variable and individual-level factor (for example, activity patterns) as an outcome variable?

 Bengt O. Muthen posted on Monday, October 24, 2016 - 10:47 am
No. But the UG has examples where a latent class variable influences a distal outcome. See e.g. UG ex 8.6. You can piece it together starting from that.
 Ernest Boakye-Dankwa posted on Friday, October 28, 2016 - 11:44 pm
Dear Dr Muthen,

Thank you for the suggestion. I just identified that the example 10.2 in the UG "Two-level mixture regression for a continuous dependent variable with a between categorical latent variable"? may be able to assist my work. My reason is that I am investigating on how neighbourhood environmental features influence a person's activity patterns, which means that I should be focusing on latent classes at the neighbourhood level instead of individual-level.

In that example, both level-one and level-two factors are all continuous variables. What case in point may fit a situation where the dataset has both categorical and continuous variables?

Thank you for your support!

 Bengt O. Muthen posted on Saturday, October 29, 2016 - 3:36 pm
That combination presents no special input difficulties. Just put the categorical variables on the Categorical list.
 Ernest Boakye-Dankwa posted on Sunday, October 30, 2016 - 8:22 pm
Thank you, Dr. Muthen for your support.
 Bengt O. Muthen posted on Wednesday, November 02, 2016 - 5:38 pm
 Ernest Boakye-Dankwa posted on Tuesday, November 29, 2016 - 10:36 pm
Hello Dr. Muthen,

I am practising how to get the following plots; i.e., either figure 8 or figure 9 in Henry and Muthen (2010). Is there a specific Mplus code to get the bar chart in either figure 8 or figure 9 having both levels on the same plot?

Thank you for your support!

 Bengt O. Muthen posted on Thursday, December 01, 2016 - 10:51 am
No, this was done outside Mplus.
 Ernest Boakye-Dankwa posted on Thursday, December 01, 2016 - 2:29 pm
Okay! Thank you, Dr. Muthen.
 fritzie cacas posted on Monday, April 24, 2017 - 11:51 am
Hello sir,

I am using the 7.4 demo version and I am doing a multilevel lca. I have a question to ask sir. I have
6 indicators, student level covariate which is gender, and courses as my level 2 or cluster.

STARTS = 100 50;

is my model correct sir? what does c#1 mean?
 Linda K. Muthen posted on Monday, April 24, 2017 - 11:54 am
See Example 10.4 in the user's guide.
 fritzie cacas posted on Monday, April 24, 2017 - 12:03 pm
I'm sorry sir but can you explain it to me. I am new to Multilevel lca and this is my first time using MPlus.
As from what I've understand describes the student and course level. But I have no idea what is C#1.
Am I doing the right analysis sir?
 Linda K. Muthen posted on Monday, April 24, 2017 - 1:32 pm
If you are new to mixture modeling, you should the Topic 6 course video on the website where all of this is described.
 Djangou C posted on Monday, May 22, 2017 - 4:23 pm
Dear Mplus team,
I am running multilevel latent class analysis and I have some questions regarding which model to use. According to Henry and Muthen (2010), indicators specific random effects can be included in the formation of the latent classes. I was wondering if there was any rule regarding their inclusion in the model. Do we know the consequences of omitting these indicators in class formation and parameter estimates? I couldn’t locate any paper that discussed this issue.
Thank you for your help.
 Bengt O. Muthen posted on Tuesday, May 23, 2017 - 5:47 pm
No rules that I know of. But if these indicator-specific variances are significant I would include them.
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