multilevel | Expose a LevelDB over the network | Runtime Evironment library

My first problem is that if I add "weight" (and its multiple values per ID) as a variable, I have the following error "boundary (singular) fit: see help('isSingular')" (even in my large dataset), while if I keep only variables with one value per patient (e.g. sex) I do not have this problem. Can anyone explain me why ?

This happens when the random effects structure is too complex to be supported by the data. Other than this it is usually not possible to identify exactly why this happens in some situations and not others. Basically the model is overfitted. A few things you can try are:

• centering the month variable
• centering other numeric variables
• fitting the model without the correlation between random slopes and intercepts, by using || instead of |

There are also some related questions and answers here:

https://stats.stackexchange.com/questions/378939/dealing-with-singular-fit-in-mixed-models/379068#379068

https://stats.stackexchange.com/questions/509892/why-is-this-linear-mixed-model-singular/509971#509971

As for the 2nd question, it sounds like you want some kind of time series model. An autoregressive model such as AR(1) might be sufficient, but this is not supported by lme4. You could try nmle instead.

Your question is too vague what you mean by "multilevel" since you don't provide an example. But for what you show, then the following will for every key, key, that is common to both dictionaries a and b, update the dictionary a[key] with the dictionary b[key]. This assumes, of course, that key values are dictionaries.

Query

• if you know the path, you can do it using a series of nested
  • $getField
  • $arrayElemAt
• you can do it in one stage with nested calls, or with many new fields like i did bellow, or with mongodb variables

*i am not sure what output you need, this goes inside to get the 2 using the indexes (if this is not what you need add if you can the expected output)

Test code here

Data

You can do the old "facet that doesn't look like a facet" trick:

The usual reason for a singular fit with mixed effects models is that either the random structure is overfitted - typically because of the inclusion of random slopes, or in the case such as this where we only have random intercepts, then the variation in the intercepts is so small that the model cannot detect it.

Looking at your model formula I suspect the issue is:

The random effect (level 2) is called intersect1 which includes each unique combination of the categorical variables (gender x marital x disability).

If I have understood this correctly, the model is equivalent to:

Seeing as you want to see which genes appear in different datasets, it sounds like an inner join might be more useful? With User ID as just a single row index.

Try this:

This is more a data manipulation question rather than a question about html/markdown. You need to get the data you want from the mod objects, once you have that the rest is easy. Here's an example of what I mean:

If your Address entity must be created with specified StateId and CountryId you need to use the original approach and force to set their value while object creation. Because, an Aggregate Root is responsible to preserve its own integrity. (See the related documentation for more info)

• I guess you also asking what will happen if the StateId does not exist in your database and if it is a just simple GUID. In such a case, if you've set your StateId as a foreign key it won't be added to your database. But if you want to query it in any way and throw an exception if it does not exist, you can create a Domain Service and check if there is a state with the given stateId and if it exists pass it to the Address constructor (if not throw an exception) and create a new address record in your database.