Comments (2)
alexanderrobitzsch
commented on September 25, 2024
"The mice algorithm will estimate the forward stepwise regression to predict "chl" on a bootstrap version of the observed values on "chl" at every iteration."
yes.
"The predictors that the forward stepwise algorithm will scan are the ones defined by the predictor matrix provided in the mice call (the default one in this case)."
yes.
"At every iteration, the step-wise algorithm might select different predictors for the imputation model of "chl"."
yes.
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EdoardoCostantini
commented on September 25, 2024
Great. Thank you for responding so quickly.
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Related Issues (20)
- micombine.cor with Fisher transform? HOT 2
- mi.anova intercept? HOT 3
- groupwise imputation with ml.lmer? HOT 3
- summary() subscript out of bounds HOT 2
- subscript out of bounds HOT 5
- mice.impute.bygroup - outs of bounds HOT 9
- glm.cluster yielding wrong p-values HOT 3
- not able to impute using ml.lmer in v 3.3? HOT 3
- glm.cluster reliant on/generates NULL wgt__ value HOT 3
- Error when using 2lonly.function with polyreg HOT 2
- datlist2mids fails after subsetting if factors don't still contain all levels HOT 1
- pooling error with nested imputations HOT 1
- Memory limit error with weighted imputation HOT 1
- Error in weighted predictive mean matching method HOT 1
- different variable imputed values using same predictor variable - 2l.pmm HOT 3
- `mice.impute.ml.lmer` on large three-level dataset: `"binary"` logistic model returns error, 'hangs' when adding random slopes or interactions HOT 1
- Is it possible to convert mids objects to an Amelia object? HOT 2
- post hoc test for mi.anova
- Possible error in example for ml.lmer documentation HOT 1
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