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

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.