|
|
 |
| Are growth models nested? |
 
|
| Message/Author |
|
|
|
|
Dear Dr Muthen,
I was wondering whether a growth model with only a linear slope is nested in a model including a linear and quadratic slope. I.e., could these two models be compared using the chi-square test?
Or should I use AIC and BIC for model comparison?
Thank you for your advice!
Sincerely,
Aurelie |
|
|
|
|
| If the quadratic slope has zero variance (but non-zero mean) you can use the chi-2 difference test. With free variance, the variance=0 precludes correct chi-2 diff testing. Using AIC or BIC is good. |
|
|
|
|
Dear dr Muthen,
Thank you for reply.
What about adding a dependent variable (y) to the between-level in M1? This variable is already a dependent variable on the within level in the M0.
%within%
m on x1;
y on m x1;
%between%
m on x2;
y on x2; !NEW PATH
Is there a 'rule of thumb' to know when models are nested? Or is there some way to check this in the output?
thank you!
Cheers,
Aurelie |
|
|
|
|
If M0 has a variance of y on Between then it is nested within M1 which adds a path. M0 simply says that y on x2 = 0.
There is a 2010 Psych methods article by Bentler and Satorra that describes a method for checking nesting. |
|
|
|
|
Dear dr Muthen,
With my GMM (default settings with regard to growth factor variances), I received a warning message with the 4-class model related to a not positive definite PSI. I followed your advice, posted in another thread, of constricting the variance of the slope @0 because my slope variance was not significant for the 4-class model. After that, the error message indeed disappeared.
However, for the 1-class and 2-class default GMM models, I did have significant slope variances (for the 3-class model I did not).
With regard to reporting the results in my paper, I wonder whether I should report:
(1) 1-class, 2-class and 3-class results for the models with default settings regarding growth factor variance; and 4-class results for the model with s@0 (because I first received the error message for the 4-class model)
or
(2) reports results for ALL models with s@0, so starting from the 1-class model.
(sidenote: BIC is very comparable for default models and models with s@0, for all classes)
I feel like this question might be related to models being nested; I believe these models are not nested and as such I should start with the 1-class model with s@0 and report those results (so my guess is that I should use option (2)). Am I right? |
|
|
|
|
| I would go with (1). |
|
|
|
|
Thank you for your reply.
I am still wondering if, when I go with (1), it would not be wrong to report e.g. the LMR-LRT and BLRT values for a 3-class versus 2-class model, as I worked with s@0 for the 3-class model whereas I did not constrict the slope factor variance for the 2-class model.
Because when I ask for the output of TECH11 and TECH14 for the 3-class s@0 model, it compares this model with a 2-class s@0 model, right? How should I deal with this, as I used a 2-class model without the constricted slope factor variance?
Thank you in advance. |
|
|
|
|
As for your first paragraph, I think it would be wrong.
I would simply use BIC. |
|
|
| Back to top |
|
|
