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Description
mira objects (MultiplyImputedRepeatedAnalyses) are created when pooling analysis over several imputations.
These object are created with themice package, which is a reference for multiple imputation in R.
Unfortunately, such objects are not supported (yet) in thereport package.
library(mice)library(report)imp<- mice(airquality,m=5,maxit=5,seed=123)mod<- with(imp, lm(Ozone~Solar.R+Wind+Temp+Month))report(mod)#> Error: Oops, objects of class [mira, matrix] are not supported (yet) by report() :(#>#> Want to help? Check out https://easystats.github.io/report/articles/new_models.html
Created on 2025-08-27 withreprex v2.1.0
However, each individual model (i.e. the models fitted on single imputations) works with thereport() function, so making it work with themira object should not be too difficult I think.
fit<-mod$analyses[[1]]report(fit)#> Warning: Could not recover model data from environment. Please make sure your#> data is available in your workspace.#> Trying to retrieve data from the model frame now.#> We fitted a linear model (estimated using OLS) to predict Ozone with Solar.R,#> Wind, Temp and Month (formula: Ozone ~ Solar.R + Wind + Temp + Month). The#> model explains a statistically significant and substantial proportion of#> variance (R2 = 0.54, F(4, 148) = 42.59, p < .001, adj. R2 = 0.52). The model's#> intercept, corresponding to Solar.R = 0, Wind = 0, Temp = 0 and Month = 0, is#> at -52.03 (95% CI [-91.71, -12.36], t(148) = -2.59, p = 0.011). Within this#> model:#>#> - The effect of Solar R is statistically non-significant and positive (beta =#> 0.02, 95% CI [-0.02, 0.06], t(148) = 0.96, p = 0.336; Std. beta = 0.06, 95% CI#> [-0.06, 0.18])#> - The effect of Wind is statistically significant and negative (beta = -3.19,#> 95% CI [-4.32, -2.06], t(148) = -5.58, p < .001; Std. beta = -0.35, 95% CI#> [-0.48, -0.23])#> - The effect of Temp is statistically significant and positive (beta = 1.71,#> 95% CI [1.22, 2.20], t(148) = 6.95, p < .001; Std. beta = 0.51, 95% CI [0.36,#> 0.65])#> - The effect of Month is statistically non-significant and negative (beta =#> -1.79, 95% CI [-4.59, 1.01], t(148) = -1.26, p = 0.208; Std. beta = -0.08, 95%#> CI [-0.20, 0.04])#>#> Standardized parameters were obtained by fitting the model on a standardized#> version of the dataset. 95% Confidence Intervals (CIs) and p-values were#> computed using a Wald t-distribution approximation.
Created on 2025-08-27 withreprex v2.1.0