Questions tagged [r-mice]
Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds).
r-mice
592
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Factor Analysis with Multiple Imputation
I have a dataset with 49 Items of a questionnaire (ordinal; 0,1,2,3,4) with 5 diagnostic group of samples (n1: 50, n2: 25; n3:30, n4:23, n5:60). However, the dataset have missings like for 10-12 ...
- 15
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Applying a function to all imputed datasets at once?
Thank you so much in advance for your help! Long story short, I am trying to get data ready for a mixed effects model after imputing 50 data sets.
I have an object BP.3_impute_list which contains 50 ...
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Caret model after multiple imputation with mice
I need help to fit a Neural network model (with caret R package) for a multiple imputed (m=5) datasets. I have performed the imputation and then run the models in the different imputed datasets. ...
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Using adjustedCurve package after multiple imputation - error: arguments of zero length and no non-missing arguments to max
I am having some issues creating adjusted cumulative incidence function using Kaplan Meier estimator after mice. I repeatedly get an error and, being fairly new to R, I am not sure what it means.
When ...
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After using ga.lasso from the miselect package how do I pool results?
ive been running multiple imputation on a dataset using the mice package creating 5 mids objects. Using those objects ive performed variable selection using the cv.galasso function from the miselect ...
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How do use multiple imputation only for intermittent missing values?
I have a dataset with time-ordered variables where I distinguish between a continuous series of missing values including the final value (monotone missing) and missing values where at least one non-...
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54
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How to visualize GAM fit with a multiple imputed dataset?
I’m working with a dataset that has missing values, and I am using multiple imputation with the mice package in R. I then fit a Generalized Additive Model (GAM) using the mgcv package on the imputed ...
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Pooling Levene’s Test in R: Why is D1 method not working? [duplicate]
I want to perform a Levene's Test on multiply imputed datasets (m=5) using the pool_leventest function in R.
First, I followed the example code to understand the procedure:
imp_data <- mice(...
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Extract the effective degrees of freedom (EDF) from a Generalized Additive Model (GAM) applied to an imputed dataset
How do you extract the pooled estimated degrees of freedom (edf) from a pooled generalized additive model ?
library(mice) # For multiple imputation
library(mgcv) # For GAM models
library(broom) # ...
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1
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How to get pooled mean by group after multiple imputation?
Assume we use the following example from the mice package:
imp <- mice(nhanes, m=5, print=FALSE, seed=55152)
I want to obtain the means of nhanes$chl grouped by nhanes$hyp. Without using multiple ...
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Plot ROC and nomogram after multiple imputation
How to do ROC and nomogram plotting after multiple imputation with the "mice" package？
I found online that I could use the "pool_performance" function for calibration curve ...
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How do I solve module 'numpy' has no attribute 'float'. Error while using MICE?
Here's my code
1
2
Here's some data
3 - data sample
Here's knn imputation result
4 - knn imputation
Hi, I'm a beginner in machine learning. While filling in the missing values in the data using MICE, ...
- 1
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Multiple imputation (MICE)
In my study, I want to examine the association between psychosocial factors and death and calculate the incidence rates of death by the psychosocial factors at baseline. However, some of the ...
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Imputing NA values using Mice while also using a column 'Total' as a condition for the imputation R
ID
Year
Maths
Eng
Total
1
2010
20
15
35
1
2011
17
NA
40
2
2010
NA
NA
46
2
2011
NA
NA
39
3
2010
NA
15
41
3
2011
18
NA
43
4
2010
NA
15
NA
4
2011
NA
18
NA
Hello, I am trying to use the mice ...
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Fixed Effects Panel Data Models with Multiply Imputed Data
I used the mice package to create 5 implicates of a dataset. I am interested in using fixest:feols() to estimate a fixed effects model that looks like this
m1 <- with(mi_data,
...
