Comments (2)
ngreifer
commented on July 28, 2024
Levels of a factor are dropped in a regression when there are no units with those values or when they are linearly dependent on other variables (including levels of the same factor). What likely happened is that the matching changed the distribution of the covariates to yield one of the above phenomena. For example, it may be that after matching, all of the observations for a given breeder have the same region, and vice-versa, so that that level of breeder is redundant after including region in the model. You should examine the match.data() output to see if a phenomenon of this type is occurring.
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wimul
commented on July 28, 2024
Thanks, @ngreifer. I'll check and will let you know.
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Related Issues (20)
- optmatch missing from CRAN HOT 2
- Memory allocation problem with method="full" in matchit : Error: (from optmatch) result would exceed 2^31-1 bytes
- weight to initial variable to achieve 100% matching for certain variable
- ratio = 0.5 is not supported HOT 1
- Propensity score weigths & ordinal variables HOT 4
- MatchIt should warn against matching without caliper HOT 1
- Possible Infinite Loop when Exact Matching for Method = 'Nearest' HOT 1
- Errors from using random forest HOT 2
- Error - CEM with NULL in k2k.method HOT 4
- Improve error output of `matchit()` HOT 2
- How larger is the value of caliper by default when the method was set with “nearest” . HOT 4
- "antiexact" not working as expected HOT 1
- Why is `ratio=2` different from two 1:1 iterations HOT 3
- How does MatchIt calculate Mean for factors/categories? HOT 4
- Interpretation balance statistics HOT 1
- cardinality matching with exact match HOT 2
- What is the meaning of a negative Standardized mean difference (SMD)? HOT 1
- nn table disappeared? HOT 1
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